A mobile-agent-based wireless sensing network for structural monitoring applications

International Nuclear Information System (INIS)

Taylor, Stuart G; Farinholt, Kevin M; Figueiredo, Eloi; Moro, Erik A; Park, Gyuhae; Farrar, Charles R; Flynn, Eric B; Mascarenas, David L; Todd, Michael D

2009-01-01

A new wireless sensing network paradigm is presented for structural monitoring applications. In this approach, both power and data interrogation commands are conveyed via a mobile agent that is sent to sensor nodes to perform intended interrogations, which can alleviate several limitations of the traditional sensing networks. Furthermore, the mobile agent provides computational power to make near real-time assessments on the structural conditions. This paper will discuss such prototype systems, which are used to interrogate impedance-based sensors for structural health monitoring applications. Our wireless sensor node is specifically designed to accept various energy sources, including wireless energy transmission, and to be wirelessly triggered on an as-needed basis by the mobile agent or other sensor nodes. The capabilities of this proposed sensing network paradigm are demonstrated in the laboratory and the field

High Resolution Sensing and Control of Urban Water Networks

Science.gov (United States)

Bartos, M. D.; Wong, B. P.; Kerkez, B.

2016-12-01

We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.

Participatory sensing as an enabler for self-organisation in future cellular networks

International Nuclear Information System (INIS)

Imran, Muhammad Ali; Onireti, Oluwakayode; Imran, Ali

2013-01-01

In this short review paper we summarise the emerging challenges in the field of participatory sensing for the self-organisation of the next generation of wireless cellular networks. We identify the potential of participatory sensing in enabling the self-organisation, deployment optimisation and radio resource management of wireless cellular networks. We also highlight how this approach can meet the future goals for the next generation of cellular system in terms of infrastructure sharing, management of multiple radio access techniques, flexible usage of spectrum and efficient management of very small data cells

Smart Sensor Network System For Environment Monitoring

Directory of Open Access Journals (Sweden)

Javed Ali Baloch

2012-07-01

Full Text Available SSN (Smart Sensor Network systems could be used to monitor buildings with modern infrastructure, plant sites with chemical pollution, horticulture, natural habitat, wastewater management and modern transport system. To sense attributes of phenomena and make decisions on the basis of the sensed value is the primary goal of such systems. In this paper a Smart Spatially aware sensor system is presented. A smart system, which could continuously monitor the network to observe the functionality and trigger, alerts to the base station if a change in the system occurs and provide feedback periodically, on demand or even continuously depending on the nature of the application. The results of the simulation trials presented in this paper exhibit the performance of a Smart Spatially Aware Sensor Networks.

A patch-based convolutional neural network for remote sensing image classification.

Science.gov (United States)

Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

2017-11-01

Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

Science.gov (United States)

Brown, Molly E.; Brickley, Elizabeth B.

2011-01-01

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Enhancing Sensing and Channel Access in Cognitive Radio Networks

KAUST Repository

Hamza, Doha R.

2014-06-18

Cognitive radio technology is a promising technology to solve the wireless spectrum scarcity problem by intelligently allowing secondary, or unlicensed, users access to the primary, licensed, users\\' frequency bands. Cognitive technology involves two main tasks: 1) sensing the wireless medium to assess the presence of the primary users and 2) designing secondary spectrum access techniques that maximize the secondary users\\' benefits while maintaining the primary users\\' privileged status. On the spectrum sensing side, we make two contributions. First, we maximize a utility function representing the secondary throughput while constraining the collision probability with the primary below a certain value. We optimize therein the channel sensing time, the sensing decision threshold, the channel probing time, together with the channel sensing order for wideband primary channels. Second, we design a cooperative spectrum sensing technique termed sensing with equal gain combining whereby cognitive radios simultaneously transmit their sensing results to the fusion center over multipath fading reporting channels. The proposed scheme is shown to outperform orthogonal reporting systems in terms of achievable secondary throughput and to be robust against phase and synchronization errors. On the spectrum access side, we make four contributions. First, we design a secondary scheduling scheme with the goal of minimizing the secondary queueing delay under constraints on the average secondary transmit power and the maximum tolerable primary outage probability. Second, we design another secondary scheduling scheme based on the spectrum sensing results and the primary automatic repeat request feedback. The optimal medium access probabilities are obtained via maximizing the secondary throughput subject to constraints that guarantee quality of service parameters for the primary. Third, we propose a three-message superposition coding scheme to maximize the secondary throughput without

RSComPro: An Open Communication Protocol for Remote Sensing Systems

DEFF Research Database (Denmark)

Vasiljevic, Nikola; Trujillo, Juan-José

The remote sensing protocol (RSComPro) is a communication protocol, which has been developed for controlling multiple remote sensing systems simultaneously through a UDP/IP and TPC/IP network. This protocol is meant to be open to the remote sensing community. The scope is the implementation of so...

A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

Directory of Open Access Journals (Sweden)

Jorge Sá Silva

2012-02-01

Full Text Available As the Internet evolved, social networks (such as Facebook have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype.

A Web Service-based framework model for people-centric sensing applications applied to social networking.

Science.gov (United States)

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

Health Participatory Sensing Networks

Directory of Open Access Journals (Sweden)

Andrew Clarke

2014-01-01

Full Text Available The use of participatory sensing in relation to the capture of health-related data is rapidly becoming a possibility due to the widespread consumer adoption of emerging mobile computing technologies and sensing platforms. This has the potential to revolutionize data collection for population health, aspects of epidemiology, and health-related e-Science applications and as we will describe, provide new public health intervention capabilities, with the classifications and capabilities of such participatory sensing platforms only just beginning to be explored. Such a development will have important benefits for access to near real-time, large-scale, up to population-scale data collection. However, there are also numerous issues to be addressed first: provision of stringent anonymity and privacy within these methodologies, user interface issues, and the related issue of how to incentivize participants and address barriers/concerns over participation. To provide a step towards describing these aspects, in this paper we present a first classification of health participatory sensing models, a novel contribution to the literature, and provide a conceptual reference architecture for health participatory sensing networks (HPSNs and user interaction example case study.

Cognitive networked sensing and big data

CERN Document Server

Qiu, Robert

2013-01-01

Wireless Distributed Computing and Cognitive Sensing defines high-dimensional data processing in the context of wireless distributed computing and cognitive sensing. This book presents the challenges that are unique to this area such as synchronization caused by the high mobility of the nodes. The author will discuss the integration of software defined radio implementation and testbed development. The book will also bridge new research results and contextual reviews. Also the author provides an examination of large cognitive radio network; hardware testbed; distributed sensing; and distributed

Centralized cooperative spectrum sensing for ad-hoc disaster relief network clusters

DEFF Research Database (Denmark)

Pratas, Nuno; Marchetti, Nicola; Prasad, Neeli R.

2010-01-01

Disaster relief networks have to be highly adaptable and resilient. Cognitive radio enhanced ad-hoc architecture have been put forward as a candidate to enable such networks. Spectrum sensing is the cornerstone of the cognitive radio paradigm, and it has been the target of intensive research....... The main common conclusion was that the achievable spectrum sensing accuracy can be greatly enhanced through the use of cooperative sensing schemes. When considering applying Cognitive Radio to ad-hoc disaster relief networks, spectrum sensing cooperative schemes are paramount. A centralized cluster...

Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks

Science.gov (United States)

Wang, Wenkai; Li, Husheng; Sun, Yan(Lindsay); Han, Zhu

2009-12-01

Cognitive radio is a revolutionary paradigm to migrate the spectrum scarcity problem in wireless networks. In cognitive radio networks, collaborative spectrum sensing is considered as an effective method to improve the performance of primary user detection. For current collaborative spectrum sensing schemes, secondary users are usually assumed to report their sensing information honestly. However, compromised nodes can send false sensing information to mislead the system. In this paper, we study the detection of untrustworthy secondary users in cognitive radio networks. We first analyze the case when there is only one compromised node in collaborative spectrum sensing schemes. Then we investigate the scenario that there are multiple compromised nodes. Defense schemes are proposed to detect malicious nodes according to their reporting histories. We calculate the suspicious level of all nodes based on their reports. The reports from nodes with high suspicious levels will be excluded in decision-making. Compared with existing defense methods, the proposed scheme can effectively differentiate malicious nodes and honest nodes. As a result, it can significantly improve the performance of collaborative sensing. For example, when there are 10 secondary users, with the primary user detection rate being equal to 0.99, one malicious user can make the false alarm rate [InlineEquation not available: see fulltext.] increase to 72%. The proposed scheme can reduce it to 5%. Two malicious users can make [InlineEquation not available: see fulltext.] increase to 85% and the proposed scheme reduces it to 8%.

A mobile sensing system for structural health monitoring: design and validation

International Nuclear Information System (INIS)

Zhu, Dapeng; Yi, Xiaohua; Wang, Yang; Lee, Kok-Meng; Guo, Jiajie

2010-01-01

This paper describes a new approach using mobile sensor networks for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper first describes the design of a mobile sensing node that is capable of maneuvering on structures built with ferromagnetic materials. The mobile sensing node can also attach/detach an accelerometer onto/from the structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments. Two mobile sensing nodes are adopted for navigating on a steel portal frame and providing dense acceleration measurements. Transmissibility function analysis is conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes in the use of mobile sensors for future structural health monitoring

A mobile sensing system for structural health monitoring: design and validation

Science.gov (United States)

Zhu, Dapeng; Yi, Xiaohua; Wang, Yang; Lee, Kok-Meng; Guo, Jiajie

2010-05-01

This paper describes a new approach using mobile sensor networks for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper first describes the design of a mobile sensing node that is capable of maneuvering on structures built with ferromagnetic materials. The mobile sensing node can also attach/detach an accelerometer onto/from the structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments. Two mobile sensing nodes are adopted for navigating on a steel portal frame and providing dense acceleration measurements. Transmissibility function analysis is conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes in the use of mobile sensors for future structural health monitoring.

Optimized Reputable Sensing Participants Extraction for Participatory Sensor Networks

Directory of Open Access Journals (Sweden)

Weiwei Yuan

2014-01-01

Full Text Available By collecting data via sensors embedded personal smart devices, sensing participants play a key role in participatory sensor networks. Using information provided by reputable sensing participants ensures the reliability of participatory sensing data. Setting a threshold for the reputation, and those whose reputations are bigger than this value are regarded as reputable. The bigger the threshold value is, the more reliable the extracted reputable sensing participant is. However, if the threshold value is too big, only very limited participatory sensing data can be involved. This may cause unexpected bias in information collection. Existing works did not consider the relationship between the reliability of extracted reputable sensing participants and the ratio of usable participatory sensing data. In this work, we propose a criterion for optimized reputable sensing participant extraction in participatory sensor networks. This is achieved based on the mathematical analysis on the ratio of available participatory sensing data and the reliability of extracted reputable sensing participants. Our suggested threshold value for reputable sensing participant extraction is only related to the power of sensing participant’s reputation distribution. It is easy to be applied in real applications. Simulation results tested on real application data further verified the effectiveness of our proposed method.

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems.

Science.gov (United States)

Wu, Jun; Su, Zhou; Wang, Shen; Li, Jianhua

2017-07-30

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on "friend" relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

Three neural network based sensor systems for environmental monitoring

International Nuclear Information System (INIS)

Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

1994-05-01

Compact, portable systems capable of quickly identifying contaminants in the field are of great importance when monitoring the environment. One of the missions of the Pacific Northwest Laboratory is to examine and develop new technologies for environmental restoration and waste management at the Hanford Site. In this paper, three prototype sensing systems are discussed. These prototypes are composed of sensing elements, data acquisition system, computer, and neural network implemented in software, and are capable of automatically identifying contaminants. The first system employs an array of tin-oxide gas sensors and is used to identify chemical vapors. The second system employs an array of optical sensors and is used to identify the composition of chemical dyes in liquids. The third system contains a portable gamma-ray spectrometer and is used to identify radioactive isotopes. In these systems, the neural network is used to identify the composition of the sensed contaminant. With a neural network, the intense computation takes place during the training process. Once the network is trained, operation consists of propagating the data through the network. Since the computation involved during operation consists of vector-matrix multiplication and application of look-up tables unknown samples can be rapidly identified in the field

Sense, decide, act, communicate (SDAC): next generation of smart sensor systems

Science.gov (United States)

Berry, Nina; Davis, Jesse; Ko, Teresa H.; Kyker, Ron; Pate, Ron; Stark, Doug; Stinnett, Regan; Baker, James; Cushner, Adam; Van Dyke, Colin; Kyckelhahn, Brian

2004-09-01

The recent war on terrorism and increased urban warfare has been a major catalysis for increased interest in the development of disposable unattended wireless ground sensors. While the application of these sensors to hostile domains has been generally governed by specific tasks, this research explores a unique paradigm capitalizing on the fundamental functionality related to sensor systems. This functionality includes a sensors ability to Sense - multi-modal sensing of environmental events, Decide - smart analysis of sensor data, Act - response to environmental events, and Communication - internal to system and external to humans (SDAC). The main concept behind SDAC sensor systems is to integrate the hardware, software, and networking to generate 'knowledge and not just data'. This research explores the usage of wireless SDAC units to collectively make up a sensor system capable of persistent, adaptive, and autonomous behavior. These systems are base on the evaluation of scenarios and existing systems covering various domains. This paper presents a promising view of sensor network characteristics, which will eventually yield smart (intelligent collectives) network arrays of SDAC sensing units generally applicable to multiple related domains. This paper will also discuss and evaluate the demonstration system developed to test the concepts related to SDAC systems.

Bridge SHM system based on fiber optical sensing technology

Science.gov (United States)

Li, Sheng; Fan, Dian; Fu, Jiang-hua; Huang, Xing; Jiang, De-sheng

2015-09-01

The latest progress of our lab in recent 10 years on the area of bridge structural health monitoring (SHM) based on optical fiber sensing technology is introduced. Firstly, in the part of sensing technology, optical fiber force test-ring, optical fiber vibration sensor, optical fiber smart cable, optical fiber prestressing loss monitoring method and optical fiber continuous curve mode inspection system are developed, which not only rich the sensor types, but also provides new monitoring means that are needed for the bridge health monitoring system. Secondly, in the optical fiber sensing network and computer system platform, the monitoring system architecture model is designed to effectively meet the integration scale and effect requirement of engineering application, especially the bridge expert system proposed integration of sensing information and informatization manual inspection to realize the mode of multi index intelligence and practical monitoring, diagnosis and evaluation. Finally, the Jingyue bridge monitoring system as the representative, the research on the technology of engineering applications are given.

Rapid deployable global sensing hazard alert system

Science.gov (United States)

Cordaro, Joseph V; Tibrea, Steven L; Shull, Davis J; Coleman, Jerry T; Shuler, James M

2015-04-28

A rapid deployable global sensing hazard alert system and associated methods of operation are provided. An exemplary system includes a central command, a wireless backhaul network, and a remote monitoring unit. The remote monitoring unit can include a positioning system configured to determine a position of the remote monitoring unit based on one or more signals received from one or more satellites located in Low Earth Orbit. The wireless backhaul network can provide bidirectional communication capability independent of cellular telecommunication networks and the Internet. An exemplary method includes instructing at least one of a plurality of remote monitoring units to provide an alert based at least in part on a location of a hazard and a plurality of positions respectively associated with the plurality of remote monitoring units.

Stretchable Electronic Sensors of Nanocomposite Network Films for Ultrasensitive Chemical Vapor Sensing.

Science.gov (United States)

Yan, Hong; Zhong, Mengjuan; Lv, Ze; Wan, Pengbo

2017-11-01

A stretchable, transparent, and body-attachable chemical sensor is assembled from the stretchable nanocomposite network film for ultrasensitive chemical vapor sensing. The stretchable nanocomposite network film is fabricated by in situ preparation of polyaniline/MoS 2 (PANI/MoS 2 ) nanocomposite in MoS 2 suspension and simultaneously nanocomposite deposition onto prestrain elastomeric polydimethylsiloxane substrate. The assembled stretchable electronic sensor demonstrates ultrasensitive sensing performance as low as 50 ppb, robust sensing stability, and reliable stretchability for high-performance chemical vapor sensing. The ultrasensitive sensing performance of the stretchable electronic sensors could be ascribed to the synergistic sensing advantages of MoS 2 and PANI, higher specific surface area, the reliable sensing channels of interconnected network, and the effectively exposed sensing materials. It is expected to hold great promise for assembling various flexible stretchable chemical vapor sensors with ultrasensitive sensing performance, superior sensing stability, reliable stretchability, and robust portability to be potentially integrated into wearable electronics for real-time monitoring of environment safety and human healthcare. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

Directory of Open Access Journals (Sweden)

Jun Wu

2017-07-01

Full Text Available Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

Science.gov (United States)

Wu, Jun; Su, Zhou; Li, Jianhua

2017-01-01

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems. PMID:28758943

Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing

Directory of Open Access Journals (Sweden)

Caiyun Huang

2014-07-01

Full Text Available As a newly proposed theory, compressive sensing (CS is commonly used in signal processing area. This paper investigates the applications of compressed sensing (CS in wireless sensor networks (WSNs. First, the development and research status of compressed sensing technology and wireless sensor networks are described, then a detailed investigation of WSNs research based on CS are conducted from aspects of data fusion, signal acquisition, signal routing transmission, and signal reconstruction. At the end of the paper, we conclude our survey and point out the possible future research directions.

An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network

Energy Technology Data Exchange (ETDEWEB)

Dong, Bing; Lam, Khee Poh; Zhang, Rui; Chiou, Yun-Shang [Center for Building Performance and Diagnostics, Carnegie Mellon University, Pittsburgh, PA 15213 (United States); Andrews, Burton; Hoeynck, Michael; Benitez, Diego [Research and Technology Center, Robert BOSCH LLC, Pittsburgh, PA 15212 (United States)

2010-07-15

This paper describes a large-scale wireless and wired environmental sensor network test-bed and its application to occupancy detection in an open-plan office building. Detection of occupant presence has been used extensively in built environments for applications such as demand-controlled ventilation and security; however, the ability to discern the actual number of people in a room is beyond the scope of current sensing techniques. To address this problem, a complex sensor network is deployed in the Robert L. Preger Intelligent Workplace comprising a wireless ambient-sensing system, a wired carbon dioxide sensing system, and a wired indoor air quality sensing system. A wired camera network is implemented as well for establishing true occupancy levels to be used as ground truth information for deriving algorithmic relationships with the environment conditions. To our knowledge, this extensive and diverse ambient-sensing infrastructure of the ITEST setup as well as the continuous data-collection capability is unprecedented. Final results indicate that there are significant correlations between measured environmental conditions and occupancy status. An average of 73% accuracy on the occupancy number detection was achieved by Hidden Markov Models during testing periods. This paper serves as an exploration to the research of ITEST for occupancy detection in offices. In addition, its utility extends to a wide variety of other building technology research areas such as human-centered environmental control, security, energy efficient and sustainable green buildings. (author)

Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

Directory of Open Access Journals (Sweden)

Laisen Nie

2018-01-01

Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

Handbook of sensor networks compact wireless and wired sensing systems

CERN Document Server

Ilyas, Mohammad

2004-01-01

INTRODUCTION Opportunities and Challenges in Wireless Sensor Networks, M. Haenggi, Next Generation Technologies to Enable Sensor Networks, J. I.  Goodman, A. I. Reuther, and D. R. Martinez Sensor Networks Management, L. B. Ruiz, J. M. Nogueira, and A. A. F. Loureiro Models for Programmability in Sensor Networks, A. Boulis Miniaturizing Sensor Networks with MEMS, Brett Warneke A Taxonomy of Routing Techniques in Wireless Sensor Networks, J. N. Al-Karaki and A. E. Kamal Artificial Perceptual Systems, A. Loutfi, M. Lindquist, and P. Wide APPLICATIONS Sensor Network Architecture and Appl

Path Network Recovery Using Remote Sensing Data and Geospatial-Temporal Semantic Graphs

Energy Technology Data Exchange (ETDEWEB)

McLendon, William C.,; Brost, Randolph

2016-05-01

Remote sensing systems produce large volumes of high-resolution images that are difficult to search. The GeoGraphy (pronounced Geo-Graph-y) framework [2, 20] encodes remote sensing imagery into a geospatial-temporal semantic graph representation to enable high level semantic searches to be performed. Typically scene objects such as buildings and trees tend to be shaped like blocks with few holes, but other shapes generated from path networks tend to have a large number of holes and can span a large geographic region due to their connectedness. For example, we have a dataset covering the city of Philadelphia in which there is a single road network node spanning a 6 mile x 8 mile region. Even a simple question such as "find two houses near the same street" might give unexpected results. More generally, nodes arising from networks of paths (roads, sidewalks, trails, etc.) require additional processing to make them useful for searches in GeoGraphy. We have assigned the term Path Network Recovery to this process. Path Network Recovery is a three-step process involving (1) partitioning the network node into segments, (2) repairing broken path segments interrupted by occlusions or sensor noise, and (3) adding path-aware search semantics into GeoQuestions. This report covers the path network recovery process, how it is used, and some example use cases of the current capabilities.

Cognitive radio networks efficient resource allocation in cooperative sensing, cellular communications, high-speed vehicles, and smart grid

CERN Document Server

Jiang, Tao; Cao, Yang

2015-01-01

PrefaceAcknowledgmentsAbout the AuthorsIntroductionCognitive Radio-Based NetworksOpportunistic Spectrum Access NetworksCognitive Radio Networks with Cooperative SensingCognitive Radio Networks for Cellular CommunicationsCognitive Radio Networks for High-Speed VehiclesCognitive Radio Networks for a Smart GridContent and OrganizationTransmission Slot Allocation in an Opportunistic Spectrum Access NetworkSingle-User Single-Channel System ModelProbabilistic Slot Allocation SchemeOptimal Probabilistic Slot AllocationBaseline PerformanceExponential DistributionHyper-Erlang DistributionPerformance An

Wide-area remote-sensing system of pollution and gas dispersal by near-infrared absorption based on low-loss optical fiber network

Science.gov (United States)

Inaba, H.

1986-01-01

An all optical remote sensing system utilizing long distance, ultralow loss optical fiber networks is studied and discussed for near infrared absorption measurements of combustible and/or explosive gases such as CH4 and C3H8 in our environment, including experimental results achieved in a diameter more than 20 km. The use of a near infrared wavelength range is emphasized.

A packet-based dual-rate PID control strategy for a slow-rate sensing Networked Control System.

Science.gov (United States)

Cuenca, A; Alcaina, J; Salt, J; Casanova, V; Pizá, R

2018-05-01

This paper introduces a packet-based dual-rate control strategy to face time-varying network-induced delays, packet dropouts and packet disorder in a Networked Control System. Slow-rate sensing enables to achieve energy saving and to avoid packet disorder. Fast-rate actuation makes reaching the desired control performance possible. The dual-rate PID controller is split into two parts: a slow-rate PI controller located at the remote side (with no permanent communication to the plant) and a fast-rate PD controller located at the local side. The remote side also includes a prediction stage in order to generate the packet of future, estimated slow-rate control actions. These actions are sent to the local side and converted to fast-rate ones to be used when a packet does not arrive at this side due to the network-induced delay or due to occurring dropouts. The proposed control solution is able to approximately reach the nominal (no-delay, no-dropout) performance despite the existence of time-varying delays and packet dropouts. Control system stability is ensured in terms of probabilistic Linear Matrix Inequalities (LMIs). Via real-time control for a Cartesian robot, results clearly reveal the superiority of the control solution compared to a previous proposal by authors. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Equal gain combining for cooperative spectrum sensing in cognitive radio networks

KAUST Repository

Hamza, Doha R.

2014-08-01

Sensing with equal gain combining (SEGC), a novel cooperative spectrum sensing technique for cognitive radio networks, is proposed. Cognitive radios simultaneously transmit their sensing results to the fusion center (FC) over multipath fading reporting channels. The cognitive radios estimate the phases of the reporting channels and use those estimates for coherent combining of the sensing results at the FC. A global decision is made at the FC by comparing the received signal with a threshold. We obtain the global detection probabilities and secondary throughput exactly through a moment generating function approach. We verify our solution via system simulation and demonstrate that the Chernoff bound and central limit theory approximation are not tight. The cases of hard sensing and soft sensing are considered and we provide examples in which hard sensing is advantageous to soft sensing. We contrast the performance of SEGC with maximum ratio combining of the sensors\\' results and provide examples where the former is superior. Furthermore, we evaluate the performance of SEGC against existing orthogonal reporting techniques such as time division multiple access (TDMA). SEGC performance always dominates that of TDMA in terms of secondary throughput. We also study the impact of phase and synchronization errors and demonstrate the robustness of the SEGC technique against such imperfections. © 2002-2012 IEEE.

Hierarchical fiber-optic-based sensing system: impact damage monitoring of large-scale CFRP structures

International Nuclear Information System (INIS)

Minakuchi, Shu; Banshoya, Hidehiko; Takeda, Nobuo; Tsukamoto, Haruka

2011-01-01

This study proposes a novel fiber-optic-based hierarchical sensing concept for monitoring randomly induced damage in large-scale composite structures. In a hierarchical system, several kinds of specialized devices are hierarchically combined to form a sensing network. Specifically, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with an optical fiber network through transducing mechanisms. The distributed devices detect damage, and the fiber-optic network gathers the damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of a hierarchical sensing system through comparison with existing fiber-optic-based systems, and an impact damage detection system was then proposed to validate the new concept. The sensor devices were developed based on comparative vacuum monitoring (CVM), and Brillouin-based distributed strain measurement was utilized to identify damaged areas. Verification tests were conducted step-by-step, beginning with a basic test using a single sensor unit, and, finally, the proposed monitoring system was successfully verified using a carbon fiber reinforced plastic (CFRP) fuselage demonstrator. It was clearly confirmed that the hierarchical system has better repairability, higher robustness, and a wider monitorable area compared to existing systems

A Polygon Model for Wireless Sensor Network Deployment with Directional Sensing Areas

Science.gov (United States)

Wu, Chun-Hsien; Chung, Yeh-Ching

2009-01-01

The modeling of the sensing area of a sensor node is essential for the deployment algorithm of wireless sensor networks (WSNs). In this paper, a polygon model is proposed for the sensor node with directional sensing area. In addition, a WSN deployment algorithm is presented with topology control and scoring mechanisms to maintain network connectivity and improve sensing coverage rate. To evaluate the proposed polygon model and WSN deployment algorithm, a simulation is conducted. The simulation results show that the proposed polygon model outperforms the existed disk model and circular sector model in terms of the maximum sensing coverage rate. PMID:22303159

A Single-Walled Carbon Nanotube Network Gas Sensing Device

Directory of Open Access Journals (Sweden)

I-Ju Teng

2011-08-01

Full Text Available The goal of this research was to develop a chemical gas sensing device based on single-walled carbon nanotube (SWCNT networks. The SWCNT networks are synthesized on Al2O3-deposted SiO2/Si substrates with 10 nm-thick Fe as the catalyst precursor layer using microwave plasma chemical vapor deposition (MPCVD. The development of interconnected SWCNT networks can be exploited to recognize the identities of different chemical gases by the strength of their particular surface adsorptive and desorptive responses to various types of chemical vapors. The physical responses on the surface of the SWCNT networks cause superficial changes in the electric charge that can be converted into electronic signals for identification. In this study, we tested NO2 and NH3 vapors at ppm levels at room temperature with our self-made gas sensing device, which was able to obtain responses to sensitivity changes with a concentration of 10 ppm for NO2 and 24 ppm for NH3.

Ultra-short FBG based distributed sensing using shifted optical Gaussian filters and microwave-network analysis.

Science.gov (United States)

Cheng, Rui; Xia, Li; Sima, Chaotan; Ran, Yanli; Rohollahnejad, Jalal; Zhou, Jiaao; Wen, Yongqiang; Yu, Can

2016-02-08

Ultrashort fiber Bragg gratings (US-FBGs) have significant potential as weak grating sensors for distributed sensing, but the exploitation have been limited by their inherent broad spectra that are undesirable for most traditional wavelength measurements. To address this, we have recently introduced a new interrogation concept using shifted optical Gaussian filters (SOGF) which is well suitable for US-FBG measurements. Here, we apply it to demonstrate, for the first time, an US-FBG-based self-referencing distributed optical sensing technique, with the advantages of adjustable sensitivity and range, high-speed and wide-range (potentially >14000 με) intensity-based detection, and resistance to disturbance by nonuniform parameter distribution. The entire system is essentially based on a microwave network, which incorporates the SOGF with a fiber delay-line between the two arms. Differential detections of the cascaded US-FBGs are performed individually in the network time-domain response which can be obtained by analyzing its complex frequency response. Experimental results are presented and discussed using eight cascaded US-FBGs. A comprehensive numerical analysis is also conducted to assess the system performance, which shows that the use of US-FBGs instead of conventional weak FBGs could significantly improve the power budget and capacity of the distributed sensing system while maintaining the crosstalk level and intensity decay rate, providing a promising route for future sensing applications.

SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks

Science.gov (United States)

Lin, Likun

Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network

Opportunistic Sensing in Wireless Sensor Networks

NARCIS (Netherlands)

Scholten, Johan; Bakker, Pascal

Opportunistic sensing systems consist of changing constellations of wireless sensor nodes that, for a limited amount of time, work together to achieve a common goal. Such constellations are self-organizing and come into being spontaneously. This paper presents an opportunistic sensing system to

Real-time network traffic classification technique for wireless local area networks based on compressed sensing

Science.gov (United States)

Balouchestani, Mohammadreza

2017-05-01

Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

Airplane detection in remote sensing images using convolutional neural networks

Science.gov (United States)

Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

2018-03-01

Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

Real time network traffic monitoring for wireless local area networks based on compressed sensing

Science.gov (United States)

Balouchestani, Mohammadreza

2017-05-01

A wireless local area network (WLAN) is an important type of wireless networks which connotes different wireless nodes in a local area network. WLANs suffer from important problems such as network load balancing, large amount of energy, and load of sampling. This paper presents a new networking traffic approach based on Compressed Sensing (CS) for improving the quality of WLANs. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, which is a good record for WLANs. The proposed architecture is increased Data Throughput (DT) to 22 % and Signal to Noise (S/N) ratio to 17 %, which provide a good background for establishing high qualified local area networks. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog-CS framework is applied at the sensing step before analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed algorithm out-performs existing algorithms by achieving a good level of Quality of Service (QoS). This ability allows reducing 15 % of Bit Error Rate (BER) at each wireless node.

Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

Science.gov (United States)

Missif, Lial Raja; Kadhum, Mohammad M.

2017-09-01

Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

Smart sensing surveillance system

Science.gov (United States)

Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen

2010-04-01

An effective public safety sensor system for heavily-populated applications requires sophisticated and geographically-distributed infrastructures, centralized supervision, and deployment of large-scale security and surveillance networks. Artificial intelligence in sensor systems is a critical design to raise awareness levels, improve the performance of the system and adapt to a changing scenario and environment. In this paper, a highly-distributed, fault-tolerant, and energy-efficient Smart Sensing Surveillance System (S4) is presented to efficiently provide a 24/7 and all weather security operation in crowded environments or restricted areas. Technically, the S4 consists of a number of distributed sensor nodes integrated with specific passive sensors to rapidly collect, process, and disseminate heterogeneous sensor data from near omni-directions. These distributed sensor nodes can cooperatively work to send immediate security information when new objects appear. When the new objects are detected, the S4 will smartly select the available node with a Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR camera to track the objects and capture associated imagery. The S4 provides applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. Other imaging processes can be updated to meet specific requirements and operations. In the S4, all the sensor nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology. This UWB RF technology can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The Service Oriented Architecture of S4 enables remote applications to interact with the S4

Sensing across large-scale cognitive radio networks: Data processing, algorithms, and testbed for wireless tomography and moving target tracking

Science.gov (United States)

Bonior, Jason David

As the use of wireless devices has become more widespread so has the potential for utilizing wireless networks for remote sensing applications. Regular wireless communication devices are not typically designed for remote sensing. Remote sensing techniques must be carefully tailored to the capabilities of these networks before they can be applied. Experimental verification of these techniques and algorithms requires robust yet flexible testbeds. In this dissertation, two experimental testbeds for the advancement of research into sensing across large-scale cognitive radio networks are presented. System architectures, implementations, capabilities, experimental verification, and performance are discussed. One testbed is designed for the collection of scattering data to be used in RF and wireless tomography research. This system is used to collect full complex scattering data using a vector network analyzer (VNA) and amplitude-only data using non-synchronous software-defined radios (SDRs). Collected data is used to experimentally validate a technique for phase reconstruction using semidefinite relaxation and demonstrate the feasibility of wireless tomography. The second testbed is a SDR network for the collection of experimental data. The development of tools for network maintenance and data collection is presented and discussed. A novel recursive weighted centroid algorithm for device-free target localization using the variance of received signal strength for wireless links is proposed. The signal variance resulting from a moving target is modeled as having contours related to Cassini ovals. This model is used to formulate recursive weights which reduce the influence of wireless links that are farther from the target location estimate. The algorithm and its implementation on this testbed are presented and experimental results discussed.

Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

Science.gov (United States)

Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

2011-01-01

Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

Distributed Schemes for Crowdsourcing-Based Sensing Task Assignment in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Linbo Zhai

2017-01-01

Full Text Available Spectrum sensing is an important issue in cognitive radio networks. The unlicensed users can access the licensed wireless spectrum only when the licensed wireless spectrum is sensed to be idle. Since mobile terminals such as smartphones and tablets are popular among people, spectrum sensing can be assigned to these mobile intelligent terminals, which is called crowdsourcing method. Based on the crowdsourcing method, this paper studies the distributed scheme to assign spectrum sensing task to mobile terminals such as smartphones and tablets. Considering the fact that mobile terminals’ positions may influence the sensing results, a precise sensing effect function is designed for the crowdsourcing-based sensing task assignment. We aim to maximize the sensing effect function and cast this optimization problem to address crowdsensing task assignment in cognitive radio networks. This problem is difficult to be solved because the complexity of this problem increases exponentially with the growth in mobile terminals. To assign crowdsensing task, we propose four distributed algorithms with different transition probabilities and use a Markov chain to analyze the approximation gap of our proposed schemes. Simulation results evaluate the average performance of our proposed algorithms and validate the algorithm’s convergence.

Parking Sensing and Information System: Sensors, Deployment, and Evaluation

OpenAIRE

Chen, Xiao; Zhen; Qian; Rajagopal, Ram; Stiers, Todd; Flores, Christopher; Kavaler, Robert; Williams III, Floyd

2017-01-01

This paper describes a smart parking sensing and information system that disseminates the parking availability information for public users in a cost-effective and efficient manner. The hardware framework of the system is built on advanced wireless sensor networks and cloud service over the Internet, and the system is highly scalable. The parking information provided to the users is set in the form of occupancy rates and expected cruising time. Both are obtained from our analytical algorithm ...

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

Science.gov (United States)

Brown, Molly Elizabeth; Brickley, Elizabeth B

2012-01-01

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Adjusting Sensing Range to Maximize Throughput on Ad-Hoc Multi-Hop Wireless Networks

National Research Council Canada - National Science Library

Roberts, Christopher

2003-01-01

.... Such a network is referred to as a multi-hop ad-hoc network, or simply a multi-hop network. Most multi-hop network protocols use some form of carrier sensing to determine if the wireless channel is in use...

LIGO sensing system performance

CERN Document Server

Landry, M

2002-01-01

The optical sensing subsystem of a LIGO interferometer is described. The system includes two complex interferometric sensing schemes to control test masses in length and alignment. The length sensing system is currently employed on all LIGO interferometers to lock coupled cavities on resonance. Auto-alignment is to be accomplished by a wavefront-sensing scheme which automatically corrects for angular fluctuations of the test masses. Improvements in lock stability and duration are noted when the wavefront auto-alignment system is employed. Preliminary results from the commissioning of the 2 km detector in Washington are shown.

Intelligent environmental sensing

CERN Document Server

Mukhopadhyay, Subhas

2015-01-01

Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

Crack identification for reinforced concrete using PZT based smart rebar active sensing diagnostic network

Science.gov (United States)

Song, N. N.; Wu, F.

2016-04-01

An active sensing diagnostic system using PZT based smart rebar for SHM of RC structure has been currently under investigation. Previous test results showed that the system could detect the de-bond of concrete from reinforcement, and the diagnostic signals were increased exponentially with the de-bonding size. Previous study also showed that the smart rebar could function well like regular reinforcement to undertake tension stresses. In this study, a smart rebar network has been used to detect the crack damage of concrete based on guided waves. Experimental test has been carried out for the study. In the test, concrete beams with 2 reinforcements have been built. 8 sets of PZT elements were mounted onto the reinforcement bars in an optimized way to form an active sensing diagnostic system. A 90 kHz 5-cycle Hanning-windowed tone burst was used as input. Multiple cracks have been generated on the concrete structures. Through the guided bulk waves propagating in the structures from actuators and sensors mounted from different bars, crack damage could be detected clearly. Cases for both single and multiple cracks were tested. Different crack depths from the surface and different crack numbers have been studied. Test result shows that the amplitude of sensor output signals is deceased linearly with a propagating crack, and is decreased exponentially with increased crack numbers. From the study, the active sensing diagnostic system using PZT based smart rebar network shows a promising way to provide concrete crack damage information through the "talk" among sensors.

VCSEL-based gigabit IR-UWB link for converged communication and sensing applications in optical metro-access networks

DEFF Research Database (Denmark)

Pham, Tien Thang; Gibbon, Timothy Braidwood; Tafur Monroy, Idelfonso

2012-01-01

We report on experimental demonstration of an impulse radio ultrawideband (IR-UWB) based converged communication and sensing system. A 1550-nm VCSEL-generated IR-UWB signal is used for 2-Gbps wireless data distribution over 800-m and 50-km single mode fiber links which present short-range in-buil...... application, paving the way forward for the development and deployment of converged UWB VCSEL-based technologies in access and in-building networks of the future.......We report on experimental demonstration of an impulse radio ultrawideband (IR-UWB) based converged communication and sensing system. A 1550-nm VCSEL-generated IR-UWB signal is used for 2-Gbps wireless data distribution over 800-m and 50-km single mode fiber links which present short-range in......-building and long-reach access network applications. The IR-UWB signal is also used to simultaneously measure the rotational speed of a blade spinning between 18 and 30 Hz. To the best of our knowledge, this is the very first demonstration of a simultaneous gigabit UWB telecommunication and wireless UWB sensing...

Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

Science.gov (United States)

Kiang, Richard K.

1992-01-01

Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

Learning Frameworks for Cooperative Spectrum Sensing and Energy-Efficient Data Protection in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Vinh Quang Do

2018-05-01

Full Text Available This paper studies learning frameworks for energy-efficient data communications in an energy-harvesting cognitive radio network in which secondary users (SUs harvest energy from solar power while opportunistically accessing a licensed channel for data transmission. The SUs perform spectrum sensing individually, and send local decisions about the presence of the primary user (PU on the channel to a fusion center (FC. We first design a new cooperative spectrum-sensing technique based on a convolutional neural network in which the FC uses historical sensing data to train the network for classification problem. The system is assumed to operate in a time-slotted manner. At the beginning of each time slot, the FC uses the current local decisions as input for the trained network to decide whether the PU is active or not in that time slot. In addition, legitimate transmissions can be vulnerable to a hidden eavesdropper, which always passively listens to the communication. Therefore, we further propose a transfer learning actor–critic algorithm for an SU to decide its operation mode to increase the security level under the constraint of limited energy. In this approach, the SU directly interacts with the environment to learn its dynamics (i.e., an arrival of harvested energy; then, the SU can either stay idle to save energy or transmit to the FC secured data that are encrypted using a suitable private-key encryption method to maximize the long-term effective security level of the network. We finally present numerical simulation results under various configurations to evaluate our proposed schemes.

Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

Science.gov (United States)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.

Bioinspired Infrared Sensing Materials and Systems.

Science.gov (United States)

Shen, Qingchen; Luo, Zhen; Ma, Shuai; Tao, Peng; Song, Chengyi; Wu, Jianbo; Shang, Wen; Deng, Tao

2018-05-11

Bioinspired engineering offers a promising alternative approach in accelerating the development of many man-made systems. Next-generation infrared (IR) sensing systems can also benefit from such nature-inspired approach. The inherent compact and uncooled operation of biological IR sensing systems provides ample inspiration for the engineering of portable and high-performance artificial IR sensing systems. This review overviews the current understanding of the biological IR sensing systems, most of which are thermal-based IR sensors that rely on either bolometer-like or photomechanic sensing mechanism. The existing efforts inspired by the biological IR sensing systems and possible future bioinspired approaches in the development of new IR sensing systems are also discussed in the review. Besides these biological IR sensing systems, other biological systems that do not have IR sensing capabilities but can help advance the development of engineered IR sensing systems are also discussed, and the related engineering efforts are overviewed as well. Further efforts in understanding the biological IR sensing systems, the learning from the integration of multifunction in biological systems, and the reduction of barriers to maximize the multidiscipline collaborations are needed to move this research field forward. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

Science.gov (United States)

Zhang, Zhen; Ma, Cheng; Zhu, Rong

2016-10-14

High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules

Directory of Open Access Journals (Sweden)

Zhen Zhang

2016-10-01

Full Text Available High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial–temporal complexity. This paper presents a multi-input multi-output (MIMO self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional–integral–derivative (PID neural network (FCPIDNN and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

Intelligent Balanced Device and its Sensing System for Beam Pumping Units

Directory of Open Access Journals (Sweden)

Hangxin WEI

2014-11-01

Full Text Available In order to save the energy of the beam pumping unit, the intelligent balanced device was developed. The device can adjust the position of the balanced-block automatically by the single chip microcomputer controller, and the fuzzy PD control algorithm was used to control the servo motor of the device. Since some signals should be inputted into the intelligent balanced device to calculate the balanced index of the pumping unit, the signals sensing system were designed. The sensing system includes the electric current sensor and voltage sensor of the main motor, the displacement sensor and the force sensor of the horse head. The sensing network has three layers: slave station, relay station and master station. The data transmission between them is based on ZigBee and GPRS method which can adapt the environment of the oil field. The results of application show that the intelligent balanced device and its sensing system can have the effect of reducing the power consumption, working reliability and communication efficiently.

Explicit Content Caching at Mobile Edge Networks with Cross-Layer Sensing

Science.gov (United States)

Chen, Lingyu; Su, Youxing; Luo, Wenbin; Hong, Xuemin; Shi, Jianghong

2018-01-01

The deployment density and computational power of small base stations (BSs) are expected to increase significantly in the next generation mobile communication networks. These BSs form the mobile edge network, which is a pervasive and distributed infrastructure that can empower a variety of edge/fog computing applications. This paper proposes a novel edge-computing application called explicit caching, which stores selective contents at BSs and exposes such contents to local users for interactive browsing and download. We formulate the explicit caching problem as a joint content recommendation, caching, and delivery problem, which aims to maximize the expected user quality-of-experience (QoE) with varying degrees of cross-layer sensing capability. Optimal and effective heuristic algorithms are presented to solve the problem. The theoretical performance bounds of the explicit caching system are derived in simplified scenarios. The impacts of cache storage space, BS backhaul capacity, cross-layer information, and user mobility on the system performance are simulated and discussed in realistic scenarios. Results suggest that, compared with conventional implicit caching schemes, explicit caching can better exploit the mobile edge network infrastructure for personalized content dissemination. PMID:29565313

Explicit Content Caching at Mobile Edge Networks with Cross-Layer Sensing.

Science.gov (United States)

Chen, Lingyu; Su, Youxing; Luo, Wenbin; Hong, Xuemin; Shi, Jianghong

2018-03-22

The deployment density and computational power of small base stations (BSs) are expected to increase significantly in the next generation mobile communication networks. These BSs form the mobile edge network, which is a pervasive and distributed infrastructure that can empower a variety of edge/fog computing applications. This paper proposes a novel edge-computing application called explicit caching, which stores selective contents at BSs and exposes such contents to local users for interactive browsing and download. We formulate the explicit caching problem as a joint content recommendation, caching, and delivery problem, which aims to maximize the expected user quality-of-experience (QoE) with varying degrees of cross-layer sensing capability. Optimal and effective heuristic algorithms are presented to solve the problem. The theoretical performance bounds of the explicit caching system are derived in simplified scenarios. The impacts of cache storage space, BS backhaul capacity, cross-layer information, and user mobility on the system performance are simulated and discussed in realistic scenarios. Results suggest that, compared with conventional implicit caching schemes, explicit caching can better exploit the mobile edge network infrastructure for personalized content dissemination.

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

Science.gov (United States)

Taboun, Mohammed S; Brennan, Robert W

2017-09-14

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

Geometry correction Algorithm for UAV Remote Sensing Image Based on Improved Neural Network

Science.gov (United States)

Liu, Ruian; Liu, Nan; Zeng, Beibei; Chen, Tingting; Yin, Ninghao

2018-03-01

Aiming at the disadvantage of current geometry correction algorithm for UAV remote sensing image, a new algorithm is proposed. Adaptive genetic algorithm (AGA) and RBF neural network are introduced into this algorithm. And combined with the geometry correction principle for UAV remote sensing image, the algorithm and solving steps of AGA-RBF are presented in order to realize geometry correction for UAV remote sensing. The correction accuracy and operational efficiency is improved through optimizing the structure and connection weight of RBF neural network separately with AGA and LMS algorithm. Finally, experiments show that AGA-RBF algorithm has the advantages of high correction accuracy, high running rate and strong generalization ability.

An Adaptive Data Gathering Scheme for Multi-Hop Wireless Sensor Networks Based on Compressed Sensing and Network Coding.

Science.gov (United States)

Yin, Jun; Yang, Yuwang; Wang, Lei

2016-04-01

Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering--CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes--MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme.

Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

Science.gov (United States)

Mollenhauer, Hannes; Schima, Robert; Remmler, Paul; Mollenhauer, Olaf; Hutschenreuther, Tino; Toepfer, Hannes; Dietrich, Peter; Bumberger, Jan

2015-04-01

For an adequate characterization of ecosystems it is necessary to detect individual processes with suitable monitoring strategies and methods. Due to the natural complexity of all environmental compartments, single point or temporally and spatially fixed measurements are mostly insufficient for an adequate representation. The application of mobile wireless sensor networks for soil and atmosphere sensing offers significant benefits, due to the simple adjustment of the sensor distribution, the sensor types and the sample rate (e.g. by using optimization approaches or event triggering modes) to the local test conditions. This can be essential for the monitoring of heterogeneous and dynamic environmental systems and processes. One significant advantage in the application of mobile ad-hoc wireless sensor networks is their self-organizing behavior. Thus, the network autonomously initializes and optimizes itself. Due to the localization via satellite a major reduction in installation and operation costs and time is generated. In addition, single point measurements with a sensor are significantly improved by measuring at several optimized points continuously. Since performing analog and digital signal processing and computation in the sensor nodes close to the sensors a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of nodes. Furthermore, the miniaturization of the nodes and energy harvesting are current topics under investigation. First results of field measurements are given to present the potentials and limitations of this application in environmental science. In particular, collected in-situ data with numerous specific soil and atmosphere parameters per sensor node (more than 25) recorded over several days illustrates the high performance of this system for advanced soil sensing and soil-atmosphere interaction monitoring. Moreover, investigations of biotic and abiotic process interactions and optimization

Modelling, Estimation and Control of Networked Complex Systems

CERN Document Server

Chiuso, Alessandro; Frasca, Mattia; Rizzo, Alessandro; Schenato, Luca; Zampieri, Sandro

2009-01-01

The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization of different disciplines and approaches. This book is devoted to networked systems which are one of the most promising paradigms of complexity. It is demonstrated that complex, dynamical networks are powerful tools to model, estimate, and control many interesting phenomena, like agent coordination, synchronization, social and economics events, networks of critical infrastructures, resources allocation, information processing, or control over communication networks. Moreover, it is shown how the recent technological advances in wireless communication and decreasing in cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile cap...

Data-Filtering System to Avoid Total Data Distortion in IoT Networking

Directory of Open Access Journals (Sweden)

Dae-Young Kim

2017-01-01

Full Text Available In the Internet of Things (IoT networking, numerous objects are connected to a network. They sense events and deliver the sensed information to the cloud. A lot of data is generated in the IoT network, and servers in the cloud gather the sensed data from the objects. Then, the servers analyze the collected data and provide proper intelligent services to users through the results of the analysis. When the server analyzes the collected data, if there exists malfunctioning data, distortional results of the analysis will be generated. The distortional results lead to misdirection of the intelligent services, leading to poor user experience. In the analysis for intelligent services in IoT, malfunctioning data should be avoided because integrity of the collected data is crucial. Therefore, this paper proposes a data-filtering system for the server in the cloud. The proposed data-filtering system is placed in front of the server and firstly receives the sensed data from the objects. It employs the naïve Bayesian classifier and, by learning, classifies the malfunctioning data from among the collected data. Data with integrity is delivered to the server for analysis. Because the proposed system filters the malfunctioning data, the server can obtain accurate analysis results and reduce computing load. The performance of the proposed data-filtering system is evaluated through computer simulation. Through the simulation results, the efficiency of the proposed data-filtering system is shown.

Cosmic Ray Neutron Sensing in Complex Systems

Science.gov (United States)

Piussi, L. M.; Tomelleri, E.; Tonon, G.; Bertoldi, G.; Mejia Aguilar, A.; Monsorno, R.; Zebisch, M.

2017-12-01

Soil moisture is a key variable in environmental monitoring and modelling: being located at the soil-atmosphere boundary, it is a driving force for water, energy and carbon fluxes. Nevertheless its importance, soil moisture observations lack of long time-series at high acquisition frequency in spatial meso-scale resolutions: traditional measurements deliver either long time series with high measurement frequency at spatial point scale or large scale and low frequency acquisitions. The Cosmic Ray Neutron Sensing (CRNS) technique fills this gap because it supplies information from a footprint of 240m of diameter and 15 to 83 cm of depth at a temporal resolution varying between 15 minutes and 24 hours. In addition, being a passive sensing technique, it is non-invasive. For these reasons, CRNS is gaining more and more attention from the scientific community. Nevertheless, the application of this technique in complex systems is still an open issue: where different Hydrogen pools are present and where their distributions vary appreciably with space and time, the traditional calibration method shows some limits. In order to obtain a better understanding of the data and to compare them with remote sensing products and spatially distributed traditional measurements (i.e. Wireless Sensors Network), the complexity of the surrounding environment has to be taken into account. In the current work we assessed the effects of spatial-temporal variability of soil moisture within the footprint, in a steep, heterogeneous mountain grassland area. Measurement were performed with a Cosmic Ray Neutron Probe (CRNP) and a mobile Wireless Sensors Network. We performed an in-deep sensitivity analysis of the effects of varying distributions of soil moisture on the calibration of the CRNP and our preliminary results show how the footprint shape varies depending on these dynamics. The results are then compared with remote sensing data (Sentinel 1 and 2). The current work is an assessment of

Compressive sensing of high betweenness centrality nodes in networks

Science.gov (United States)

Mahyar, Hamidreza; Hasheminezhad, Rouzbeh; Ghalebi K., Elahe; Nazemian, Ali; Grosu, Radu; Movaghar, Ali; Rabiee, Hamid R.

2018-05-01

Betweenness centrality is a prominent centrality measure expressing importance of a node within a network, in terms of the fraction of shortest paths passing through that node. Nodes with high betweenness centrality have significant impacts on the spread of influence and idea in social networks, the user activity in mobile phone networks, the contagion process in biological networks, and the bottlenecks in communication networks. Thus, identifying k-highest betweenness centrality nodes in networks will be of great interest in many applications. In this paper, we introduce CS-HiBet, a new method to efficiently detect top- k betweenness centrality nodes in networks, using compressive sensing. CS-HiBet can perform as a distributed algorithm by using only the local information at each node. Hence, it is applicable to large real-world and unknown networks in which the global approaches are usually unrealizable. The performance of the proposed method is evaluated by extensive simulations on several synthetic and real-world networks. The experimental results demonstrate that CS-HiBet outperforms the best existing methods with notable improvements.

Secure Cooperative Spectrum Sensing for the Cognitive Radio Network Using Nonuniform Reliability

Directory of Open Access Journals (Sweden)

Muhammad Usman

2014-01-01

Full Text Available Both reliable detection of the primary signal in a noisy and fading environment and nullifying the effect of unauthorized users are important tasks in cognitive radio networks. To address these issues, we consider a cooperative spectrum sensing approach where each user is assigned nonuniform reliability based on the sensing performance. Users with poor channel or faulty sensor are assigned low reliability. The nonuniform reliabilities serve as identification tags and are used to isolate users with malicious behavior. We consider a link layer attack similar to the Byzantine attack, which falsifies the spectrum sensing data. Three different strategies are presented in this paper to ignore unreliable and malicious users in the network. Considering only reliable users for global decision improves sensing time and decreases collisions in the control channel. The fusion center uses the degree of reliability as a weighting factor to determine the global decision in scheme I. Schemes II and III consider the unreliability of users, which makes the computations even simpler. The proposed schemes reduce the number of sensing reports and increase the inference accuracy. The advantages of our proposed schemes over conventional cooperative spectrum sensing and the Chair-Varshney optimum rule are demonstrated through simulations.

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

Science.gov (United States)

Brennan, Robert W.

2017-01-01

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network. PMID:28906452

Impact of Sink Node Placement onto Wireless Sensor Networks Performance Regarding Clustering Routing and Compressive Sensing Theory

Directory of Open Access Journals (Sweden)

Shima Pakdaman Tirani

2016-01-01

Full Text Available Wireless Sensor Networks (WSNs consist of several sensor nodes with sensing, computation, and wireless communication capabilities. The energy constraint is one of the most important issues in these networks. Thus, the data-gathering process should be carefully designed to conserve the energy. In this situation, a load balancing strategy can enhance the resources utilization, and consequently, increase the network lifetime. Furthermore, recently, the sparse nature of data in WSNs has been motivated the use of the compressive sensing as an efficient data gathering technique. Using the compressive sensing theory significantly leads to decreasing the volume of the transmitted data. Taking the above challenges into account, the main goal of this paper is to jointly consider the compressive sensing method and the load-balancing in WSNs. In this regards, using the conventional network model, we analyze the network performance in several different states. These states challenge the sink location in term of the number of transmissions. Numerical results demonstrate the efficiency of the load-balancing in the network performance.

Network monitoring module of BES III system environment

International Nuclear Information System (INIS)

Song Liwen; Zhao Jingwei; Zhang Bingyun

2002-01-01

In order to meet the needs of the complicated network architecture of BES III (Beijing Spectrometer III) and make sure normal online running in the future, it is necessary to develop a multi-platforms Network Monitoring Tool which can help system administrator monitor and manage BES III network. The author provides a module that can monitor not only the traffic of switch-router's ports but also the performance status of key devices in the network environment, meanwhile it can also give warning to manager and submit the related reports. the great sense, the theory basis, the implementing method and the graph in formation of this tool will be discussed

Energy Efficient Cooperative Spectrum Sensing in Cognitive Radio Networks Using Distributed Dynamic Load Balanced Clustering Scheme

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Muthukkumar R.

2017-04-01

Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.

Energy Efficient Cooperative Spectrum Sensing in Cognitive Radio Networks Using Distributed Dynamic Load Balanced Clustering Scheme

Directory of Open Access Journals (Sweden)

Muthukkumar R.

2016-07-01

Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.

Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

Science.gov (United States)

Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.

1993-01-01

Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.

A light and faster regional convolutional neural network for object detection in optical remote sensing images

Science.gov (United States)

Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

2018-07-01

Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

In-service communication channel sensing based on reflectometry for TWDM-PON systems

Science.gov (United States)

Iida, Daisuke; Kuwano, Shigeru; Terada, Jun

2014-05-01

Many base stations are accommodated in TWDM-PON based mobile backhaul and fronthaul networks for future radio access, and failed connections in an optical network unit (ONU) wavelength channel severely degrade system performance. A cost effective in-service ONU wavelength channel monitor is essential to ensure proper system operation without failed connections. To address this issue we propose a reflectometry-based remote sensing method that provides wavelength channel information with the optical line terminal (OLT)-ONU distance. The method realizes real-time monitoring of ONU wavelength channels without signal quality degradation. Experimental results show it achieves wavelength channel distinction with high distance resolution.

On the Feedback Reduction of Relay Multiuser Networks using Compressive Sensing

KAUST Repository

Elkhalil, Khalil; Eltayeb, Mohammed; Kammoun, Abla; Al-Naffouri, Tareq Y.; Bahrami, Hamid Reza

2016-01-01

This paper presents a comprehensive performance analysis of full-duplex multiuser relay networks employing opportunistic scheduling with noisy and compressive feedback. Specifically, two feedback techniques based on compressive sensing (CS) theory

Protecting Mobile Crowd Sensing against Sybil Attacks Using Cloud Based Trust Management System

Directory of Open Access Journals (Sweden)

Shih-Hao Chang

2016-01-01

Full Text Available Mobile crowd sensing (MCS arises as a new sensing paradigm, which leverages citizens for large-scale sensing by various mobile devices to efficiently collect and share local information. Unlike other MCS application challenges that consider user privacy and data trustworthiness, this study focuses on the network trustworthiness problem, namely, Sybil attacks in MCS network. The Sybil attack in computer security is a type of security attack, which illegally forges multiple identities in peer-to-peer networks, namely, Sybil identities. These Sybil identities will falsify multiple identities that negatively influence the effectiveness of sensing data in this MCS network or degrading entire network performance. To cope with this problem, a cloud based trust management scheme (CbTMS was proposed to detect Sybil attacks in the MCS network. The CbTMS was proffered for performing active and passive checking scheme, in addition to the mobile PCS trustworthiness management, and includes a decision tree algorithm, to verify the covered nodes in the MCS network. Simulation studies show that our CbTMS can efficiently detect the malicious Sybil nodes in the network and cause 6.87 Wh power reduction compared with other malicious Sybil node attack mode.

Smart sensing surveillance system

Science.gov (United States)

Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen

2010-04-01

Unattended ground sensor (UGS) networks have been widely used in remote battlefield and other tactical applications over the last few decades due to the advances of the digital signal processing. The UGS network can be applied in a variety of areas including border surveillance, special force operations, perimeter and building protection, target acquisition, situational awareness, and force protection. In this paper, a highly-distributed, fault-tolerant, and energyefficient Smart Sensing Surveillance System (S4) is presented to efficiently provide 24/7 and all weather security operation in a situation management environment. The S4 is composed of a number of distributed nodes to collect, process, and disseminate heterogeneous sensor data. Nearly all S4 nodes have passive sensors to provide rapid omnidirectional detection. In addition, Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR cameras are integrated to selected nodes to track the objects and capture associated imagery. These S4 camera-connected nodes will provide applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. In the S4, all the nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology, which can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The S4 utilizes a Service Oriented Architecture such that remote applications can interact with the S4 network and use the specific presentation methods. The S4 capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded

Estimation and Control of Networked Distributed Parameter Systems: Application to Traffic Flow

KAUST Repository

Canepa, Edward

2016-11-01

The management of large-scale transportation infrastructure is becoming a very complex task for the urban areas of this century which are covering bigger geographic spaces and facing the inclusion of connected and self-controlled vehicles. This new system paradigm can leverage many forms of sensing and interaction, including a high-scale mobile sensing approach. To obtain a high penetration sensing system on urban areas more practical and scalable platforms are needed, combined with estimation algorithms suitable to the computational capabilities of these platforms. The purpose of this work was to develop a transportation framework that is able to handle different kinds of sensing data (e.g., connected vehicles, loop detectors) and optimize the traffic state on a defined traffic network. The framework estimates the traffic on road networks modeled by a family of Lighthill-Whitham-Richards equations. Based on an equivalent formulation of the problem using a Hamilton-Jacobi equation and using a semi-analytic formula, I will show that the model constraints resulting from the Hamilton-Jacobi equation are linear, albeit with unknown integer variables. This general framework solve exactly a variety of problems arising in transportation networks: traffic estimation, traffic control (including robust control), cybersecurity and sensor fault detection, or privacy analysis of users in probe-based traffic monitoring systems. This framework is very flexible, fast, and yields exact results. The recent advances in sensors (GPS, inertial measurement units) and microprocessors enable the development low-cost dedicated devices for traffic sensing in cities, 5 which are highly scalable, providing a feasible solution to cover large urban areas. However, one of the main problems to address is the privacy of the users of the transportation system, the framework presented here is a viable option to guarantee the privacy of the users by design.

Effectiveness of compressed sensing and transmission in wireless sensor networks for structural health monitoring

Science.gov (United States)

Fujiwara, Takahiro; Uchiito, Haruki; Tokairin, Tomoya; Kawai, Hiroyuki

2017-04-01

Regarding Structural Health Monitoring (SHM) for seismic acceleration, Wireless Sensor Networks (WSN) is a promising tool for low-cost monitoring. Compressed sensing and transmission schemes have been drawing attention to achieve effective data collection in WSN. Especially, SHM systems installing massive nodes of WSN require efficient data transmission due to restricted communications capability. The dominant frequency band of seismic acceleration is occupied within 100 Hz or less. In addition, the response motions on upper floors of a structure are activated at a natural frequency, resulting in induced shaking at the specified narrow band. Focusing on the vibration characteristics of structures, we introduce data compression techniques for seismic acceleration monitoring in order to reduce the amount of transmission data. We carry out a compressed sensing and transmission scheme by band pass filtering for seismic acceleration data. The algorithm executes the discrete Fourier transform for the frequency domain and band path filtering for the compressed transmission. Assuming that the compressed data is transmitted through computer networks, restoration of the data is performed by the inverse Fourier transform in the receiving node. This paper discusses the evaluation of the compressed sensing for seismic acceleration by way of an average error. The results present the average error was 0.06 or less for the horizontal acceleration, in conditions where the acceleration was compressed into 1/32. Especially, the average error on the 4th floor achieved a small error of 0.02. Those results indicate that compressed sensing and transmission technique is effective to reduce the amount of data with maintaining the small average error.

A Cross-Layer Approach in Sensing and Resource Allocation for Multimedia Transmission over Cognitive UWB Networks

Directory of Open Access Journals (Sweden)

Lo ACC

2010-01-01

Full Text Available We propose an MAC centric cross-layer approach to address the problem of multimedia transmission over cognitive Ultra Wideband (C-UWB networks. Several fundamental design issues, which are related to application (APP, medium access control (MAC, and physical (PHY layer, are discussed. Although substantial research has been carried out in the PHY layer perspective of cognitive radio system, this paper attempts to extend the existing research paradigm to MAC and APP layers, which can be considered as premature at this time. This paper proposed a cross-layer design that is aware of (a UWB wireless channel conditions, (b time slot allocations at the MAC layer, and (c MPEG-4 video at the APP layer. Two cooperative sensing mechanisms, namely, AND and OR, are analyzed in terms of probability of detection ( , probability of false alarm ( , and the required sensing period. Then, the impact of sensing scheduling to the MPEG-4 video transmission over wireless cognitive UWB networks is observed. In addition, we also proposed the packet reception rate- (PRR- based resource allocation scheme that is aware of the channel condition, target PRR, and queue status.

Radar network communication through sensing of frequency hopping

Science.gov (United States)

Dowla, Farid; Nekoogar, Faranak

2013-05-28

In one embodiment, a radar communication system includes a plurality of radars having a communication range and being capable of operating at a sensing frequency and a reporting frequency, wherein the reporting frequency is different than the sensing frequency, each radar is adapted for operating at the sensing frequency until an event is detected, each radar in the plurality of radars has an identification/location frequency for reporting information different from the sensing frequency, a first radar of the radars which senses the event sends a reporting frequency corresponding to its identification/location frequency when the event is detected, and all other radars in the plurality of radars switch their reporting frequencies to match the reporting frequency of the first radar upon detecting the reporting frequency switch of a radar within the communication range. In another embodiment, a method is presented for communicating information in a radar system.

Fast Automatic Airport Detection in Remote Sensing Images Using Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Fen Chen

2018-03-01

Full Text Available Fast and automatic detection of airports from remote sensing images is useful for many military and civilian applications. In this paper, a fast automatic detection method is proposed to detect airports from remote sensing images based on convolutional neural networks using the Faster R-CNN algorithm. This method first applies a convolutional neural network to generate candidate airport regions. Based on the features extracted from these proposals, it then uses another convolutional neural network to perform airport detection. By taking the typical elongated linear geometric shape of airports into consideration, some specific improvements to the method are proposed. These approaches successfully improve the quality of positive samples and achieve a better accuracy in the final detection results. Experimental results on an airport dataset, Landsat 8 images, and a Gaofen-1 satellite scene demonstrate the effectiveness and efficiency of the proposed method.

Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

Science.gov (United States)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

Wireless sensor networks (WSNs) are one of the emerging areas that received great attention during the last few years. This is mainly due to the fact that WSNs have provided scientists with the capability of developing real-time monitoring systems equipped with sensors based on Micro-Electro-Mechanical Systems (MEMS). WSNs have great potential for many applications in environmental monitoring since the sensor nodes that comprised from can host several MEMS sensors (such as temperature, humidity, inertial, pressure, strain-gauge) and transducers (such as position, velocity, acceleration, vibration). The resulting devices are small and inexpensive but with limited memory and computing resources. Each sensor node contains a sensing module which along with an RF transceiver. The communication is broadcast-based since the network topology can change rapidly due to node failures [1]. Sensor nodes can transmit their measurements to central servers through gateway nodes without any processing or they make preliminary calculations locally in order to produce results that will be sent to central servers [2]. Based on the above characteristics, two prototypes using WSNs are presented in this paper: A Landslide detection system and a Flood warning system. Both systems sent their data to central processing server where the core of processing routines exists. Transmission is made using Zigbee and IEEE 802.11b protocol but is capable to use VSAT communication also. Landslide detection system uses structured network topology. Each measuring node comprises of a columnar module that is half buried to the area under investigation. Each sensing module contains a geophone, an inclinometer and a set of strain gauges. Data transmitted to central processing server where possible landslide evolution is monitored. Flood detection system uses unstructured network topology since the failure rate of sensor nodes is expected higher. Each sensing module contains a custom water level sensor

Multi-field coupled sensing network for health monitoring of composite bolted joint

Science.gov (United States)

Wang, Yishou; Qing, Xinlin; Dong, Liang; Banerjee, Sourav

2016-04-01

Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and excellent designability. As key components of large composite structures, joints play important roles to ensure the integrity of the composite structures. However, it is very difficult to analyze the strength and failure modes of composite joints due to their complex nonlinear coupling factors. Therefore, there is a need to monitor, diagnose, evaluate and predict the structure state of composite joints. This paper proposes a multi-field coupled sensing network for health monitoring of composite bolted joints. Major work of this paper includes: 1) The concept of multifunctional sensor layer integrated with eddy current sensors, Rogowski coil and arrayed piezoelectric sensors; 2) Development of the process for integrating the eddy current sensor foil, Rogowski coil and piezoelectric sensor array in multifunctional sensor layer; 3) A new concept of smart composite joint with multifunctional sensing capability. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the study.

Sum Utilization of Spectrum with Spectrum Handoff and Imperfect Sensing in Interweave Multi-Channel Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Waqas Khalid

2018-05-01

Full Text Available Fifth-generation (5G heterogeneous network deployment poses new challenges for 5G-based cognitive radio networks (5G-CRNs as the primary user (PU is required to be more active because of the small cells, random user arrival, and spectrum handoff. Interweave CRNs (I-CRNs improve spectrum utilization by allowing opportunistic spectrum access (OSA for secondary users (SUs. The sum utilization of spectrum, i.e., joint utilization of spectrum by the SU and PU, depends on the spatial and temporal variations of PU activities, sensing outcomes, transmitting conditions, and spectrum handoff. In this study, we formulate and analyze the sum utilization of spectrum with different sets of channels under different PU and SU co-existing network topologies. We consider realistic multi-channel scenarios for the SU, with each channel licensed to a PU. The SU, aided by spectrum handoff, is authorized to utilize the channels on the basis of sensing outcomes and PU interruptions. The numerical evaluation of the proposed work is presented under different network and sensing parameters. Moreover, the sum utilization gain is investigated to analyze the sensitivities of different sensing parameters. It is demonstrated that different sets of channels, PU activities, and sensing outcomes have a significant impact on the sum utilization of spectrum associated with a specific network topology.

TinyONet: A Cache-Based Sensor Network Bridge Enabling Sensing Data Reusability and Customized Wireless Sensor Network Services

Science.gov (United States)

Jung, Eui-Hyun; Park, Yong-Jin

2008-01-01

In recent years, a few protocol bridge research projects have been announced to enable a seamless integration of Wireless Sensor Networks (WSNs) with the TCP/IP network. These studies have ensured the transparent end-to-end communication between two network sides in the node-centric manner. Researchers expect this integration will trigger the development of various application domains. However, prior research projects have not fully explored some essential features for WSNs, especially the reusability of sensing data and the data-centric communication. To resolve these issues, we suggested a new protocol bridge system named TinyONet. In TinyONet, virtual sensors play roles as virtual counterparts of physical sensors and they dynamically group to make a functional entity, Slice. Instead of direct interaction with individual physical sensors, each sensor application uses its own WSN service provided by Slices. If a new kind of service is required in TinyONet, the corresponding function can be dynamically added at runtime. Beside the data-centric communication, it also supports the node-centric communication and the synchronous access. In order to show the effectiveness of the system, we implemented TinyONet on an embedded Linux machine and evaluated it with several experimental scenarios. PMID:27873968

Study on Additional Carrier Sensing for IEEE 802.15.4 Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Bih-Hwang Lee

2010-06-01

Full Text Available Wireless sensor networks based on the IEEE 802.15.4 standard are able to achieve low-power transmissions in the guise of low-rate and short-distance wireless personal area networks (WPANs. The slotted carrier sense multiple access with collision avoidance (CSMA/CA is used for contention mechanism. Sensor nodes perform a backoff process as soon as the clear channel assessment (CCA detects a busy channel. In doing so they may neglect the implicit information of the failed CCA detection and further cause the redundant sensing. The blind backoff process in the slotted CSMA/CA will cause lower channel utilization. This paper proposes an additional carrier sensing (ACS algorithm based on IEEE 802.15.4 to enhance the carrier sensing mechanism for the original slotted CSMA/CA. An analytical Markov chain model is developed to evaluate the performance of the ACS algorithm. Both analytical and simulation results show that the proposed algorithm performs better than IEEE 802.15.4, which in turn significantly improves throughput, average medium access control (MAC delay and power consumption of CCA detection.

Study on additional carrier sensing for IEEE 802.15.4 wireless sensor networks.

Science.gov (United States)

Lee, Bih-Hwang; Lai, Ruei-Lung; Wu, Huai-Kuei; Wong, Chi-Ming

2010-01-01

Wireless sensor networks based on the IEEE 802.15.4 standard are able to achieve low-power transmissions in the guise of low-rate and short-distance wireless personal area networks (WPANs). The slotted carrier sense multiple access with collision avoidance (CSMA/CA) is used for contention mechanism. Sensor nodes perform a backoff process as soon as the clear channel assessment (CCA) detects a busy channel. In doing so they may neglect the implicit information of the failed CCA detection and further cause the redundant sensing. The blind backoff process in the slotted CSMA/CA will cause lower channel utilization. This paper proposes an additional carrier sensing (ACS) algorithm based on IEEE 802.15.4 to enhance the carrier sensing mechanism for the original slotted CSMA/CA. An analytical Markov chain model is developed to evaluate the performance of the ACS algorithm. Both analytical and simulation results show that the proposed algorithm performs better than IEEE 802.15.4, which in turn significantly improves throughput, average medium access control (MAC) delay and power consumption of CCA detection.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

Science.gov (United States)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Social Sensor Analytics: Making Sense of Network Models in Social Media

Energy Technology Data Exchange (ETDEWEB)

Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.; Sego, Landon H.; Corley, Courtney D.

2015-07-27

Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013 and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.

Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

Science.gov (United States)

Ren, Shengwei; Zhang, Li; Zhang, Shibing

2016-10-01

Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

Monolayer-functionalized microfluidics devices for optical sensing of acidity

NARCIS (Netherlands)

Mela, P.; Onclin, S.; Goedbloed, M.H.; Levi, S.; Garcia Parajo, M.F.; van Hulst, N.F.; Ravoo, B.J.; Reinhoudt, David; van den Berg, Albert

This paper describes the integration of opto-chemosensors in microfluidics networks. Our technique exploits the internal surface of the network as a platform to build a sensing system by coating the surface with a self-assembled monolayer and subsequently binding a fluorescent sensing molecule to

Study on cooperative active sensing system

International Nuclear Information System (INIS)

Tsukune, Hideo; Kita, Nobuyuki; Hirai, Shigeoki; Kuniyoshi, Yasuo; Hara, Isao; Matsui, Toshihiro

1999-01-01

In order to realize autonomous type nuclear plant, three-dimensional geometrical modelling method, and a basic technology on information collection and processing system preparation in some nuclear basic technology developments such as 'study on system evaluation of nuclear facility furnished with artificial intelligence for nuclear power' and 'study on adaptability evaluation of information collection and processing system into autonomous type plant' had already been developed. In this study, a study on sensing system required for constructing robot groups capable of conducting autonomously traveling inspection and maintenance in large scale, complicated and diverse plant has been processed by aiming at establishment of dispersed cooperative intelligent system technology. In 1997 fiscal year, integration of cooperative visual sensing technique was attempted. And, at the same time, upgrading of individual element technology and transportation method essential to the integrated system were investigated. As a result, an operative active sensing prototype system due to transportation robot groups furnished with real time processing capacity on diverse informations by integration of cooperative active sensing technique and real time active sensing technique developed independently plural transportation robot. (G.K.)

Optical networks for wideband sensor array

Science.gov (United States)

Sheng, Lin Horng

2011-12-01

This thesis presents the realization of novel systems for optical sensing networks with an array of long-period grating (LPG) sensors. As a launching point of the thesis, the motivation to implement optical sensing network in precisely catering LPG sensors is presented. It highlights the flexibility of the sensing network to act as the foundation in order to boost the application of the various LPG sensor design in biological and chemical sensing. After the thorough study on the various optical sensing networks, sub-carrier multiplexing (SCM) and optical time division multiplexing (OTDM) schemes are adopted in conjunction with tunable laser source (TLS) to facilitate simultaneous interrogation of the LPG sensors array. In fact, these systems are distinct to have the capability to accommodate wideband optical sensors. Specifically, the LPG sensors which is in 20nm bandwidth are identified to operate in these systems. The working principles of the systems are comprehensively elucidated in this thesis. It highlights the mathematical approach to quantify the experimental setup of the optical sensing network. Additionally, the system components of the designs are identified and methodically characterized so that the components well operate in the designed environment. A mockup has been setup to demonstrate the application in sensing of various liquid indices and analyse the response of the LPG sensors in order to evaluate the performance of the systems. Eventually, the resemblance of the demultiplexed spectral response to the pristine spectral response are quantified to have excellent agreement. Finally, the promising result consistency of the systems is verified through repeatability test.

Compressed Sensing in Vibration Monitoring Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Osvaldo Casares-Quirós

2014-12-01

After an experimental test using Waspmotes the fixed-variable variant has a 56.58% reduction of power consumption by introducing a maximum error ± 0.00195g and compress in 52.44% the amount of samples. This algorithm increased the network energy autonomy from 17 hours to 26.5 hours. Through mathematical analysis, the variable-fixed technique reduces in 74.81% the power consumption in sensing nodes transmissions and decrease in 90% the number of samples.

A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients

Directory of Open Access Journals (Sweden)

Lei Yu

2016-02-01

Full Text Available Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1 they are susceptible to subjective factors; (2 they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information.

A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients

Science.gov (United States)

Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

2016-01-01

Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they are susceptible to subjective factors; (2) they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information. PMID:26861337

Novel Spectrum Sensing Algorithms for OFDM Cognitive Radio Networks.

Science.gov (United States)

Shi, Zhenguo; Wu, Zhilu; Yin, Zhendong; Cheng, Qingqing

2015-06-15

Spectrum sensing technology plays an increasingly important role in cognitive radio networks. Consequently, several spectrum sensing algorithms have been proposed in the literature. In this paper, we present a new spectrum sensing algorithm "Differential Characteristics-Based OFDM (DC-OFDM)" for detecting OFDM signal on account of differential characteristics. We put the primary value on channel gain θ around zero to detect the presence of primary user. Furthermore, utilizing the same method of differential operation, we improve two traditional OFDM sensing algorithms (cyclic prefix and pilot tones detecting algorithms), and propose a "Differential Characteristics-Based Cyclic Prefix (DC-CP)" detector and a "Differential Characteristics-Based Pilot Tones (DC-PT)" detector, respectively. DC-CP detector is based on auto-correlation vector to sense the spectrum, while the DC-PT detector takes the frequency-domain cross-correlation of PT as the test statistic to detect the primary user. Moreover, the distributions of the test statistics of the three proposed methods have been derived. Simulation results illustrate that all of the three proposed methods can achieve good performance under low signal to noise ratio (SNR) with the presence of timing delay. Specifically, the DC-OFDM detector gets the best performance among the presented detectors. Moreover, both of the DC-CP and DC-PT detector achieve significant improvements compared with their corresponding original detectors.

Compressive Sensing in Communication Systems

DEFF Research Database (Denmark)

Fyhn, Karsten

2013-01-01

. The need for cheaper, smarter and more energy efficient wireless devices is greater now than ever. This thesis addresses this problem and concerns the application of the recently developed sampling theory of compressive sensing in communication systems. Compressive sensing is the merging of signal...... acquisition and compression. It allows for sampling a signal with a rate below the bound dictated by the celebrated Shannon-Nyquist sampling theorem. In some communication systems this necessary minimum sample rate, dictated by the Shannon-Nyquist sampling theorem, is so high it is at the limit of what...... with using compressive sensing in communication systems. The main contribution of this thesis is two-fold: 1) a new compressive sensing hardware structure for spread spectrum signals, which is simpler than the current state-of-the-art, and 2) a range of algorithms for parameter estimation for the class...

Dispersed Sensing Networks in Nano-Engineered Polymer Composites: From Static Strain Measurement to Ultrasonic Wave Acquisition

Directory of Open Access Journals (Sweden)

Yehai Li

2018-05-01

Full Text Available Self-sensing capability of composite materials has been the core of intensive research over the years and particularly boosted up by the recent quantum leap in nanotechnology. The capacity of most existing self-sensing approaches is restricted to static strains or low-frequency structural vibration. In this study, a new breed of functionalized epoxy-based composites is developed and fabricated, with a graphene nanoparticle-enriched, dispersed sensing network, whereby to self-perceive broadband elastic disturbance from static strains, through low-frequency vibration to guided waves in an ultrasonic regime. Owing to the dispersed and networked sensing capability, signals can be captured at any desired part of the composites. Experimental validation has demonstrated that the functionalized composites can self-sense strains, outperforming conventional metal foil strain sensors with a significantly enhanced gauge factor and a much broader response bandwidth. Precise and fast self-response of the composites to broadband ultrasonic signals (up to 440 kHz has revealed that the composite structure itself can serve as ultrasound sensors, comparable to piezoceramic sensors in performance, whereas avoiding the use of bulky cables and wires as used in a piezoceramic sensor network. This study has spotlighted promising potentials of the developed approach to functionalize conventional composites with a self-sensing capability of high-sensitivity yet minimized intrusion to original structures.

Simulation Of Wireless Networked Control System Using TRUETIME And MATLAB

Directory of Open Access Journals (Sweden)

Nyan Phyo Aung

2015-08-01

Full Text Available Wireless networked control systems WNCS are attracting an increasing research interests in the past decade. Wireless networked control system WNCS is composed of a group of distributed sensors and actuators that communicate through wireless link which achieves distributed sensing and executing tasks. This is particularly relevant for the areas of communication control and computing where successful design of WNCS brings about new challenges to the researchers. The primary motivation of this survey paper is to examine the design issues and to provide directions for successful simulation and implementation of WNCS. The paper also as well reviews some simulation tools for such systems.

Hydroball string sensing system

International Nuclear Information System (INIS)

Hurwitz, M.J.; Ekeroth, D.E.; Squarer, D.

1991-01-01

This patent describes a hydroball string sensing system for a nuclear reactor having a core containing a fluid at a fluid pressure. It comprises a tube connectable to the nuclear reactor so that the fluid can flow within the tube at a fluid pressure that is substantially the same as the fluid pressure of the nuclear reactor core; a hydroball string including - a string member having objects positioned therealong with a specified spacing, the object including a plurality of hydroballs, and bullet members positioned at opposing ends of the string member; first sensor means, positioned outside a first segment of the tube, for sensing one of the objects being positioned within the first segment, and for providing a sensing signal responsive to the sensing of the first sensing means

Airborne Wireless Sensor Networks for Airplane Monitoring System

Directory of Open Access Journals (Sweden)

Shang Gao

2018-01-01

Full Text Available In traditional airplane monitoring system (AMS, data sensed from strain, vibration, ultrasound of structures or temperature, and humidity in cabin environment are transmitted to central data repository via wires. However, drawbacks still exist in wired AMS such as expensive installation and maintenance, and complicated wired connections. In recent years, accumulating interest has been drawn to performing AMS via airborne wireless sensor network (AWSN system with the advantages of flexibility, low cost, and easy deployment. In this review, we present an overview of AMS and AWSN and demonstrate the requirements of AWSN for AMS particularly. Furthermore, existing wireless hardware prototypes and network communication schemes of AWSN are investigated according to these requirements. This paper will improve the understanding of how the AWSN design under AMS acquires sensor data accurately and carries out network communication efficiently, providing insights into prognostics and health management (PHM for AMS in future.

Wireless Sensor Network Based Smart Parking System

Directory of Open Access Journals (Sweden)

Jeffrey JOSEPH

2014-01-01

Full Text Available Ambient Intelligence is a vision in which various devices come together and process information from multiple sources in order to exert control on the physical environment. In addition to computation and control, communication plays a crucial role in the overall functionality of such a system. Wireless Sensor Networks are one such class of networks, which meet these criteria. These networks consist of spatially distributed sensor motes which work in a co-operative manner to sense and control the environment. In this work, an implementation of an energy-efficient and cost-effective, wireless sensor networks based vehicle parking system for a multi-floor indoor parking facility has been introduced. The system monitors the availability of free parking slots and guides the vehicle to the nearest free slot. The amount of time the vehicle has been parked is monitored for billing purposes. The status of the motes (dead/alive is also recorded. Information like slot allocated, directions to the slot and billing data is sent as a message to customer’s mobile phones. This paper extends our previous work 1 with the development of a low cost sensor mote, about one tenth the cost of a commercially available mote, keeping in mind the price sensitive markets of the developing countries.

Studying Sensing-Based Systems

DEFF Research Database (Denmark)

Kjærgaard, Mikkel Baun

2013-01-01

Recent sensing-based systems involve a multitude of users, devices, and places. These types of systems challenge existing approaches for conducting valid system evaluations. Here, the author discusses such evaluation challenges and revisits existing system evaluation methodologies....

Recent developments in seismic seabed oil reservoir monitoring applications using fibre-optic sensing networks

International Nuclear Information System (INIS)

De Freitas, J M

2011-01-01

This review looks at recent developments in seismic seabed oil reservoir monitoring techniques using fibre-optic sensing networks. After a brief introduction covering the background and scope of the review, the following section focuses on state-of-the-art fibre-optic hydrophones and accelerometers used for seismic applications. Related metrology aspects of the sensor such as measurement of sensitivity, noise and cross-axis performance are addressed. The third section focuses on interrogation systems. Two main phase-based competing systems have emerged over the past two decades for seismic applications, with a third technique showing much promise; these have been compared in terms of general performance. (topical review)

Study on cooperative active sensing system

International Nuclear Information System (INIS)

Tsukune, Hideo; Kita, Nobuyuki; Kuniyoshi, Yasuo; Hara, Isao; Matsui, Toshihiro; Matsushita, Toshio; Nagata, Kazuyuki; Nagakubo, Akihiko

1998-01-01

This study aims to develop a dispersed cooperative intellectualized system technique and a sensing system required for construction of a robot group inspectable in patrol and maintainable in selfish in a plant with large scale and complex variety. In particular, in order to establish a system with flexibility response to environment and soundness durable to abnormal accident, a cooperative active sensing technique and real-time active vision sensing technique were started. On the base of last two years results, in 1996 fiscal year, important and expansion of each element technique was conducted to start a study on movement of focussing point which was an important function of the active vision sensing. (G.K.)

The Development of Wireless Body Area Network for Motion Sensing Application

Science.gov (United States)

Puspitaningayu, P.; Widodo, A.; Yundra, E.; Ramadhany, F.; Arianto, L.; Habibie, D.

2018-04-01

The information era has driven the society into the digitally-controlled lifestyle. Wireless body area networks (WBAN) as the specific scope of wireless sensor networks (WSN) is consistently growing into bigger applications. Currently, people are able to monitor their medical parameters by simply using small electronics devices attached to their body and connected to the authorities. On top of that, this time, smart phones are typically equipped with sensors such as accelerometer, gyroscope, barometric pressure, heart rate monitor, etc. It means that the sensing yet the signal processing can be performed by a single device. Moreover, Android opens lot wider opportunities for new applications as the most popular open-sourced smart phone platform. This paper is intended to show the development of motion sensing application which focused on analysing data from accelerometer and gyroscope. Beside reads the sensors, this application also has the ability to convert the sensors’ numerical value into graphs.

A localized cooperative wideband spectrum sensing for dynamic access of TV bands using RF sensor networks

KAUST Repository

Mirza, Mohammed; Alouini, Mohamed-Slim

2011-01-01

In this paper we address and simulate a Radio Frequency (RF) sensor network for a cooperative spectrum sensing and localization scheme. The proposed method integrates a Wavelet based Multi-Resolution Spectrum Sensing (MRSS), an N-bit hard

PLANNING TRIPOLI METRO NETWORK BY THE USE OF REMOTE SENSING IMAGERY

Directory of Open Access Journals (Sweden)

O. Alhusain

2012-08-01

Full Text Available Tripoli, the capital city of Libya is going through significant and integrated development process, this development is expected to continue in the next few decades. The Libyan authorities have put it as their goal to develop Tripoli to an important metropolis in North Africa. To achieve this goal, they identified goals for the city's future development in all human, economic, cultural, touristic, and nonetheless infrastructure levels. On the infrastructure development level, among other things, they have identified the development of public transportation as one of the important development priorities. At present, public transportation in Tripoli is carried out by a limited capacity bus network alongside of individual transportation. However, movement in the city is characterized mainly by individual transportation with all its disadvantages such as traffic jams, significant air pollution with both carbon monoxide and dust, and lack of parking space. The Libyan authorities wisely opted for an efficient, modern, and environment friendly solution for public transportation, this was to plan a complex Metro Network as the backbone of public transportation in the city, and to develop and integrate the bus network and other means of transportation to be in harmony with the planned Metro network. The Metro network is planned to provide convenient connections to Tripoli International Airport and to the planned Railway station. They plan to build a system of Park and Ride (P+R facilities at suitable locations along the Metro lines. This paper will present in details the planned Metro Network, some of the applied technological solutions, the importance of applying remote sensing and GIS technologies in different planning phases, and problems and benefits associated with the use of multi-temporal-, multi-format spatial data in the whole network planning phase.

Planning Tripoli Metro Network by the Use of Remote Sensing Imagery

Science.gov (United States)

Alhusain, O.; Engedy, Gy.; Milady, A.; Paulini, L.; Soos, G.

2012-08-01

Tripoli, the capital city of Libya is going through significant and integrated development process, this development is expected to continue in the next few decades. The Libyan authorities have put it as their goal to develop Tripoli to an important metropolis in North Africa. To achieve this goal, they identified goals for the city's future development in all human, economic, cultural, touristic, and nonetheless infrastructure levels. On the infrastructure development level, among other things, they have identified the development of public transportation as one of the important development priorities. At present, public transportation in Tripoli is carried out by a limited capacity bus network alongside of individual transportation. However, movement in the city is characterized mainly by individual transportation with all its disadvantages such as traffic jams, significant air pollution with both carbon monoxide and dust, and lack of parking space. The Libyan authorities wisely opted for an efficient, modern, and environment friendly solution for public transportation, this was to plan a complex Metro Network as the backbone of public transportation in the city, and to develop and integrate the bus network and other means of transportation to be in harmony with the planned Metro network. The Metro network is planned to provide convenient connections to Tripoli International Airport and to the planned Railway station. They plan to build a system of Park and Ride (P+R) facilities at suitable locations along the Metro lines. This paper will present in details the planned Metro Network, some of the applied technological solutions, the importance of applying remote sensing and GIS technologies in different planning phases, and problems and benefits associated with the use of multi-temporal-, multi-format spatial data in the whole network planning phase.

Making sense of information in noisy networks: human communication, gossip, and distortion.

Science.gov (United States)

Laidre, Mark E; Lamb, Alex; Shultz, Susanne; Olsen, Megan

2013-01-21

Information from others can be unreliable. Humans nevertheless act on such information, including gossip, to make various social calculations, thus raising the question of whether individuals can sort through social information to identify what is, in fact, true. Inspired by empirical literature on people's decision-making when considering gossip, we built an agent-based simulation model to examine how well simple decision rules could make sense of information as it propagated through a network. Our simulations revealed that a minimalistic decision-rule 'Bit-wise mode' - which compared information from multiple sources and then sought a consensus majority for each component bit within the message - was consistently the most successful at converging upon the truth. This decision rule attained high relative fitness even in maximally noisy networks, composed entirely of nodes that distorted the message. The rule was also superior to other decision rules regardless of its frequency in the population. Simulations carried out with variable agent memory constraints, different numbers of observers who initiated information propagation, and a variety of network types suggested that the single most important factor in making sense of information was the number of independent sources that agents could consult. Broadly, our model suggests that despite the distortion information is subject to in the real world, it is nevertheless possible to make sense of it based on simple Darwinian computations that integrate multiple sources. Copyright © 2012 Elsevier Ltd. All rights reserved.

Displacement sensing system and method

Science.gov (United States)

VunKannon, Jr., Robert S

2006-08-08

A displacement sensing system and method addresses demanding requirements for high precision sensing of displacement of a shaft, for use typically in a linear electro-dynamic machine, having low failure rates over multi-year unattended operation in hostile environments. Applications include outer space travel by spacecraft having high-temperature, sealed environments without opportunity for servicing over many years of operation. The displacement sensing system uses a three coil sensor configuration, including a reference and sense coils, to provide a pair of ratio-metric signals, which are inputted into a synchronous comparison circuit, which is synchronously processed for a resultant displacement determination. The pair of ratio-metric signals are similarly affected by environmental conditions so that the comparison circuit is able to subtract or nullify environmental conditions that would otherwise cause changes in accuracy to occur.

Optimal Energy-Efficient Sensing and Power Allocation in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Xia Wu

2014-01-01

Full Text Available We consider a joint optimization of sensing parameter and power allocation for an energy-efficient cognitive radio network (CRN in which the primary user (PU is protected. The optimization problem to maximize the energy efficiency of CRN is formulated as a function of two variables, which are sensing time and transmit power, subject to the average interference power to the PU and the target detection probability. During the optimizing process, the quality of service parameter (the minimum rate acceptable to secondary users (SUs has also been taken into consideration. The optimal solutions are analyzed and an algorithm combined with fractional programming that maximizes the energy efficiency for CRN is presented. Numerical results show that the performance improvement is achieved by the joint optimization of sensing time and power allocation.

Deep Space Network Radiometric Remote Sensing Program

Science.gov (United States)

Walter, Steven J.

1994-01-01

Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid, and precipitation, emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band because communication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of water vapor-induced propagation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity wave experiments, and radio science missions. During 1993, WVRs provided data for propagation model development, supported planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily

A Network Coverage Information-Based Sensor Registry System for IoT Environments.

Science.gov (United States)

Jung, Hyunjun; Jeong, Dongwon; Lee, Sukhoon; On, Byung-Won; Baik, Doo-Kwon

2016-07-25

The Internet of Things (IoT) is expected to provide better services through the interaction of physical objects via the Internet. However, its limitations cause an interoperability problem when the sensed data are exchanged between the sensor nodes in wireless sensor networks (WSNs), which constitute the core infrastructure of the IoT. To address this problem, a Sensor Registry System (SRS) is used. By using a SRS, the information of the heterogeneous sensed data remains pure. If users move along a road, their mobile devices predict their next positions and obtain the sensed data for that position from the SRS. If the WSNs in the location in which the users move are unstable, the sensed data will be lost. Consider a situation where the user passes through dangerous areas. If the user's mobile device cannot receive information, they cannot be warned about the dangerous situation. To avoid this, two novel SRSs that use network coverage information have been proposed: one uses OpenSignal and the other uses the probabilistic distribution of the users accessing SRS. The empirical study showed that the proposed method can seamlessly provide services related to sensing data under any abnormal circumstance.

Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields

Directory of Open Access Journals (Sweden)

Teerapong Panboonyuen

2017-07-01

Full Text Available Object segmentation of remotely-sensed aerial (or very-high resolution, VHS images and satellite (or high-resolution, HR images, has been applied to many application domains, especially in road extraction in which the segmented objects are served as a mandatory layer in geospatial databases. Several attempts at applying the deep convolutional neural network (DCNN to extract roads from remote sensing images have been made; however, the accuracy is still limited. In this paper, we present an enhanced DCNN framework specifically tailored for road extraction of remote sensing images by applying landscape metrics (LMs and conditional random fields (CRFs. To improve the DCNN, a modern activation function called the exponential linear unit (ELU, is employed in our network, resulting in a higher number of, and yet more accurate, extracted roads. To further reduce falsely classified road objects, a solution based on an adoption of LMs is proposed. Finally, to sharpen the extracted roads, a CRF method is added to our framework. The experiments were conducted on Massachusetts road aerial imagery as well as the Thailand Earth Observation System (THEOS satellite imagery data sets. The results showed that our proposed framework outperformed Segnet, a state-of-the-art object segmentation technique, on any kinds of remote sensing imagery, in most of the cases in terms of precision, recall, and F 1 .

Exploratory community sensing in social networks

Science.gov (United States)

Khrabrov, Alexy; Stocco, Gabriel; Cybenko, George

2010-04-01

Social networks generally provide an implementation of some kind of groups or communities which users can voluntarily join. Twitter does not have this functionality, and there is no notion of a formal group or community. We propose a method for identification of communities and assignment of semantic meaning to the discussion topics of the resulting communities. Using this analysis method and a sample of roughly a month's worth of Tweets from Twitter's "gardenhose" feed, we demonstrate the discovery of meaningful user communities on Twitter. We examine Twitter data streaming in real time and treat it as a sensor. Twitter is a social network which pioneered microblogging with the messages fitting an SMS, and a variety of clients, browsers, smart phones and PDAs are used for status updates by individuals, businesses, media outlets and even devices all over the world. Often an aggregate trend of such statuses may represent an important development in the world, which has been demonstrated with the Iran and Moldova elections and the anniversary of the Tiananmen in China. We propose using Twitter as a sensor, tracking individuals and communities of interest, and characterizing individual roles and dynamics of their communications. We developed a novel algorithm of community identification in social networks based on direct communication, as opposed to linking. We show ways to find communities of interest and then browse their neighborhoods by either similarity or diversity of individuals and groups adjacent to the one of interest. We use frequent collocations and statistically improbable phrases to summarize the focus of the community, giving a quick overview of its main topics. Our methods provide insight into the largest social sensor network in the world and constitute a platform for social sensing.

Green Cooperative Spectrum Sensing and Scheduling in Heterogeneous Cognitive Radio Networks

KAUST Repository

Celik, Abdulkadir

2016-09-12

In this paper, we consider heterogeneous cognitive radio networks (CRNs) comprising primary channels (PCs) with heterogeneous characteristics and secondary users (SUs) with various sensing and reporting qualities for different PCs. We first define the opportunity as the achievable total data rate and its cost as the energy consumption caused from sensing, reporting, and channel switching operations and formulate a joint spectrum discovery and energy efficiency objective to minimize the energy spent per unit of data rate. Then, a mixed integer nonlinear programming problem is formulated to determine: 1) the optimal subset of PCs to be scheduled for sensing; 2) the SU assignment set for each scheduled PC; and 3) sensing durations and detection thresholds of each SU on PCs it is assigned to sense. Thereafter, an equivalent convex framework is developed for specific instances of the above combinatorial problem. For comparison, optimal detection and sensing thresholds are also derived analytically under the homogeneity assumption. Based on these, a prioritized ordering heuristic is developed to order channels under the spectrum, energy, and spectrum-energy limited regimes. After that, a scheduling and assignment heuristic is proposed and is shown to perform very close to the exhaustive optimal solution. Finally, the behavior of the CRN is numerically analyzed under these regimes with respect to different numbers of SUs, PCs, and sensing qualities.

Templated synthesis, characterization, and sensing application of macroscopic platinum nanowire network electrodes

DEFF Research Database (Denmark)

Wang, D. H.; Kou, R.; Gil, M. P.

2005-01-01

properties of the electrodes, such as electrochemical active area and methanol oxidation, have also been studied. Compared with conventional polycrystalline Pt electrodes, these novel nanowire network electrodes possess high electrochemical active areas and demonstrate higher current densities and a lower...... onset potential for methanol electro-oxidation. Enzymatic Pt nanowire-network-based sensors show higher sensitivity for glucose detection than that using conventional polycrystalline Pt electrode. Such macroscopic nanowire network electrodes provide ideal platforms for sensing and other device......Abstract: Novel platinum nanowire network electrodes have been fabricated through electrodeposition using mesoporous silica thin films as templates. These electrodes were characterized by X-ray diffraction, transmission electron microscope, and scanning electron microscope. The electrochemical...

A review and analysis of neural networks for classification of remotely sensed multispectral imagery

Science.gov (United States)

Paola, Justin D.; Schowengerdt, Robert A.

1993-01-01

A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks

KAUST Repository

Al-Halafi, Abdullah

2016-09-08

Wireless sensor networks (WSN) are widely used to sense and measure physical conditions for different purposes and within different regions. However due to the limited lifetime of the sensor\\'s energy source, many efforts are made to design energy efficient WSN. As a result, many techniques were presented in the literature such as power adaptation, sleep and wake-up, and scheduling in order to enhance WSN lifetime. These techniques where presented separately and shown to achieve some gain in terms of energy efficiency. In this paper, we present an energy efficient cross layer design for WSN that we named \\'green Task-Based Sensing\\' (gTBS) scheme. The gTBS design is a task based sensing scheme that not only prevents wasting power in unnecessary signaling, but also utilizes several techniques for achieving reliable and energy efficient WSN. The proposed gTBS combines the power adaptation with a sleep and wake-up technique that allows inactive nodes to sleep. Also, it adopts a gradient-oriented unicast approach to overcome the synchronization problem, minimize network traffic hurdles, and significantly reduce the overall power consumption of the network. We implement the gTBS on a testbed and we show that it reduces the power consumption by a factor of 20%-55% compared to traditional TBS. It also reduces the delay by 54%-145% and improves the delivery ratio by 24%-73%. © 2016 IEEE.

Wireless Damage Location Sensing System

Science.gov (United States)

Woodard, Stanley E. (Inventor); Taylor, Bryant Douglas (Inventor)

2012-01-01

A wireless damage location sensing system uses a geometric-patterned wireless sensor that resonates in the presence of a time-varying magnetic field to generate a harmonic response that will experience a change when the sensor experiences a change in its geometric pattern. The sensing system also includes a magnetic field response recorder for wirelessly transmitting the time-varying magnetic field and for wirelessly detecting the harmonic response. The sensing system compares the actual harmonic response to a plurality of predetermined harmonic responses. Each predetermined harmonic response is associated with a severing of the sensor at a corresponding known location thereof so that a match between the actual harmonic response and one of the predetermined harmonic responses defines the known location of the severing that is associated therewith.

TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications.

Science.gov (United States)

Costa, Daniel G; Duran-Faundez, Cristian; Andrade, Daniel C; Rocha-Junior, João B; Peixoto, João Paulo Just

2018-04-03

Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter , and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events.

TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications

Directory of Open Access Journals (Sweden)

Daniel G. Costa

2018-04-01

Full Text Available Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter, and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

Science.gov (United States)

Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

Collaboratively Adaptive Vibration Sensing System for High-fidelity Monitoring of Structural Responses Induced by Pedestrians

Directory of Open Access Journals (Sweden)

Shijia Pan

2017-05-01

Full Text Available This paper presents a collaboratively adaptive vibration monitoring system that captures high-fidelity structural vibration signals induced by pedestrians. These signals can be used for various human activities’ monitoring by inferring information about the impact sources, such as pedestrian footsteps, door opening and closing, and dragging objects. Such applications often require high-fidelity (high resolution and low distortion signals. Traditionally, expensive high resolution and high dynamic range sensors are adopted to ensure sufficient resolution. However, for sensing systems that use low-cost sensing devices, the resolution and dynamic range are often limited; hence this type of sensing methods is not well explored ubiquitously. We propose a low-cost sensing system that utilizes (1 a heuristic model of the investigating excitations and (2 shared information through networked devices to adapt hardware configurations and obtain high-fidelity structural vibration signals. To further explain the system, we use indoor pedestrian footstep sensing through ambient structural vibration as an example to demonstrate the system performance. We evaluate the application with three metrics that measure the signal quality from different aspects: the sufficient resolution rate to present signal resolution improvement without clipping, the clipping rate to measure the distortion of the footstep signal, and the signal magnitude to quantify the detailed resolution of the detected footstep signal. In experiments conducted in a school building, our system demonstrated up to 2× increase on the sufficient resolution rate and 2× less error rate when used to locate the pedestrians as they walk along the hallway, compared to a fixed sensing setting.

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems.

Science.gov (United States)

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-12-12

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.

Portable remote sensing image processing system; Kahangata remote sensing gazo shori system

Energy Technology Data Exchange (ETDEWEB)

Fujikawa, S; Uchida, K; Tanaka, S; Jingo, H [Dowa Engineering Co. Ltd., Tokyo (Japan); Hato, M [Earth Remote Sensing Data Analysis Center, Tokyo (Japan)

1997-10-22

Recently, geological analysis using remote sensing data has been put into practice due to data with high spectral resolution and high spatial resolution. There has been a remarkable increase in both software and hardware of personal computer. Software is independent of hardware due to Windows. It has become easy to develop softwares. Under such situation, a portable remote sensing image processing system coping with Window 95 has been developed. Using this system, basic image processing can be conducted, and present location can be displayed on the image in real time by linking with GPS. Accordingly, it is not required to bring printed images for the field works of image processing. This system can be used instead of topographic maps for overseas surveys. Microsoft Visual C++ ver. 2.0 is used for the software. 1 fig.

PERFORMANCE OF OPPORTUNISTIC SPECTRUM ACCESS WITH SENSING ERROR IN COGNITIVE RADIO AD HOC NETWORKS

Directory of Open Access Journals (Sweden)

N. ARMI

2012-04-01

Full Text Available Sensing in opportunistic spectrum access (OSA has a responsibility to detect the available channel by performing binary hypothesis as busy or idle states. If channel is busy, secondary user (SU cannot access and refrain from data transmission. SU is allowed to access when primary user (PU does not use it (idle states. However, channel is sensed on imperfect communication link. Fading, noise and any obstacles existed can cause sensing errors in PU signal detection. False alarm detects idle states as a busy channel while miss-identification detects busy states as an idle channel. False detection makes SU refrain from transmission and reduces number of bits transmitted. On the other hand, miss-identification causes SU collide to PU transmission. This paper study the performance of OSA based on the greedy approach with sensing errors by the restriction of maximum collision probability allowed (collision threshold by PU network. The throughput of SU and spectrum capacity metric is used to evaluate OSA performance and make comparisons to those ones without sensing error as function of number of slot based on the greedy approach. The relations between throughput and signal to noise ratio (SNR with different collision probability as well as false detection with different SNR are presented. According to the obtained results show that CR users can gain the reward from the previous slot for both of with and without sensing errors. It is indicated by the throughput improvement as slot number increases. However, sensing on imperfect channel with sensing errors can degrade the throughput performance. Subsequently, the throughput of SU and spectrum capacity improves by increasing maximum collision probability allowed by PU network as well. Due to frequent collision with PU, the throughput of SU and spectrum capacity decreases at certain value of collision threshold. Computer simulation is used to evaluate and validate these works.

System-Aware Smart Network Management for Nano-Enriched Water Quality Monitoring

Directory of Open Access Journals (Sweden)

B. Mokhtar

2016-01-01

Full Text Available This paper presents a comprehensive water quality monitoring system that employs a smart network management, nano-enriched sensing framework, and intelligent and efficient data analysis and forwarding protocols for smart and system-aware decision making. The presented system comprises two main subsystems, a data sensing and forwarding subsystem (DSFS, and Operation Management Subsystem (OMS. The OMS operates based on real-time learned patterns and rules of system operations projected from the DSFS to manage the entire network of sensors. The main tasks of OMS are to enable real-time data visualization, managed system control, and secure system operation. The DSFS employs a Hybrid Intelligence (HI scheme which is proposed through integrating an association rule learning algorithm with fuzzy logic and weighted decision trees. The DSFS operation is based on profiling and registering raw data readings, generated from a set of optical nanosensors, as profiles of attribute-value pairs. As a case study, we evaluate our implemented test bed via simulation scenarios in a water quality monitoring framework. The monitoring processes are simulated based on measuring the percentage of dissolved oxygen and potential hydrogen (PH in fresh water. Simulation results show the efficiency of the proposed HI-based methodology at learning different water quality classes.

On the Feedback Reduction of Relay Multiuser Networks using Compressive Sensing

KAUST Repository

Elkhalil, Khalil

2016-01-29

This paper presents a comprehensive performance analysis of full-duplex multiuser relay networks employing opportunistic scheduling with noisy and compressive feedback. Specifically, two feedback techniques based on compressive sensing (CS) theory are introduced and their effect on the system performance is analyzed. The problem of joint user identity and signal-tonoise ratio (SNR) estimation at the base-station is casted as a block sparse signal recovery problem in CS. Using existing CS block recovery algorithms, the identity of the strong users is obtained and their corresponding SNRs are estimated using the best linear unbiased estimator (BLUE). To minimize the effect of feedback noise on the estimated SNRs, a back-off strategy that optimally backs-off on the noisy estimated SNRs is introduced, and the error covariance matrix of the noise after CS recovery is derived. Finally, closed-form expressions for the end-to-end SNRs of the system are derived. Numerical results show that the proposed techniques drastically reduce the feedback air-time and achieve a rate close to that obtained by scheduling techniques that require dedicated error-free feedback from all network users. Key findings of this paper suggest that the choice of half-duplex or full-duplex SNR feedback is dependent on the channel coherence interval, and on low coherence intervals, full-duplex feedback is superior to the interference-free half-duplex feedback.

Training Small Networks for Scene Classification of Remote Sensing Images via Knowledge Distillation

Directory of Open Access Journals (Sweden)

Guanzhou Chen

2018-05-01

Full Text Available Scene classification, aiming to identify the land-cover categories of remotely sensed image patches, is now a fundamental task in the remote sensing image analysis field. Deep-learning-model-based algorithms are widely applied in scene classification and achieve remarkable performance, but these high-level methods are computationally expensive and time-consuming. Consequently in this paper, we introduce a knowledge distillation framework, currently a mainstream model compression method, into remote sensing scene classification to improve the performance of smaller and shallower network models. Our knowledge distillation training method makes the high-temperature softmax output of a small and shallow student model match the large and deep teacher model. In our experiments, we evaluate knowledge distillation training method for remote sensing scene classification on four public datasets: AID dataset, UCMerced dataset, NWPU-RESISC dataset, and EuroSAT dataset. Results show that our proposed training method was effective and increased overall accuracy (3% in AID experiments, 5% in UCMerced experiments, 1% in NWPU-RESISC and EuroSAT experiments for small and shallow models. We further explored the performance of the student model on small and unbalanced datasets. Our findings indicate that knowledge distillation can improve the performance of small network models on datasets with lower spatial resolution images, numerous categories, as well as fewer training samples.

Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks

Directory of Open Access Journals (Sweden)

Rui Guo

2018-03-01

Full Text Available Considering the classification of high spatial resolution remote sensing imagery, this paper presents a novel classification method for such imagery using deep neural networks. Deep learning methods, such as a fully convolutional network (FCN model, achieve state-of-the-art performance in natural image semantic segmentation when provided with large-scale datasets and respective labels. To use data efficiently in the training stage, we first pre-segment training images and their labels into small patches as supplements of training data using graph-based segmentation and the selective search method. Subsequently, FCN with atrous convolution is used to perform pixel-wise classification. In the testing stage, post-processing with fully connected conditional random fields (CRFs is used to refine results. Extensive experiments based on the Vaihingen dataset demonstrate that our method performs better than the reference state-of-the-art networks when applied to high-resolution remote sensing imagery classification.

System design choices in smartautonomous networked irrigation systems

OpenAIRE

Öberg, Kim; Simonsson, Johanna

2014-01-01

Wireless Sensor Networks are often deployed in great numbers spanning large, sometimes hard to reach and hostile, areas with the aim of monitoring environmental conditions through the use of different sensors. Due to decreasing costs of ownership (e.g. non-proprietary protocols), recent advances in processor, radio, and memory technologies and the engineering of increasingly smaller sensing devices, the availability and area of application for wireless sensor networks have steadily been incre...

Boolean network model of the Pseudomonas aeruginosa quorum sensing circuits.

Science.gov (United States)

Dallidis, Stylianos E; Karafyllidis, Ioannis G

2014-09-01

To coordinate their behavior and virulence and to synchronize attacks against their hosts, bacteria communicate by continuously producing signaling molecules (called autoinducers) and continuously monitoring the concentration of these molecules. This communication is controlled by biological circuits called quorum sensing (QS) circuits. Recently QS circuits and have been recognized as an alternative target for controlling bacterial virulence and infections without the use of antibiotics. Pseudomonas aeruginosa is a Gram-negative bacterium that infects insects, plants, animals and humans and can cause acute infections. This bacterium has three interconnected QS circuits that form a very complex and versatile QS system, the operation of which is still under investigation. Here we use Boolean networks to model the complete QS system of Pseudomonas aeruginosa and we simulate and analyze its operation in both synchronous and asynchronous modes. The state space of the QS system is constructed and it turned out to be very large, hierarchical, modular and scale-free. Furthermore, we developed a simulation tool that can simulate gene knock-outs and study their effect on the regulons controlled by the three QS circuits. The model and tools we developed will give to life scientists a deeper insight to this complex QS system.

Space remote sensing systems an introduction

CERN Document Server

Chen, H S

1985-01-01

Space Remote Sensing Systems: An Introduction discusses the space remote sensing system, which is a modern high-technology field developed from earth sciences, engineering, and space systems technology for environmental protection, resource monitoring, climate prediction, weather forecasting, ocean measurement, and many other applications. This book consists of 10 chapters. Chapter 1 describes the science of the atmosphere and the earth's surface. Chapter 2 discusses spaceborne radiation collector systems, while Chapter 3 focuses on space detector and CCD systems. The passive space optical rad

Mathematical Analysis of a PDE System for Biological Network Formation

KAUST Repository

Haskovec, Jan

2015-02-04

Motivated by recent physics papers describing rules for natural network formation, we study an elliptic-parabolic system of partial differential equations proposed by Hu and Cai [13, 15]. The model describes the pressure field thanks to Darcy\\'s type equation and the dynamics of the conductance network under pressure force effects with a diffusion rate D >= 0 representing randomness in the material structure. We prove the existence of global weak solutions and of local mild solutions and study their long term behavior. It turns out that, by energy dissipation, steady states play a central role to understand the network formation capacity of the system. We show that for a large diffusion coefficient D, the zero steady state is stable, while network formation occurs for small values of D due to the instability of the zero steady state, and the borderline case D = 0 exhibits a large class of dynamically stable (in the linearized sense) steady states.

Monitoring of Thermal Protection Systems Using Robust Self-Organizing Optical Fiber Sensing Networks

Science.gov (United States)

Richards, Lance

2013-01-01

The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, and an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during re-entry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry

Optical chaos and hybrid WDM/TDM based large capacity quasi-distributed sensing network with real-time fiber fault monitoring.

Science.gov (United States)

Luo, Yiyang; Xia, Li; Xu, Zhilin; Yu, Can; Sun, Qizhen; Li, Wei; Huang, Di; Liu, Deming

2015-02-09

An optical chaos and hybrid wavelength division multiplexing/time division multiplexing (WDM/TDM) based large capacity quasi-distributed sensing network with real-time fiber fault monitoring is proposed. Chirped fiber Bragg grating (CFBG) intensity demodulation is adopted to improve the dynamic range of the measurements. Compared with the traditional sensing interrogation methods in time, radio frequency and optical wavelength domains, the measurand sensing and the precise locating of the proposed sensing network can be simultaneously interrogated by the relative amplitude change (RAC) and the time delay of the correlation peak in the cross-correlation spectrum. Assisted with the WDM/TDM technology, hundreds of sensing units could be potentially multiplexed in the multiple sensing fiber lines. Based on the proof-of-concept experiment for axial strain measurement with three sensing fiber lines, the strain sensitivity up to 0.14% RAC/με and the precise locating of the sensors are achieved. Significantly, real-time fiber fault monitoring in the three sensing fiber lines is also implemented with a spatial resolution of 2.8 cm.

An Adaptive Joint Sparsity Recovery for Compressive Sensing Based EEG System

Directory of Open Access Journals (Sweden)

Hamza Djelouat

2017-01-01

Full Text Available The last decade has witnessed tremendous efforts to shape the Internet of things (IoT platforms to be well suited for healthcare applications. These platforms are comprised of a network of wireless sensors to monitor several physical and physiological quantities. For instance, long-term monitoring of brain activities using wearable electroencephalogram (EEG sensors is widely exploited in the clinical diagnosis of epileptic seizures and sleeping disorders. However, the deployment of such platforms is challenged by the high power consumption and system complexity. Energy efficiency can be achieved by exploring efficient compression techniques such as compressive sensing (CS. CS is an emerging theory that enables a compressed acquisition using well-designed sensing matrices. Moreover, system complexity can be optimized by using hardware friendly structured sensing matrices. This paper quantifies the performance of a CS-based multichannel EEG monitoring. In addition, the paper exploits the joint sparsity of multichannel EEG using subspace pursuit (SP algorithm as well as a designed sparsifying basis in order to improve the reconstruction quality. Furthermore, the paper proposes a modification to the SP algorithm based on an adaptive selection approach to further improve the performance in terms of reconstruction quality, execution time, and the robustness of the recovery process.

Intelligent hand-portable proliferation sensing system

International Nuclear Information System (INIS)

Dieckman, S.L.; Bostrom, G.A.; Waterfield, L.G.; Jendrzejczyk, J.A.; Ahuja, S.; Raptis, A.C.

1997-01-01

Argonne National Laboratory, with support from DOE's Office of Nonproliferation and National Security, is currently developing an intelligent hand-portable sensor system. This system is designed specifically to support the intelligence community with the task of in-field sensing of nuclear proliferation and related activities. Based upon pulsed laser photo-ionization time-of-flight mass spectrometry technology, this novel sensing system is capable of quickly providing a molecular or atomic analysis of specimens. The system is capable of analyzing virtually any gas phase molecule, or molecule that can be induced into the gas phase by (for example) sample heating. This system has the unique advantages of providing unprecedented portability, excellent sensitivity, tremendous fieldability, and a high performance/cost ratio. The system will be capable of operating in a highly automated manner for on-site inspections, and easily modified for other applications such as perimeter monitoring aboard a plane or drone. The paper describes the sensing system

Differentially Private Distributed Sensing

Energy Technology Data Exchange (ETDEWEB)

Fink, Glenn A.

2016-12-11

The growth of the Internet of Things (IoT) creates the possibility of decentralized systems of sensing and actuation, potentially on a global scale. IoT devices connected to cloud networks can offer Sensing and Actuation as a Service (SAaaS) enabling networks of sensors to grow to a global scale. But extremely large sensor networks can violate privacy, especially in the case where IoT devices are mobile and connected directly to the behaviors of people. The thesis of this paper is that by adapting differential privacy (adding statistically appropriate noise to query results) to groups of geographically distributed sensors privacy could be maintained without ever sending all values up to a central curator and without compromising the overall accuracy of the data collected. This paper outlines such a scheme and performs an analysis of differential privacy techniques adapted to edge computing in a simulated sensor network where ground truth is known. The positive and negative outcomes of employing differential privacy in distributed networks of devices are discussed and a brief research agenda is presented.

Spectrum Sensing and Primary User Localization in Cognitive Radio Networks via Sparsity

Directory of Open Access Journals (Sweden)

Lanchao Liu

2016-01-01

Full Text Available The theory of compressive sensing (CS has been employed to detect available spectrum resource in cognitive radio (CR networks recently. Capitalizing on the spectrum resource underutilization and spatial sparsity of primary user (PU locations, CS enables the identification of the unused spectrum bands and PU locations at a low sampling rate. Although CS has been studied in the cooperative spectrum sensing mechanism in which CR nodes work collaboratively to accomplish the spectrum sensing and PU localization task, many important issues remain unsettled. Does the designed compressive spectrum sensing mechanism satisfy the Restricted Isometry Property, which guarantees a successful recovery of the original sparse signal? Can the spectrum sensing results help the localization of PUs? What are the characteristics of localization errors? To answer those questions, we try to justify the applicability of the CS theory to the compressive spectrum sensing framework in this paper, and propose a design of PU localization utilizing the spectrum usage information. The localization error is analyzed by the Cramér-Rao lower bound, which can be exploited to improve the localization performance. Detail analysis and simulations are presented to support the claims and demonstrate the efficacy and efficiency of the proposed mechanism.

Communication-Free Distributed Coverage for Networked Systems

KAUST Repository

Yazicioglu, A. Yasin

2016-01-15

In this paper, we present a communication-free algorithm for distributed coverage of an arbitrary network by a group of mobile agents with local sensing capabilities. The network is represented as a graph, and the agents are arbitrarily deployed on some nodes of the graph. Any node of the graph is covered if it is within the sensing range of at least one agent. The agents are mobile devices that aim to explore the graph and to optimize their locations in a decentralized fashion by relying only on their sensory inputs. We formulate this problem in a game theoretic setting and propose a communication-free learning algorithm for maximizing the coverage.

Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment

Directory of Open Access Journals (Sweden)

P. W. Thorne

2017-11-01

Full Text Available There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies, etc. The Horizon 2020 project GAIA–CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is correct. Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available and maintains rich metadata. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based on such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate on networks measuring primarily a subset of the atmospheric Essential Climate Variables of interest to GAIA–CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream example applications of the GAIA–CLIM project. However, the approach laid out should be more widely applicable across

Poster Abstract: Towards a Categorization Framework for Occupancy Sensing Systems

DEFF Research Database (Denmark)

Kjærgaard, Mikkel Baun; Lazarova-Molnar, Sanja; Jradi, Muhyiddine

2015-01-01

on occupancy sensing systems goes beyond basic methods, there is an increasing need for better comparison of proposed occupancy sensing systems. Developers of occupancy sensing systems are also lacking good frameworks for understanding different options when building occupancy sensing systems. This poster...

(abstract) Deep Space Network Radiometric Remote Sensing Program

Science.gov (United States)

Walter, Steven J.

1994-01-01

Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid,and precipitation , emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band becausecommunication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of watervapor-induced prop agation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity waveexperiments, and r adio science missions. During 1993, WVRs provided data for propagation mode development, supp orted planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily

Recent Progress of Self-Powered Sensing Systems for Wearable Electronics.

Science.gov (United States)

Lou, Zheng; Li, La; Wang, Lili; Shen, Guozhen

2017-12-01

Wearable/flexible electronic sensing systems are considered to be one of the key technologies in the next generation of smart personal electronics. To realize personal portable devices with mobile electronics application, i.e., wearable electronic sensors that can work sustainably and continuously without an external power supply are highly desired. The recent progress and advantages of wearable self-powered electronic sensing systems for mobile or personal attachable health monitoring applications are presented. An overview of various types of wearable electronic sensors, including flexible tactile sensors, wearable image sensor array, biological and chemical sensor, temperature sensors, and multifunctional integrated sensing systems is provided. Self-powered sensing systems with integrated energy units are then discussed, separated as energy harvesting self-powered sensing systems, energy storage integrated sensing systems, and all-in-on integrated sensing systems. Finally, the future perspectives of self-powered sensing systems for wearable electronics are discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Devising Mobile Sensing and Actuation Infrastructure with Drones

Directory of Open Access Journals (Sweden)

Mungyu Bae

2018-02-01

Full Text Available Vast applications and services have been enabled as the number of mobile or sensing devices with communication capabilities has grown. However, managing the devices, integrating networks or combining services across different networks has become a new problem since each network is not directly connected via back-end core networks or servers. The issue is and has been discussed especially in wireless sensor and actuator networks (WSAN. In such systems, sensors and actuators are tightly coupled, so when an independent WSAN needs to collaborate with other networks, it is difficult to adequately combine them into an integrated infrastructure. In this paper, we propose drone-as-a-gateway (DaaG, which uses drones as mobile gateways to interconnect isolated networks or combine independent services. Our system contains features that focus on the service being provided in the order of importance, different from an adaptive simple mobile sink system or delay-tolerant system. Our simulation results have shown that the proposed system is able to activate actuators in the order of importance of the service, which uses separate sensors’ data, and it consumes almost the same time in comparison with other path-planning algorithms. Moreover, we have implemented DaaG and presented results in a field test to show that it can enable large-scale on-demand deployment of sensing and actuation infrastructure or the Internet of Things (IoT.

Devising Mobile Sensing and Actuation Infrastructure with Drones

Science.gov (United States)

Jung, Jongtack; Park, Seongjoon; Kim, Kangho; Lee, Joon Yeop

2018-01-01

Vast applications and services have been enabled as the number of mobile or sensing devices with communication capabilities has grown. However, managing the devices, integrating networks or combining services across different networks has become a new problem since each network is not directly connected via back-end core networks or servers. The issue is and has been discussed especially in wireless sensor and actuator networks (WSAN). In such systems, sensors and actuators are tightly coupled, so when an independent WSAN needs to collaborate with other networks, it is difficult to adequately combine them into an integrated infrastructure. In this paper, we propose drone-as-a-gateway (DaaG), which uses drones as mobile gateways to interconnect isolated networks or combine independent services. Our system contains features that focus on the service being provided in the order of importance, different from an adaptive simple mobile sink system or delay-tolerant system. Our simulation results have shown that the proposed system is able to activate actuators in the order of importance of the service, which uses separate sensors’ data, and it consumes almost the same time in comparison with other path-planning algorithms. Moreover, we have implemented DaaG and presented results in a field test to show that it can enable large-scale on-demand deployment of sensing and actuation infrastructure or the Internet of Things (IoT). PMID:29463064

Devising Mobile Sensing and Actuation Infrastructure with Drones.

Science.gov (United States)

Bae, Mungyu; Yoo, Seungho; Jung, Jongtack; Park, Seongjoon; Kim, Kangho; Kim, Joon Yeop Lee; Kim, Hwangnam

2018-02-19

Vast applications and services have been enabled as the number of mobile or sensing devices with communication capabilities has grown. However, managing the devices, integrating networks or combining services across different networks has become a new problem since each network is not directly connected via back-end core networks or servers. The issue is and has been discussed especially in wireless sensor and actuator networks (WSAN). In such systems, sensors and actuators are tightly coupled, so when an independent WSAN needs to collaborate with other networks, it is difficult to adequately combine them into an integrated infrastructure. In this paper, we propose drone-as-a-gateway (DaaG), which uses drones as mobile gateways to interconnect isolated networks or combine independent services. Our system contains features that focus on the service being provided in the order of importance, different from an adaptive simple mobile sink system or delay-tolerant system. Our simulation results have shown that the proposed system is able to activate actuators in the order of importance of the service, which uses separate sensors' data, and it consumes almost the same time in comparison with other path-planning algorithms. Moreover, we have implemented DaaG and presented results in a field test to show that it can enable large-scale on-demand deployment of sensing and actuation infrastructure or the Internet of Things (IoT).

Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks.

Science.gov (United States)

Zheng, Haifeng; Li, Jiayin; Feng, Xinxin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

2017-11-08

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs .

Compressive Sensing for Feedback Reduction in Wireless Multiuser Networks

KAUST Repository

Elkhalil, Khalil

2015-05-01

User/relay selection is a simple technique that achieves spatial diversity in multiuser networks. However, for user/relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating users/relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed-back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. Motivated by the aforementioned challenges, we propose a limited feedback user/relay selection scheme that is based on the theory of compressed sensing. Firstly, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback air-time. Following that, the CSI of the selected relays is estimated using minimum mean square error estimation without any additional feedback. To minimize the effect of noise on the fed-back CSI, we introduce a back-off strategy that optimally backs-off on the noisy received CSI. In the second part of the thesis, we propose a feedback reduction scheme for full-duplex relay-aided multiuser networks. The proposed scheme permits the base station (BS) to obtain channel state information (CSI) from a subset of strong users under substantially reduced feedback overhead. More specifically, we cast the problem of user identification and CSI estimation as a block sparse signal recovery problem in compressive sensing (CS). Using existing CS block recovery algorithms, we first obtain the identity of the strong users and then estimate their CSI using the best linear unbiased estimator (BLUE). Moreover, we derive the

Distributed Weak Fiber Bragg Grating Vibration Sensing System Based on 3 × 3 Fiber Coupler

Science.gov (United States)

Li, Wei; Zhang, Jian

2018-06-01

A novel distributed weak fiber Bragg gratings (FBGs) vibration sensing system has been designed to overcome the disadvantages of the conventional methods for optical fiber sensing networking, which are: low signal intensity in the usually adopted time-division multiplexing (TDM) technology, insufficient quantity of multiplexed FBGs in the wavelength-division multiplexing (WDM) technology, and that the mixed WDM/TDM technology measures only the physical parameters of the FBG locations but cannot perform distributed measurement over the whole optical fiber. This novel system determines vibration events in the optical fiber line according to the intensity variation of the interference signals between the adjacent weak FBG reflected signals and locates the vibration points accurately using the TDM technology. It has been proven by tests that this system performs vibration signal detection and demodulation in a way more convenient than the conventional methods for the optical fiber sensing system. It also measures over the whole optical fiber, therefore, distributed measurement is fulfilled, and the system locating accuracy is up to 20 m, capable of detecting any signals of whose drive signals lower limit voltage is 0.2 V while the frequency range is 3 Hz‒1 000 Hz. The system has the great practical significance and application value for perimeter surveillance systems.

Hard Fusion Based Spectrum Sensing over Mobile Fading Channels in Cognitive Vehicular Networks.

Science.gov (United States)

Qian, Xiaomin; Hao, Li; Ni, Dadong; Tran, Quang Thanh

2018-02-06

An explosive growth in vehicular wireless applications gives rise to spectrum resource starvation. Cognitive radio has been used in vehicular networks to mitigate the impending spectrum starvation problem by allowing vehicles to fully exploit spectrum opportunities unoccupied by licensed users. Efficient and effective detection of licensed user is a critical issue to realize cognitive radio applications. However, spectrum sensing in vehicular environments is a very challenging task due to vehicle mobility. For instance, vehicle mobility has a large effect on the wireless channel, thereby impacting the detection performance of spectrum sensing. Thus, gargantuan efforts have been made in order to analyze the fading properties of mobile radio channel in vehicular environments. Indeed, numerous studies have demonstrated that the wireless channel in vehicular environments can be characterized by a temporally correlated Rayleigh fading. In this paper, we focus on energy detection for spectrum sensing and a counting rule for cooperative sensing based on Neyman-Pearson criteria. Further, we go into the effect of the sensing and reporting channel conditions on the sensing performance under the temporally correlated Rayleigh channel. For local and cooperative sensing, we derive some alternative expressions for the average probability of misdetection. The pertinent numerical and simulating results are provided to further validate our theoretical analyses under a variety of scenarios.

Active Sensing System with In Situ Adjustable Sensor Morphology

Science.gov (United States)

Nurzaman, Surya G.; Culha, Utku; Brodbeck, Luzius; Wang, Liyu; Iida, Fumiya

2013-01-01

Background Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. Methodology This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. Conclusions/Significance The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed. PMID:24416094

Active sensing system with in situ adjustable sensor morphology.

Science.gov (United States)

Nurzaman, Surya G; Culha, Utku; Brodbeck, Luzius; Wang, Liyu; Iida, Fumiya

2013-01-01

Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed.

Sparse Channel Estimation for MIMO-OFDM Two-Way Relay Network with Compressed Sensing

Directory of Open Access Journals (Sweden)

Aihua Zhang

2013-01-01

Full Text Available Accurate channel impulse response (CIR is required for equalization and can help improve communication service quality in next-generation wireless communication systems. An example of an advanced system is amplify-and-forward multiple-input multiple-output two-way relay network, which is modulated by orthogonal frequency-division multiplexing. Linear channel estimation methods, for example, least squares and expectation conditional maximization, have been proposed previously for the system. However, these methods do not take advantage of channel sparsity, and they decrease estimation performance. We propose a sparse channel estimation scheme, which is different from linear methods, at end users under the relay channel to enable us to exploit sparsity. First, we formulate the sparse channel estimation problem as a compressed sensing problem by using sparse decomposition theory. Second, the CIR is reconstructed by CoSaMP and OMP algorithms. Finally, computer simulations are conducted to confirm the superiority of the proposed methods over traditional linear channel estimation methods.

A localized cooperative wideband spectrum sensing for dynamic access of TV bands using RF sensor networks

KAUST Repository

Mirza, Mohammed

2011-07-01

In this paper we address and simulate a Radio Frequency (RF) sensor network for a cooperative spectrum sensing and localization scheme. The proposed method integrates a Wavelet based Multi-Resolution Spectrum Sensing (MRSS), an N-bit hard combination technique for cooperative decision making and a Received Signal Strength (RSS) based localization algorithm to detect the availability of frequency bands and the location of the usable base station. We develop an N-bit hard combination technique and compare its performance to a traditionally used 2-bit hard combination for cooperative sensing. The key idea is to design a novel RF sensor network based cooperative wideband spectrum sensing and localization scheme by using a wavelet based Multi-Resolution Spectrum Sensing (MRSS) and Received Signal Strength (RSS) Localization techniques which were originally proposed for cognitive radio applications. The performance evaluations are also done to show the different detection accuracies for varying parameters such as number of sensor nodes, Signal to Noise Ratios (SNR) and number of averaged Power Spectral Densities (PSD). The proposed scheme improves the problems of shadowing, fading and noise. In addition, the RSS based localization technique was shown to be an acceptable means of estimating the position of the available transmitter. © 2011 IEEE.

A Nonlinear Multiparameters Temperature Error Modeling and Compensation of POS Applied in Airborne Remote Sensing System

Directory of Open Access Journals (Sweden)

Jianli Li

2014-01-01

Full Text Available The position and orientation system (POS is a key equipment for airborne remote sensing systems, which provides high-precision position, velocity, and attitude information for various imaging payloads. Temperature error is the main source that affects the precision of POS. Traditional temperature error model is single temperature parameter linear function, which is not sufficient for the higher accuracy requirement of POS. The traditional compensation method based on neural network faces great problem in the repeatability error under different temperature conditions. In order to improve the precision and generalization ability of the temperature error compensation for POS, a nonlinear multiparameters temperature error modeling and compensation method based on Bayesian regularization neural network was proposed. The temperature error of POS was analyzed and a nonlinear multiparameters model was established. Bayesian regularization method was used as the evaluation criterion, which further optimized the coefficients of the temperature error. The experimental results show that the proposed method can improve temperature environmental adaptability and precision. The developed POS had been successfully applied in airborne TSMFTIS remote sensing system for the first time, which improved the accuracy of the reconstructed spectrum by 47.99%.

Cascade Convolutional Neural Network Based on Transfer-Learning for Aircraft Detection on High-Resolution Remote Sensing Images

Directory of Open Access Journals (Sweden)

Bin Pan

2017-01-01

Full Text Available Aircraft detection from high-resolution remote sensing images is important for civil and military applications. Recently, detection methods based on deep learning have rapidly advanced. However, they require numerous samples to train the detection model and cannot be directly used to efficiently handle large-area remote sensing images. A weakly supervised learning method (WSLM can detect a target with few samples. However, it cannot extract an adequate number of features, and the detection accuracy requires improvement. We propose a cascade convolutional neural network (CCNN framework based on transfer-learning and geometric feature constraints (GFC for aircraft detection. It achieves high accuracy and efficient detection with relatively few samples. A high-accuracy detection model is first obtained using transfer-learning to fine-tune pretrained models with few samples. Then, a GFC region proposal filtering method improves detection efficiency. The CCNN framework completes the aircraft detection for large-area remote sensing images. The framework first-level network is an image classifier, which filters the entire image, excluding most areas with no aircraft. The second-level network is an object detector, which rapidly detects aircraft from the first-level network output. Compared with WSLM, detection accuracy increased by 3.66%, false detection decreased by 64%, and missed detection decreased by 23.1%.

Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments

Energy Technology Data Exchange (ETDEWEB)

Wang, Anbo [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

2016-09-30

This report summarizes technical progress on the program “Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments” funded by the National Energy Technology Laboratory of the U.S. Department of Energy, and performed by the Center for Photonics Technology at Virginia Tech. The objective of this project is to develop a first-of-a-kind technology for remote fiber optic generation and detection of acoustic waves for structural health monitoring in harsh environments. During the project period, which is from April 1, 2013 to Septemeber 30, 2016, three different acoustic generation mechanisms were studied in detail for their applications in building a fiber optic acoustic generation unit (AGU), including laser induced plasma breakdown (LIP), Erbium-doped fiber laser absorption, and metal laser absorption. By comparing the performance of the AGUs designed based on these three mechanisms and analyzing the experimental results with simulations, the metal laser absorption method was selected to build a complete fiber optic structure health monitoring (FO-SHM) system for the proposed high temperature multi-parameter structure health monitoring application. Based on the simulation of elastic wave propagation and fiber Bragg grating acoustic pulse detection, an FO-SHM element together with a completed interrogation system were designed and built. This system was first tested on an aluminum piece in the low-temperature range and successfully demonstrated its capability of multi-parameter monitoring and multi-point sensing. In the later stages of the project, the research was focused on improving the surface attachment design and preparing the FO-SHM element for high temperature environment tests. After several upgrades to the surface attachment methods, the FO-SHM element was able to work reliably up to 600oC when attached to P91 pipes, which are the target material of this project. In the final stage of this project, this FO

Implementation of Network Leader Sponsored Supply Chain Management Systems: A Case Study of Supplier IT Business Value

Science.gov (United States)

Miller, Mark S.

2010-01-01

This qualitative multiple-case study was conducted to explore and understand how the implementation of required relationship-specific supply chain management system (SCMS) dictated by the network leader within a supplier network affects a supplier organization. The study, on a very broad sense, attempted to research the current validity of how the…

Development of airborne remote sensing data assimilation system

International Nuclear Information System (INIS)

Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W

2014-01-01

In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data

An integrated risk sensing system for geo-structural safety

Institute of Scientific and Technical Information of China (English)

H.W. Huang; D.M. Zhang; B.M. Ayyub

2017-01-01

Over the last decades, geo-structures are experiencing a rapid development in China. The potential risks inherent in the huge amount of construction and asset operation projects in China were well managed in the major project, i.e. the project of Shanghai Yangtze tunnel in 2002. Since then, risk assessment of geo-structures has been gradually developed from a qualitative manner to a quantitative manner. However, the current practices of risk management have been paid considerable attention to the assessment, but little on risk control. As a result, the responses to risks occurrences after a comprehensive assessment are basically too late. In this paper, a smart system for risk sensing incorporating the wireless sensor network (WSN) on-site visualization techniques and the resilience-based repair strategy was proposed. The merit of this system is the real-time monitoring for geo-structural performance and dynamic pre-warning for safety of on-site workers. The sectional convergence, joint opening, and seepage of segmental lining of shield tunnel were monitored by the micro-electro-mechanical systems (MEMS) based sensors. The light emitting diode (LED) coupling with the above WSN system was used to indicate different risk levels on site. By sensing the risks and telling the risks in real time, the geo-risks could be controlled and the safety of geo-structures could be assured to a certain degree. Finally, a resilience-based analysis model was proposed for designing the repair strategy by using the measured data from the WSN system. The application and efficiency of this system have been validated by two cases including Shanghai metro tunnel and underwater road tunnel.

Optical wireless networked-systems: applications to aircrafts

Science.gov (United States)

Kavehrad, Mohsen; Fadlullah, Jarir

2011-01-01

This paper focuses on leveraging the progress in semiconductor technologies to facilitate production of efficient light-based in-flight entertainment (IFE), distributed sensing, navigation and control systems. We demonstrate the ease of configuring "engineered pipes" using cheap lenses, etc. to achieve simple linear transmission capacity growth. Investigation of energy-efficient, miniaturized transceivers will create a wireless medium, for both inter and intra aircrafts, providing enhanced security, and improved quality-of-service for communications links in greater harmony with onboard systems. The applications will seamlessly inter-connect multiple intelligent devices in a network that is deployable for aircrafts navigation systems, onboard sensors and entertainment data delivery systems, and high-definition audio-visual broadcasting systems. Recent experimental results on a high-capacity infrared (808 nm) system are presented. The light source can be applied in a hybrid package along with a visible lighting LED for both lighting and communications. Also, we present a pragmatic combination of light communications through "Spotlighting" and existing onboard power-lines. It is demonstrated in details that a high-capacity IFE visible light system communicating over existing power-lines (VLC/PLC) may lead to savings in many areas through reduction of size, weight and energy consumption. This paper addresses the challenges of integrating optimized optical devices in the variety of environments described above, and presents mitigation and tailoring approaches for a multi-purpose optical network.

Developing a robust wireless sensor network structure for environmental sensing

Science.gov (United States)

Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

The American River Hydrologic Observatory is being strategically deployed as a real-time ground-based measurement network that delivers accurate and timely information on snow conditions and other hydrologic attributes with a previously unheard of granularity of time and space. The basin-scale network involves 18 sub-networks set out at physiographically representative locations spanning the seasonally snow-covered half of the 5000 km2 American river basin. Each sub-network, covering about a 1-km2 area, consists of 10 wirelessly networked sensing nodes that continuously measure and telemeter temperature, and snow depth; plus selected locations are equipped with sensors for relative humidity, solar radiation, and soil moisture at several depths. The sensor locations were chosen to maximize the variance sampled for snow depth within the basin. Network design and deployment involves an iterative but efficient process. After sensor-station locations are determined, a robust network of interlinking sensor stations and signal repeaters must be constructed to route sensor data to a central base station with a two-way communicable data uplink. Data can then be uploaded from site to remote servers in real time through satellite and cell modems. Signal repeaters are placed for robustness of a self-healing network with redundant signal paths to the base station. Manual, trial-and-error heuristic approaches for node placement are inefficient and labor intensive. In that approach field personnel must restructure the network in real time and wait for new network statistics to be calculated at the base station before finalizing a placement, acting without knowledge of the global topography or overall network structure. We show how digital elevation plus high-definition aerial photographs to give foliage coverage can optimize planning of signal repeater placements and guarantee a robust network structure prior to the physical deployment. We can also 'stress test' the final network

Building a sense of virtual community: the role of the features of social networking sites.

Science.gov (United States)

Chen, Chi-Wen; Lin, Chiun-Sin

2014-07-01

In recent years, social networking sites have received increased attention because of the potential of this medium to transform business by building virtual communities. However, theoretical and empirical studies investigating how specific features of social networking sites contribute to building a sense of virtual community (SOVC)-an important dimension of a successful virtual community-are rare. Furthermore, SOVC scales have been developed, and research on this issue has been called for, but few studies have heeded this call. On the basis of prior literature, this study proposes that perceptions of the three most salient features of social networking sites-system quality (SQ), information quality (IQ), and social information exchange (SIE)-play a key role in fostering SOVC. In particular, SQ is proposed to increase IQ and SIE, and SIE is proposed to enhance IQ, both of which thereafter build SOVC. The research model was examined in the context of Facebook, one of the most popular social networking sites in the world. We adopted Blanchard's scales to measure SOVC. Data gathered using a Web-based questionnaire, and analyzed with partial least squares, were utilized to test the model. The results demonstrate that SIE, SQ, and IQ are the factors that form SOVC. The findings also suggest that SQ plays a fundamental role in supporting SIE and IQ in social networking sites. Implications for theory, practice, and future research directions are discussed.

Network Connectedness, Sense of Community, and Risk Perception of Climate Change Professionals in the Pacific Islands Region

Science.gov (United States)

Corlew, L. K.; Keener, V. W.; Finucane, M.

2013-12-01

The Pacific Regional Integrated Sciences and Assessments (Pacific RISA) Program conducted social network analysis research of climate change professionals (broadly defined) who are from or work in Hawaii and the U.S.-Affiliated Pacific Islands (USAPI) region. This study is supported by the National Oceanic and Atmospheric Administration (NOAA) and the Pacific Islands Climate Science Center (PICSC) to address an identified need for a resource that quantifies the region's collaborative network of climate change professionals, and that supports the further development of cross-regional and inter-sectoral collaborations for future research and adaptation activities. A survey was distributed to nearly 1,200 people who are from and/or work in climate change related fields in the region. The Part One Survey questions (not confidential) created a preferential attachment network by listing major players in Hawaii and the USAPI, with additional open fields to identify important contacts in the greater professional network. Participants (n=340) identified 975 network contacts and frequency of communications (weekly, monthly, seasonally, yearly, at least once ever). Part Two Survey questions (confidential, n=302) explored climate change risk perceptions, Psychological Sense of Community (PSOC), sense of control over climate change impacts, sense of responsibility to act, policy beliefs and preferences regarding climate change actions, concern and optimism scales about specific impacts, and demographic information. Graphical representations of the professional network are being developed for release in September 2013 as a free online tool to promote and assist collaboration building among climate professionals in the region. The graphs are partitioned according to network 'hubs' (high centrality), participant location, and profession to clearly identify network strengths and opportunities for future collaborations across spatial and professional boundaries. For additional

Reconstruction of in-plane strain maps using hybrid dense sensor network composed of sensing skin

International Nuclear Information System (INIS)

Downey, Austin; Laflamme, Simon; Ubertini, Filippo

2016-01-01

The authors have recently developed a soft-elastomeric capacitive (SEC)-based thin film sensor for monitoring strain on mesosurfaces. Arranged in a network configuration, the sensing system is analogous to a biological skin, where local strain can be monitored over a global area. Under plane stress conditions, the sensor output contains the additive measurement of the two principal strain components over the monitored surface. In applications where the evaluation of strain maps is useful, in structural health monitoring for instance, such signal must be decomposed into linear strain components along orthogonal directions. Previous work has led to an algorithm that enabled such decomposition by leveraging a dense sensor network configuration with the addition of assumed boundary conditions. Here, we significantly improve the algorithm’s accuracy by leveraging mature off-the-shelf solutions to create a hybrid dense sensor network (HDSN) to improve on the boundary condition assumptions. The system’s boundary conditions are enforced using unidirectional RSGs and assumed virtual sensors. Results from an extensive experimental investigation demonstrate the good performance of the proposed algorithm and its robustness with respect to sensors’ layout. Overall, the proposed algorithm is seen to effectively leverage the advantages of a hybrid dense network for application of the thin film sensor to reconstruct surface strain fields over large surfaces. (paper)

Material requirements for bio-inspired sensing systems

Science.gov (United States)

Biggins, Peter; Lloyd, Peter; Salmond, David; Kusterbeck, Anne

2008-10-01

The aim of developing bio-inspired sensing systems is to try and emulate the amazing sensitivity and specificity observed in the natural world. These capabilities have evolved, often for specific tasks, which provide the organism with an advantage in its fight to survive and prosper. Capabilities cover a wide range of sensing functions including vision, temperature, hearing, touch, taste and smell. For some functions, the capabilities of natural systems are still greater than that achieved by traditional engineering solutions; a good example being a dog's sense of smell. Furthermore, attempting to emulate aspects of biological optics, processing and guidance may lead to more simple and effective devices. A bio-inspired sensing system is much more than the sensory mechanism. A system will need to collect samples, especially if pathogens or chemicals are of interest. Other functions could include the provision of power, surfaces and receptors, structure, locomotion and control. In fact it is possible to conceive of a complete bio-inspired system concept which is likely to be radically different from more conventional approaches. This concept will be described and individual component technologies considered.

Gait Dynamics Sensing Using IMU Sensor Array System

Directory of Open Access Journals (Sweden)

Slavomir Kardos

2017-01-01

Full Text Available The article deals with a progressive approach in gait sensing. It is incorporated by IMU (Inertia Measurement Unit complex sensors whose field of acting is mainly the motion sensing in medicine, automotive and other industry, self-balancing systems, etc. They allow acquiring the position and orientation of an object in 3D space. Using several IMU units the sensing array for gait dynamics was made. Based on human gait analysis the 7-sensor array was designed to build a gait motion dynamics sensing system with the possibility of graphical interpretation of data from the sensing modules in real-time graphical application interface under the LabVIEW platform. The results of analyses can serve as the information for medical diagnostic purposes. The main control part of the system is microcontroller, whose function is to control the data collection and flow, provide the communication and power management.

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment

Directory of Open Access Journals (Sweden)

Muhammad Sohail

2018-03-01

Full Text Available Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node’s transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing, which extends the widely used AODV (Ad hoc On-demand Distance Vector routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network. The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical.

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment.

Science.gov (United States)

Sohail, Muhammad; Wang, Liangmin

2018-03-14

Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node's transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing), which extends the widely used AODV (Ad hoc On-demand Distance Vector) routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network). The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical.

APPLICATION OF CONVOLUTIONAL NEURAL NETWORK IN CLASSIFICATION OF HIGH RESOLUTION AGRICULTURAL REMOTE SENSING IMAGES

Directory of Open Access Journals (Sweden)

C. Yao

2017-09-01

Full Text Available With the rapid development of Precision Agriculture (PA promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN. For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

A Neutral-Network-Fusion Architecture for Automatic Extraction of Oceanographic Features from Satellite Remote Sensing Imagery

National Research Council Canada - National Science Library

Askari, Farid

1999-01-01

This report describes an approach for automatic feature detection from fusion of remote sensing imagery using a combination of neural network architecture and the Dempster-Shafer (DS) theory of evidence...

Artificial intelligence for networks recognition in remote sensing images

Science.gov (United States)

Gilliot, Jean-Marc; Amat, Jean-Louis

1993-12-01

We describe here a knowledge-based system, NEXSYS (Nextwork EXtraction SYStem) which was designed for the recognition of communication networks in SPOT satellite images. NEXSYS is a frame-based system and uses a co-operative and distributed structure based on a blackboard architecture. Communication networks in SPOT images are composed of thin linear segments. Segments are extracted using mathematical morphology and a Hough transform. An intermediate image representation composed of geometric primitives is obtained. Then an expert module is able to process the segments at the symbolic level trying to recognize networks.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range.

Science.gov (United States)

He, Chenlong; Feng, Zuren; Ren, Zhigang

2018-02-03

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham's Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm.

SYMBIOTIC SENSING: Exploring and Exploiting Cooperative Sensing in Heterogeneous Sensor Networks

NARCIS (Netherlands)

Le Viet Duc, L Duc

2016-01-01

During the last several years we have witnessed the emergence of smartphone-based sensing applications that include activity recognition, urban sensing, social sensing, and health monitoring. In fact, most smartphones have various sensors, wireless communication interfaces, a large memory capacity,

Compressed sensing for distributed systems

CERN Document Server

Coluccia, Giulio; Magli, Enrico

2015-01-01

This book presents a survey of the state-of-the art in the exciting and timely topic of compressed sensing for distributed systems. It has to be noted that, while compressed sensing has been studied for some time now, its distributed applications are relatively new. Remarkably, such applications are ideally suited to exploit all the benefits that compressed sensing can provide. The objective of this book is to provide the reader with a comprehensive survey of this topic, from the basic concepts to different classes of centralized and distributed reconstruction algorithms, as well as a comparison of these techniques. This book collects different contributions on these aspects. It presents the underlying theory in a complete and unified way for the first time, presenting various signal models and their use cases. It contains a theoretical part collecting latest results in rate-distortion analysis of distributed compressed sensing, as well as practical implementations of algorithms obtaining performance close to...

Backstepping fuzzy-neural-network control design for hybrid maglev transportation system.

Science.gov (United States)

Wai, Rong-Jong; Yao, Jing-Xiang; Lee, Jeng-Dao

2015-02-01

This paper focuses on the design of a backstepping fuzzy-neural-network control (BFNNC) for the online levitated balancing and propulsive positioning of a hybrid magnetic levitation (maglev) transportation system. The dynamic model of the hybrid maglev transportation system including levitated hybrid electromagnets to reduce the suspension power loss and the friction force during linear movement and a propulsive linear induction motor based on the concepts of mechanical geometry and motion dynamics is first constructed. The ultimate goal is to design an online fuzzy neural network (FNN) control methodology to cope with the problem of the complicated control transformation and the chattering control effort in backstepping control (BSC) design, and to directly ensure the stability of the controlled system without the requirement of strict constraints, detailed system information, and auxiliary compensated controllers despite the existence of uncertainties. In the proposed BFNNC scheme, an FNN control is utilized to be the major control role by imitating the BSC strategy, and adaptation laws for network parameters are derived in the sense of projection algorithm and Lyapunov stability theorem to ensure the network convergence as well as stable control performance. The effectiveness of the proposed control strategy for the hybrid maglev transportation system is verified by experimental results, and the superiority of the BFNNC scheme is indicated in comparison with the BSC strategy and the backstepping particle-swarm-optimization control system in previous research.

A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Yongwei Zhang

2017-01-01

Full Text Available In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.

Facile Preparation of Carbon-Nanotube-based 3-Dimensional Transparent Conducting Networks for Flexible Noncontact Sensing Device

KAUST Repository

Tai, Yanlong; Lubineau, Gilles

2016-01-01

Here, we report the controllable fabrication of transparent conductive films (TCFs) for moisture-sensing applications based on heating-rate-triggered, 3-dimensional porous conducting networks of single-walled carbon nanotube (SWCNT)/poly(3

Mapping biological systems to network systems

CERN Document Server

Rathore, Heena

2016-01-01

The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

Data Collection Method for Mobile Control Sink Node in Wireless Sensor Network Based on Compressive Sensing

Directory of Open Access Journals (Sweden)

Ling Yongfa

2016-01-01

Full Text Available The paper proposes a mobile control sink node data collection method in the wireless sensor network based on compressive sensing. This method, with regular track, selects the optimal data collection points in the monitoring area via the disc method, calcu-lates the shortest path by using the quantum genetic algorithm, and hence determines the data collection route. Simulation results show that this method has higher network throughput and better energy efficiency, capable of collecting a huge amount of data with balanced energy consumption in the network.

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

Science.gov (United States)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Artificial senses for characterization of food quality

Institute of Scientific and Technical Information of China (English)

HUANG Yan-bo; LAN Yu-bin; R.E. Lacey

2004-01-01

Food quality is of primary concern in the food industry and to the consumer. Systems that mimic human senses have been developed and applied to the characterization of food quality. The five primary senses are: vision, hearing, smell, taste and touch.In the characterization of food quality, people assess the samples sensorially and differentiate "good" from "bad" on a continuum.However, the human sensory system is subjective, with mental and physical inconsistencies, and needs time to work. Artificial senses such as machine vision, the electronic ear, electronic nose, electronic tongue, artificial mouth and even artificial the head have been developed that mimic the human senses. These artificial senses are coordinated individually or collectively by a pattern recognition technique, typically artificial neural networks, which have been developed based on studies of the mechanism of the human brain. Such a structure has been used to formulate methods for rapid characterization of food quality. This research presents and discusses individual artificial sensing systems. With the concept of multi-sensor data fusion these sensor systems can work collectively in some way. Two such fused systems, artificial mouth and artificial head, are described and discussed. It indicates that each of the individual systems has their own artificially sensing ability to differentiate food samples. It further indicates that with a more complete mimic of human intelligence the fused systems are more powerful than the individual systems in differentiation of food samples.

Network operating system

Science.gov (United States)

1985-01-01

Long-term and short-term objectives for the development of a network operating system for the Space Station are stated. The short-term objective is to develop a prototype network operating system for a 100 megabit/second fiber optic data bus. The long-term objective is to establish guidelines for writing a detailed specification for a Space Station network operating system. Major milestones are noted. Information is given in outline form.

Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review.

Science.gov (United States)

Zou, Liang; Ge, Chang; Wang, Z Jane; Cretu, Edmond; Li, Xiaoou

2017-11-17

During the last decades, smart tactile sensing systems based on different sensing techniques have been developed due to their high potential in industry and biomedical engineering. However, smart tactile sensing technologies and systems are still in their infancy, as many technological and system issues remain unresolved and require strong interdisciplinary efforts to address them. This paper provides an overview of smart tactile sensing systems, with a focus on signal processing technologies used to interpret the measured information from tactile sensors and/or sensors for other sensory modalities. The tactile sensing transduction and principles, fabrication and structures are also discussed with their merits and demerits. Finally, the challenges that tactile sensing technology needs to overcome are highlighted.

Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review

Directory of Open Access Journals (Sweden)

Liang Zou

2017-11-01

Full Text Available During the last decades, smart tactile sensing systems based on different sensing techniques have been developed due to their high potential in industry and biomedical engineering. However, smart tactile sensing technologies and systems are still in their infancy, as many technological and system issues remain unresolved and require strong interdisciplinary efforts to address them. This paper provides an overview of smart tactile sensing systems, with a focus on signal processing technologies used to interpret the measured information from tactile sensors and/or sensors for other sensory modalities. The tactile sensing transduction and principles, fabrication and structures are also discussed with their merits and demerits. Finally, the challenges that tactile sensing technology needs to overcome are highlighted.

Spatial anomaly detection in sensor networks using neighborhood information

NARCIS (Netherlands)

Bosman, H.H.W.J.; Iacca, G.; Tejada, A.; Wörtche, H.J.; Liotta, A.

2016-01-01

The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capabil- ity, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challenge now is to extract meaningful information from

Spatial anomaly detection in sensor networks using neighborhood information

NARCIS (Netherlands)

Bosman, H.H.W.J.; Iacca, G.; Tejada, A.; Wörtche, H.J.; Liotta, A.

The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capability, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challenge now is to extract meaningful information from

Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

Science.gov (United States)

Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

2015-12-01

The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

The conceptual design of the sensing system for patrolling and inspecting a nuclear facility by the intelligent robot

International Nuclear Information System (INIS)

Ebihara, Ken-ichi

1993-11-01

Supposing that an intelligent robot, instead of a human worker, patrols and inspects nuclear facilities, it is indispensable for such robot to be capable of moving with avoiding obstacles and recognizing various abnormal conditions, carrying out some ordered works based on information from sensors mounted on the robot. The present robots being practically used in nuclear facilities, however, have the limited capability such as identifying a few specific abnormal conditions using data detected by specific sensors on them. Hence, a conceptual design of a sensor-fusion-based system, which is named 'sensing system', has been performed to collect various kinds of information required for patrol and inspection. This sensing system combines a visual sensor, which consists of a monocular camera and a range finder by the active stereopsis method, an olfactory, acoustic and dose sensors. This report describes the hardware configuration and the software function for processing sensed data. An idea of sensor fusion and the preliminary consideration in respect of applying the neural network to image data processing are also described. (author)

A Wireless Sensor Network for Growth Environment Measurement and Multi-Band Optical Sensing to Diagnose Tree Vigor.

Science.gov (United States)

Kameoka, Shinichi; Isoda, Shuhei; Hashimoto, Atsushi; Ito, Ryoei; Miyamoto, Satoru; Wada, Genki; Watanabe, Naoki; Yamakami, Takashi; Suzuki, Ken; Kameoka, Takaharu

2017-04-27

We have tried to develop the guidance system for farmers to cultivate using various phenological indices. As the sensing part of this system, we deployed a new Wireless Sensor Network (WSN). This system uses the 920 MHz radio wave based on the Wireless Smart Utility Network that enables long-range wireless communication. In addition, the data acquired by the WSN were standardized for the advanced web service interoperability. By using these standardized data, we can create a web service that offers various kinds of phenological indices as secondary information to the farmers in the field. We have also established the field management system using thermal image, fluorescent and X-ray fluorescent methods, which enable the nondestructive, chemical-free, simple, and rapid measurement of fruits or trees. We can get the information about the transpiration of plants through a thermal image. The fluorescence sensor gives us information, such as nitrate balance index (NBI), that shows the nitrate balance inside the leaf, chlorophyll content, flavonol content and anthocyanin content. These methods allow one to quickly check the health of trees and find ways to improve the tree vigor of weak ones. Furthermore, the fluorescent x-ray sensor has the possibility to quantify the loss of minerals necessary for fruit growth.

A Wireless Sensor Network for Growth Environment Measurement and Multi-Band Optical Sensing to Diagnose Tree Vigor

Directory of Open Access Journals (Sweden)

Shinichi Kameoka

2017-04-01

Full Text Available We have tried to develop the guidance system for farmers to cultivate using various phenological indices. As the sensing part of this system, we deployed a new Wireless Sensor Network (WSN. This system uses the 920 MHz radio wave based on the Wireless Smart Utility Network that enables long-range wireless communication. In addition, the data acquired by the WSN were standardized for the advanced web service interoperability. By using these standardized data, we can create a web service that offers various kinds of phenological indices as secondary information to the farmers in the field. We have also established the field management system using thermal image, fluorescent and X-ray fluorescent methods, which enable the nondestructive, chemical-free, simple, and rapid measurement of fruits or trees. We can get the information about the transpiration of plants through a thermal image. The fluorescence sensor gives us information, such as nitrate balance index (NBI, that shows the nitrate balance inside the leaf, chlorophyll content, flavonol content and anthocyanin content. These methods allow one to quickly check the health of trees and find ways to improve the tree vigor of weak ones. Furthermore, the fluorescent x-ray sensor has the possibility to quantify the loss of minerals necessary for fruit growth.

A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks.

Science.gov (United States)

Liu, Xin

2015-10-30

In a cognitive sensor network (CSN), the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs) becomes very large. In this paper, a novel wireless power transfer (WPT)-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF) energy of the primary node (PN) to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks

Directory of Open Access Journals (Sweden)

Xin Liu

2015-10-01

Full Text Available In a cognitive sensor network (CSN, the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs becomes very large. In this paper, a novel wireless power transfer (WPT-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF energy of the primary node (PN to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

Learning Low Dimensional Convolutional Neural Networks for High-Resolution Remote Sensing Image Retrieval

Directory of Open Access Journals (Sweden)

Weixun Zhou

2017-05-01

Full Text Available Learning powerful feature representations for image retrieval has always been a challenging task in the field of remote sensing. Traditional methods focus on extracting low-level hand-crafted features which are not only time-consuming but also tend to achieve unsatisfactory performance due to the complexity of remote sensing images. In this paper, we investigate how to extract deep feature representations based on convolutional neural networks (CNNs for high-resolution remote sensing image retrieval (HRRSIR. To this end, several effective schemes are proposed to generate powerful feature representations for HRRSIR. In the first scheme, a CNN pre-trained on a different problem is treated as a feature extractor since there are no sufficiently-sized remote sensing datasets to train a CNN from scratch. In the second scheme, we investigate learning features that are specific to our problem by first fine-tuning the pre-trained CNN on a remote sensing dataset and then proposing a novel CNN architecture based on convolutional layers and a three-layer perceptron. The novel CNN has fewer parameters than the pre-trained and fine-tuned CNNs and can learn low dimensional features from limited labelled images. The schemes are evaluated on several challenging, publicly available datasets. The results indicate that the proposed schemes, particularly the novel CNN, achieve state-of-the-art performance.

Meteorological, environmental remote sensing and neural network analysis of the epidemiology of malaria transmission in Thailand

Directory of Open Access Journals (Sweden)

Richard Kiang

2006-11-01

Full Text Available In many malarious regions malaria transmission roughly coincides with rainy seasons, which provide for more abundant larval habitats. In addition to precipitation, other meteorological and environmental factors may also influence malaria transmission. These factors can be remotely sensed using earth observing environmental satellites and estimated with seasonal climate forecasts. The use of remote sensing usage as an early warning tool for malaria epidemics have been broadly studied in recent years, especially for Africa, where the majority of the world’s malaria occurs. Although the Greater Mekong Subregion (GMS, which includes Thailand and the surrounding countries, is an epicenter of multidrug resistant falciparum malaria, the meteorological and environmental factors affecting malaria transmissions in the GMS have not been examined in detail. In this study, the parasitological data used consisted of the monthly malaria epidemiology data at the provincial level compiled by the Thai Ministry of Public Health. Precipitation, temperature, relative humidity, and vegetation index obtained from both climate time series and satellite measurements were used as independent variables to model malaria. We used neural network methods, an artificial-intelligence technique, to model the dependency of malaria transmission on these variables. The average training accuracy of the neural network analysis for three provinces (Kanchanaburi, Mae Hong Son, and Tak which are among the provinces most endemic for malaria, is 72.8% and the average testing accuracy is 62.9% based on the 1994-1999 data. A more complex neural network architecture resulted in higher training accuracy but also lower testing accuracy. Taking into account of the uncertainty regarding reported malaria cases, we divided the malaria cases into bands (classes to compute training accuracy. Using the same neural network architecture on the 19 most endemic provinces for years 1994 to 2000, the

Temporal compressive sensing systems

Science.gov (United States)

Reed, Bryan W.

2017-12-12

Methods and systems for temporal compressive sensing are disclosed, where within each of one or more sensor array data acquisition periods, one or more sensor array measurement datasets comprising distinct linear combinations of time slice data are acquired, and where mathematical reconstruction allows for calculation of accurate representations of the individual time slice datasets.

Networked gamma radiation detection system for tactical deployment

Science.gov (United States)

Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ronald; Smith, Ethan; Guss, Paul; Mitchell, Stephen

2015-08-01

A networked gamma radiation detection system with directional sensitivity and energy spectral data acquisition capability is being developed by the National Security Technologies, LLC, Remote Sensing Laboratory to support the close and intense tactical engagement of law enforcement who carry out counterterrorism missions. In the proposed design, three clusters of 2″ × 4″ × 16″ sodium iodide crystals (4 each) with digiBASE-E (for list mode data collection) would be placed on the passenger side of a minivan. To enhance localization and facilitate rapid identification of isotopes, advanced smart real-time localization and radioisotope identification algorithms like WAVRAD (wavelet-assisted variance reduction for anomaly detection) and NSCRAD (nuisance-rejection spectral comparison ratio anomaly detection) will be incorporated. We will test a collection of algorithms and analysis that centers on the problem of radiation detection with a distributed sensor network. We will study the basic characteristics of a radiation sensor network and focus on the trade-offs between false positive alarm rates, true positive alarm rates, and time to detect multiple radiation sources in a large area. Empirical and simulation analyses of critical system parameters, such as number of sensors, sensor placement, and sensor response functions, will be examined. This networked system will provide an integrated radiation detection architecture and framework with (i) a large nationally recognized search database equivalent that would help generate a common operational picture in a major radiological crisis; (ii) a robust reach back connectivity for search data to be evaluated by home teams; and, finally, (iii) a possibility of integrating search data from multi-agency responders.

Vehicular Visible Light Networks for Urban Mobile Crowd Sensing

Directory of Open Access Journals (Sweden)

Barbara M. Masini

2018-04-01

Full Text Available Crowd sensing is a powerful tool to map and predict interests and events. In the future, it could be boosted by an increasing number of connected vehicles sharing information and intentions. This will be made available by on board wireless connected devices able to continuously communicate with other vehicles and with the environment. Among the enabling technologies, visible light communication (VLC represents a low cost solution in the short term. In spite of the fact that vehicular communications cannot rely on the sole VLC due to the limitation provided by the light which allows communications in visibility only, VLC can however be considered to complement other wireless communication technologies which could be overloaded in dense scenarios. In this paper we evaluate the performance of VLC connected vehicles when urban crowd sensing is addressed and we compare the performance of sole vehicular visible light networks with that of VLC as a complementary technology of IEEE 802.11p. Results, obtained through a realistic simulation tool taking into account both the roadmap constraints and the technologies protocols, help to understand when VLC provides the major improvement in terms of delivered data varying the number and position of RSUs and the FOV of the receiver.

Vehicular Visible Light Networks for Urban Mobile Crowd Sensing.

Science.gov (United States)

Masini, Barbara M; Bazzi, Alessandro; Zanella, Alberto

2018-04-12

Crowd sensing is a powerful tool to map and predict interests and events. In the future, it could be boosted by an increasing number of connected vehicles sharing information and intentions. This will be made available by on board wireless connected devices able to continuously communicate with other vehicles and with the environment. Among the enabling technologies, visible light communication (VLC) represents a low cost solution in the short term. In spite of the fact that vehicular communications cannot rely on the sole VLC due to the limitation provided by the light which allows communications in visibility only, VLC can however be considered to complement other wireless communication technologies which could be overloaded in dense scenarios. In this paper we evaluate the performance of VLC connected vehicles when urban crowd sensing is addressed and we compare the performance of sole vehicular visible light networks with that of VLC as a complementary technology of IEEE 802.11p. Results, obtained through a realistic simulation tool taking into account both the roadmap constraints and the technologies protocols, help to understand when VLC provides the major improvement in terms of delivered data varying the number and position of RSUs and the FOV of the receiver.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks

Science.gov (United States)

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-01-01

Simple Summary The understanding of the spatio-temporal distribution of the species habitats would facilitate wildlife resource management and conservation efforts. Existing methods have poor performance due to the limited availability of training samples. More recently, location-aware sensors have been widely used to track animal movements. The aim of the study was to generate suitability maps of bar-head geese using movement data coupled with environmental parameters, such as remote sensing images and temperature data. Therefore, we modified a deep convolutional neural network for the multi-scale inputs. The results indicate that the proposed method can identify the areas with the dense goose species around Qinghai Lake. In addition, this approach might also be interesting for implementation in other species with different niche factors or in areas where biological survey data are scarce. Abstract With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results

Multi-source remote sensing data management system

International Nuclear Information System (INIS)

Qin Kai; Zhao Yingjun; Lu Donghua; Zhang Donghui; Wu Wenhuan

2014-01-01

In this thesis, the author explored multi-source management problems of remote sensing data. The main idea is to use the mosaic dataset model, and the ways of an integreted display of image and its interpretation. Based on ArcGIS and IMINT feature knowledge platform, the author used the C# and other programming tools for development work, so as to design and implement multi-source remote sensing data management system function module which is able to simply, conveniently and efficiently manage multi-source remote sensing data. (authors)

ATRAN Terrain Sensing Guidance-The Grand-Daddy System

Science.gov (United States)

Koch, Richard F.; Evans, Donald C.

1980-12-01

ATRAN was the pioneer terrain sensing guidance system developed in the 1950 era and deployed in Europe on the Air Force's mobile, ground launched TM-76A MACE cruise missile in the late 1950's and early 1960's. The background, principles and technology are described for this system which was the forerunner of todays modern autonomous standoff terrain sensing guided weapons.

Network SCADA System

International Nuclear Information System (INIS)

Milivojevic, Dragan R.; Tasic, Visa; Karabasevic, Dejan

2003-01-01

Copper Institute, Industrial Informatics department, is developing and applying network real time process monitoring and control systems. Some of these systems are already in use. The paper presents some hardware and software general remarks and performances, with special regard to communication sub-systems and network possibilities. (Author)

Information theory and signal transduction systems: from molecular information processing to network inference.

Science.gov (United States)

Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

2014-11-01

Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

A software architecture for adaptive modular sensing systems.

Science.gov (United States)

Lyle, Andrew C; Naish, Michael D

2010-01-01

By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration.

Monitoring of Thermal Protection Systems and MMOD using Robust Self-Organizing Optical Fiber Sensing Networks

Science.gov (United States)

Richards, Lance

2014-01-01

The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, such as those from Micrometeoroid Orbital Debris (MMOD). The approach uses an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during reentry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry.

Day-to-day evolution of the traffic network with Advanced Traveler Information System

International Nuclear Information System (INIS)

Han Linghui; Sun Huijun; Wu Jianjun; Zhu Chengjuan

2011-01-01

Highlights: → We develop a dynamical system with Advanced Travelers Information System (ATIS). → We use the dynamical system to study stability of the traffic network with ATIS. → It is found that some periodic attractors appear in some cases. → A road pricing is implemented to alleviate the instability of the traffic network with ATIS. - Abstract: Since the notion of user equilibrium (UE) was proposed by Wardrop , it has become a cornerstone for traffic assignment analysis. But, it is not sufficient to only ask whether equilibrium exists or not; it is equally important to ask whether and how the system can achieve equilibrium. Meanwhile, stability is an important performance in the sense that if equilibrium is unsustainable, both the equilibrium and the trajectory are sensitive to disturbances, even a small perturbation will result in the system evolution away from the equilibrium point. These incentive a growing interest in day-to-day dynamics. In this paper, we develop a dynamical system with Advanced Traveler Information System (ATIS) and study the stability of the network with ATIS. A simple network is used to simulate the model, and the results show that there exist periodic attractors in the traffic network in some cases (for example, the market penetration level of ATIS is 0.25 and traffic demand is 2 unit). It is found that the logit parameter of the dynamical model and the traffic demand can also affect the stability of the traffic network. More periodic attractors appear in the system when the traffic demand is large and the low logit parameter can delay the appearance of periodic attractors. By simulation, it can be concluded that if the range of the periodic attractors' domain of the simple network is known, the road pricing based on the range of the attraction domain is effective to alleviate the instability of the system.

Computer network defense system

Science.gov (United States)

Urias, Vincent; Stout, William M. S.; Loverro, Caleb

2017-08-22

A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves network connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.

Soil Moisture Retrieval Using Convolutional Neural Networks: Application to Passive Microwave Remote Sensing

Science.gov (United States)

Hu, Z.; Xu, L.; Yu, B.

2018-04-01

A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.

SOIL MOISTURE RETRIEVAL USING CONVOLUTIONAL NEURAL NETWORKS: APPLICATION TO PASSIVE MICROWAVE REMOTE SENSING

Directory of Open Access Journals (Sweden)

Z. Hu

2018-04-01

Full Text Available A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN. Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR for soil moisture retrieval.

Remote sensing observing systems of the Meteorological Service of Catalonia (SMC): application to thunderstorm surveillance

Science.gov (United States)

Argemí, O.; Bech, J.; Pineda, N.; Rigo, T.

2009-09-01

Remote sensing observing systems of the Meteorological Service of Catalonia (SMC) have been upgraded during the last years with newer technologies and enhancements. Recent changes on the weather radar network have been motivated to improve precipitation estimates by radar as well as meteorological surveillance in the area of Catalonia. This region has approximately 32,000 square kilometres and is located in the NE of Spain, limited by the Pyrenees to the North (with mountains exceeding 3000 m) and by the Mediterranean Sea to the East and South. In the case of the total lightning (intra-cloud and cloud-to-ground lightning) detection system, the current upgrades will assure a better lightning detection efficiency and location accuracy. Both upgraded systems help to enhance the tracking and the study of thunderstorm events. Initially, the weather radar network was designed to cover the complex topography of Catalonia and surrounding areas to support the regional administration, which includes civil protection and water authorities. The weather radar network was upgraded in 2008 with the addition of a new C-band Doppler radar system, which is located in the top of La Miranda Mountain (Tivissa) in the southern part of Catalonia enhancing the coverage, particularly to the South and South-West. Technically the new radar is very similar to the last one installed in 2003 (Creu del Vent radar), using a 4 m antenna (i.e., 1 degree beam width), a Vaisala-Sigmet RVP-8 digital receiver and processor and a low power transmitter using a Travelling Wave Tube (TWT) amplifier. This design allows using pulse-compression techniques to enhance radial resolution and sensitivity. Currently, the SMC is upgrading its total lightning detection system, operational since 2003. While a fourth sensor (Amposta) was added last year to enlarge the system coverage, all sensors and central processor will be upgraded this year to the new Vaisala’s total lightning location technology. The new LS8000

Time Synchronized Wireless Sensor Network for Vibration Measurement

Science.gov (United States)

Uchimura, Yutaka; Nasu, Tadashi; Takahashi, Motoichi

Network based wireless sensing has become an important area of research and various new applications for remote sensing are expected to emerge. One of the promising applications is structural health monitoring of building or civil engineering structure and it often requires vibration measurement. For the vibration measurement via wireless network, time synchronization is indispensable. In this paper, we introduce a newly developed time synchronized wireless sensor network system. The system employs IEEE 802.11 standard based TSF counter and sends the measured data with the counter value. TSF based synchronization enables consistency on common clock among different wireless nodes. We consider the scale effect on the synchronization accuracy and the effect is evaluated by stochastic analysis and simulation studies. A new wireless sensing system is developed and the hardware and software specifications are shown. The experiments are conducted in a reinforced concrete building and results show good performance enough for vibration measurement purpose.

A Software Architecture for Adaptive Modular Sensing Systems

Directory of Open Access Journals (Sweden)

Andrew C. Lyle

2010-08-01

Full Text Available By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration.

Facile Preparation of Carbon-Nanotube-based 3-Dimensional Transparent Conducting Networks for Flexible Noncontact Sensing Device

KAUST Repository

Tai, Yanlong

2016-04-12

Here, we report the controllable fabrication of transparent conductive films (TCFs) for moisture-sensing applications based on heating-rate-triggered, 3-dimensional porous conducting networks of single-walled carbon nanotube (SWCNT)/poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS). How baking conditions influence the self-assembled microstructure of the TCFs is discussed. The sensor presents high-performance properties, including a reasonable sheet resistance (2.1 kohm/sq), a high visible-range transmittance (> 69 %, PET = 90 %), and good stability when subjected to cyclic loading (> 1000 cycles, better than indium tin oxide film) during processing. Moreover, the benefits of these kinds of TCFs were verified through a fully transparent, highly sensitive, rapid response, noncontact moisture-sensing device (5×5 sensing pixels).

A Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

Science.gov (United States)

Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

2018-01-01

Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks.

Science.gov (United States)

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-04-26

With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction.

Intelligent Wireless Sensor Networks for System Health Monitoring

Science.gov (United States)

Alena, Rick

2011-01-01

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of

A Collaborative Approach for Monitoring Nodes Behavior during Spectrum Sensing to Mitigate Multiple Attacks in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Mahmoud Khasawneh

2017-01-01

Full Text Available Spectrum sensing is the first step to overcome the spectrum scarcity problem in Cognitive Radio Networks (CRNs wherein all unutilized subbands in the radio environment are explored for better spectrum utilization. Adversary nodes can threaten these spectrum sensing results by launching passive and active attacks that prevent legitimate nodes from using the spectrum efficiently. Securing the spectrum sensing process has become an important issue in CRNs in order to ensure reliable and secure spectrum sensing and fair management of resources. In this paper, a novel collaborative approach during spectrum sensing process is proposed. It monitors the behavior of sensing nodes and identifies the malicious and misbehaving sensing nodes. The proposed approach measures the node’s sensing reliability using a value called belief level. All the sensing nodes are grouped into a specific number of clusters. In each cluster, a sensing node is selected as a cluster head that is responsible for collecting sensing-reputation reports from different cognitive nodes about each node in the same cluster. The cluster head analyzes information to monitor and judge the nodes’ behavior. By simulating the proposed approach, we showed its importance and its efficiency for achieving better spectrum security by mitigating multiple passive and active attacks.

Food Security, Decision Making and the Use of Remote Sensing in Famine Early Warning Systems

Science.gov (United States)

Brown, Molly E.

2008-01-01

Famine early warning systems use remote sensing in combination with socio-economic and household food economy analysis to provide timely and rigorous information on emerging food security crises. The Famine Early Warning Systems Network (FEWS NET) is the US Agency for International Development's decision support system in 20 African countries, as well as in Guatemala, Haiti and Afghanistan. FEWS NET provides early and actionable policy guidance for the US Government and its humanitarian aid partners. As we move into an era of climate change where weather hazards will become more frequent and severe, understanding how to provide quantitative and actionable scientific information for policy makers using biophysical data is critical for an appropriate and effective response.

Remotely Piloted Aircraft Systems and a Wireless Sensors Network for Radiological Accidents

Directory of Open Access Journals (Sweden)

A. Reyes-Muñoz

2016-01-01

Full Text Available In critical radiological situations, the real time information that we could get from the disaster area becomes of great importance. However, communication systems could be affected after a radiological accident. The proposed network in this research consists of distributed sensors in charge of collecting radiological data and ground vehicles that are sent to the nuclear plant at the moment of the accident to sense environmental and radiological information. Afterwards, data would be analyzed in the control center. Collected data by sensors and ground vehicles would be delivered to a control center using Remotely Piloted Aircraft Systems (RPAS as a message carrier. We analyze the pairwise contacts, as well as visiting times, data collection, capacity of the links, size of the transmission window of the sensors, and so forth. All this calculus was made analytically and compared via network simulations.

Effective Data Acquisition Protocol for Multi-Hop Heterogeneous Wireless Sensor Networks Using Compressive Sensing

Directory of Open Access Journals (Sweden)

Ahmed M. Khedr

2015-10-01

Full Text Available In designing wireless sensor networks (WSNs, it is important to reduce energy dissipation and prolong network lifetime. Clustering of nodes is one of the most effective approaches for conserving energy in WSNs. Cluster formation protocols generally consider the heterogeneity of sensor nodes in terms of energy difference of nodes but ignore the different transmission ranges of them. In this paper, we propose an effective data acquisition clustered protocol using compressive sensing (EDACP-CS for heterogeneous WSNs that aims to conserve the energy of sensor nodes in the presence of energy and transmission range heterogeneity. In EDACP-CS, cluster heads are selected based on the distance from the base station and sensor residual energy. Simulation results show that our protocol offers a much better performance than the existing protocols in terms of energy consumption, stability, network lifetime, and throughput.

Neuronal regulation of homeostasis by nutrient sensing.

Science.gov (United States)

Lam, Tony K T

2010-04-01

In type 2 diabetes and obesity, the homeostatic control of glucose and energy balance is impaired, leading to hyperglycemia and hyperphagia. Recent studies indicate that nutrient-sensing mechanisms in the body activate negative-feedback systems to regulate energy and glucose homeostasis through a neuronal network. Direct metabolic signaling within the intestine activates gut-brain and gut-brain-liver axes to regulate energy and glucose homeostasis, respectively. In parallel, direct metabolism of nutrients within the hypothalamus regulates food intake and blood glucose levels. These findings highlight the importance of the central nervous system in mediating the ability of nutrient sensing to maintain homeostasis. Futhermore, they provide a physiological and neuronal framework by which enhancing or restoring nutrient sensing in the intestine and the brain could normalize energy and glucose homeostasis in diabetes and obesity.

Indoor Positioning System Using Depth Maps and Wireless Networks

Directory of Open Access Journals (Sweden)

Jaime Duque Domingo

2016-01-01

Full Text Available This work presents a new Indoor Positioning System (IPS based on the combination of WiFi Positioning System (WPS and depth maps, for estimating the location of people. The combination of both technologies improves the efficiency of existing methods, based uniquely on wireless positioning techniques. While other positioning systems force users to wear special devices, the system proposed in this paper just requires the use of smartphones, besides the installation of RGB-D sensors in the sensing area. Furthermore, the system is not intrusive, being not necessary to know people’s identity. The paper exposes the method developed for putting together and exploiting both types of sensory information with positioning purposes: the measurements of the level of the signal received from different access points (APs of the wireless network and the depth maps provided by the RGB-D cameras. The obtained results show a significant improvement in terms of positioning with respect to common WiFi-based systems.

The APS control system network

International Nuclear Information System (INIS)

Sidorowicz, K.V.; McDowell, W.P.

1995-01-01

The APS accelerator control system is a distributed system consisting of operator interfaces, a network, and computer-controlled interfaces to hardware. This implementation of a control system has come to be called the open-quotes Standard Model.close quotes The operator interface is a UNDC-based workstation with an X-windows graphical user interface. The workstation may be located at any point on the facility network and maintain full functionality. The function of the network is to provide a generalized communication path between the host computers, operator workstations, input/output crates, and other hardware that comprise the control system. The crate or input/output controller (IOC) provides direct control and input/output interfaces for each accelerator subsystem. The network is an integral part of all modem control systems and network performance will determine many characteristics of a control system. This paper will describe the overall APS network and examine the APS control system network in detail. Metrics are provided on the performance of the system under various conditions

Liquid Level Sensing System

Science.gov (United States)

Korman, Valentin (Inventor); Wiley, John T. (Inventor); Duffell, Amanda G. (Inventor)

2014-01-01

A liquid level sensing system includes waveguides disposed in a liquid and distributed along a path with a gap between adjacent waveguides. A source introduces electromagnetic energy into the waveguides at a first end of the path. A portion of the electromagnetic energy exits the waveguides at a second end of the path. A detector measures the portion of the electromagnetic energy exiting the second end of the path.

Promoting Social Network Awareness: A Social Network Monitoring System

Science.gov (United States)

Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

2010-01-01

To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

Triangulation positioning system network

Directory of Open Access Journals (Sweden)

Sfendourakis Marios

2017-01-01

Full Text Available This paper presents ongoing work on localization and positioning through triangulation procedure for a Fixed Sensors Network - FSN.The FSN has to work as a system.As the triangulation problem becomes high complicated in a case with large numbers of sensors and transmitters, an adequate grid topology is needed in order to tackle the detection complexity.For that reason a Network grid topology is presented and areas that are problematic and need further analysis are analyzed.The Network System in order to deal with problems of saturation and False Triangulations - FTRNs will have to find adequate methods in every sub-area of the Area Of Interest - AOI.Also, concepts like Sensor blindness and overall Network blindness, are presented. All these concepts affect the Network detection rate and its performance and ought to be considered in a way that the network overall performance won’t be degraded.Network performance should be monitored contentiously, with right algorithms and methods.It is also shown that as the number of TRNs and FTRNs is increased Detection Complexity - DC is increased.It is hoped that with further research all the characteristics of a triangulation system network for positioning will be gained and the system will be able to perform autonomously with a high detection rate.

A Ground Systems Template for Remote Sensing Systems

Science.gov (United States)

McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.

2002-10-01

Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS.

A ground systems template for remote sensing systems

International Nuclear Information System (INIS)

McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.

2002-01-01

Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS

Remote shock sensing and notification system

Science.gov (United States)

Muralidharan, Govindarajan; Britton, Charles L.; Pearce, James; Jagadish, Usha; Sikka, Vinod K.

2008-11-11

A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interference circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitting with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

Teleradiology system analysis using a discrete event-driven block-oriented network simulator

Science.gov (United States)

Stewart, Brent K.; Dwyer, Samuel J., III

1992-07-01

Performance evaluation and trade-off analysis are the central issues in the design of communication networks. Simulation plays an important role in computer-aided design and analysis of communication networks and related systems, allowing testing of numerous architectural configurations and fault scenarios. We are using the Block Oriented Network Simulator (BONeS, Comdisco, Foster City, CA) software package to perform discrete, event- driven Monte Carlo simulations in capacity planning, tradeoff analysis and evaluation of alternate architectures for a high-speed, high-resolution teleradiology project. A queuing network model of the teleradiology system has been devise, simulations executed and results analyzed. The wide area network link uses a switched, dial-up N X 56 kbps inverting multiplexer where the number of digital voice-grade lines (N) can vary from one (DS-0) through 24 (DS-1). The proposed goal of such a system is 200 films (2048 X 2048 X 12-bit) transferred between a remote and local site in an eight hour period with a mean delay time less than five minutes. It is found that: (1) the DS-1 service limit is around 100 films per eight hour period with a mean delay time of 412 +/- 39 seconds, short of the goal stipulated above; (2) compressed video teleconferencing can be run simultaneously with image data transfer over the DS-1 wide area network link without impacting the performance of the described teleradiology system; (3) there is little sense in upgrading to a higher bandwidth WAN link like DS-2 or DS-3 for the current system; and (4) the goal of transmitting 200 films in an eight hour period with a mean delay time less than five minutes can be achieved simply if the laser printer interface is updated from the current DR-11W interface to a much faster SCSI interface.

Making sense of polarities in health organizations for policy and leadership.

Science.gov (United States)

Martin, Carmel M

2010-10-01

Making sense of complex adaptive clinical practice and health systems is a pressing challenge as health services continue to struggle to adapt to changing internal and external constraints. In this Forum, we begin with Dervin's Sense-Making theories and research in communications. This provides a conceptual and theoretical context for this editions research on comparative complexity of family medicine consultations in the USA, models for adaptive leadership in clinical care and social networking to make sense of health promotion challenges for young people. Finally, a Sense-Making schema is proposed. © 2010 Blackwell Publishing Ltd.

Improving Spectral Capacity and Wireless Network Coverage by Cognitive Radio Technology and Relay Nodes in Cellular Systems

DEFF Research Database (Denmark)

Frederiksen, Flemming Bjerge

2008-01-01

Methods to enhance the use of the frequency spectrum by automatical spectrum sensing plus spectrum sharing in a cognitive radio technology context have been presented and discussed in this paper. Ideas to improve the wireless transmission by orthogonal OFDM-based communication and to increase the...... the coverage of cellular systems by future wireless networks, relay channels, relay stations and collaborate radio have been presented as well. A revised hierarchical deployment of the future wireless and wired networks are shortly discussed....

Economic and environmental assessment of rooftops regarding suitability for photovoltaic systems installation based on remote sensing data

International Nuclear Information System (INIS)

Lukač, Niko; Seme, Sebastijan; Dežan, Katarina; Žalik, Borut; Štumberger, Gorazd

2016-01-01

Within the last few years, the increase of the world's energy consumption has substantially impacted the environment. Solar energy initiative is more than ever involved to tackle this issue, especially when deploying PV (photovoltaic) systems over large-scale residential areas. However, not all surfaces in these areas are economically suitable, while some surfaces have low CO_2 mitigation. With the availability of high-resolution remote sensing data, the estimation of suitable rooftops for PV systems installation can be performed automatically by estimating the PV potential. This paper presents a novel method for estimating NPV (net present value) of the potential PV systems installed on rooftops by using LiDAR (Light Detection And Ranging) data and PV systems' nonlinear efficiency characteristics. More importantly, the environmental impact is estimated for each rooftop through EPBT (energy payback time) and GGER (greenhouse gas emission rate), based on the life-cycle of a specific PV system. This is combined with NPV in order to find rooftops that are both economically and environmentally viable candidates for PV systems deployment. Results demonstrate a case study LiDAR data for predicting each building's economical and environmental impact, as well as providing an overall view of resulting cumulative CO_2 mitigation over large residential area. - Highlights: • The method relies on PV potential estimation over LiDAR remote sensing data. • Novel economic assessment of PV systems using remote sensing data is proposed. • Environmental analysis of PV systems based on EPBT and GGER is performed. • Estimation of CO_2 mitigation over LiDAR data by considering national energy network.

A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks

Science.gov (United States)

Shahzad, Aamir; Lee, Malrey; Xiong, Neal Naixue; Jeong, Gisung; Lee, Young-Keun; Choi, Jae-Young; Mahesar, Abdul Wheed; Ahmad, Iftikhar

2016-01-01

In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interconnection (OSI) model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB) is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design. PMID:26950129

A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks.

Science.gov (United States)

Shahzad, Aamir; Lee, Malrey; Xiong, Neal Naixue; Jeong, Gisung; Lee, Young-Keun; Choi, Jae-Young; Mahesar, Abdul Wheed; Ahmad, Iftikhar

2016-03-03

In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interconnection (OSI) model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB) is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design.

A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks

Directory of Open Access Journals (Sweden)

Aamir Shahzad

2016-03-01

Full Text Available In Industrial systems, Supervisory control and data acquisition (SCADA system, the pseudo-transport layer of the distributed network protocol (DNP3 performs the functions of the transport layer and network layer of the open systems interconnection (OSI model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design.

Remote Sensing Wind and Wind Shear System.

Science.gov (United States)

Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.

Statistical physics of networks, information and complex systems

Energy Technology Data Exchange (ETDEWEB)

Ecke, Robert E [Los Alamos National Laboratory

2009-01-01

In this project we explore the mathematical methods and concepts of statistical physics that are fmding abundant applications across the scientific and technological spectrum from soft condensed matter systems and bio-infonnatics to economic and social systems. Our approach exploits the considerable similarity of concepts between statistical physics and computer science, allowing for a powerful multi-disciplinary approach that draws its strength from cross-fertilization and mUltiple interactions of researchers with different backgrounds. The work on this project takes advantage of the newly appreciated connection between computer science and statistics and addresses important problems in data storage, decoding, optimization, the infonnation processing properties of the brain, the interface between quantum and classical infonnation science, the verification of large software programs, modeling of complex systems including disease epidemiology, resource distribution issues, and the nature of highly fluctuating complex systems. Common themes that the project has been emphasizing are (i) neural computation, (ii) network theory and its applications, and (iii) a statistical physics approach to infonnation theory. The project's efforts focus on the general problem of optimization and variational techniques, algorithm development and infonnation theoretic approaches to quantum systems. These efforts are responsible for fruitful collaborations and the nucleation of science efforts that span multiple divisions such as EES, CCS, 0 , T, ISR and P. This project supports the DOE mission in Energy Security and Nuclear Non-Proliferation by developing novel infonnation science tools for communication, sensing, and interacting complex networks such as the internet or energy distribution system. The work also supports programs in Threat Reduction and Homeland Security.

CYBERNETIC BASIS AND SYSTEM PRACTICE OF REMOTE SENSING AND SPATIAL INFORMATION SCIENCE

Directory of Open Access Journals (Sweden)

X. Tan

2017-09-01

Full Text Available Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

Cybernetic Basis and System Practice of Remote Sensing and Spatial Information Science

Science.gov (United States)

Tan, X.; Jing, X.; Chen, R.; Ming, Z.; He, L.; Sun, Y.; Sun, X.; Yan, L.

2017-09-01

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

Addressing the Issue of Routing Unfairness in Opportunistic Backhaul Networks for Collecting Sensed Data

Directory of Open Access Journals (Sweden)

Tekenate E. Amah

2017-12-01

Full Text Available Widely deploying sensors in the environment and embedding them in physical objects is a crucial step towards realizing smart and sustainable cities. To cope with rising resource demands and limited budgets, opportunistic networks (OppNets offer a scalable backhaul option for collecting delay-tolerant data from sensors to gateways in order to enable efficient urban operations and services. While pervasive devices such as smartphones and tablets contribute significantly to the scalability of OppNets, closely following human movement patterns and social structure introduces network characteristics that pose routing challenges. Our study on the impact of these characteristics reveals that existing routing protocols subject a key set of devices to higher resource consumption, to which their users may respond by withdrawing participation. Unfortunately, existing solutions addressing this unfairness do not guarantee achievable throughput since they are not specifically designed for sensed data collection scenarios. Based on concepts derived from the study, we suggest design guidelines for adapting applicable routing protocols to sensed data collection scenarios. We also follow our design guidelines to propose the Fair Locality Aware Routing (FLARoute technique. Evaluating FLARoute within an existing routing protocol confirms improved fairness and throughput under conditions that compromise the performance of existing solutions.

Research on an uplink carrier sense multiple access algorithm of large indoor visible light communication networks based on an optical hard core point process.

Science.gov (United States)

Nan, Zhufen; Chi, Xuefen

2016-12-20

The IEEE 802.15.7 protocol suggests that it could coordinate the channel access process based on the competitive method of carrier sensing. However, the directionality of light and randomness of diffuse reflection would give rise to a serious imperfect carrier sense (ICS) problem [e.g., hidden node (HN) problem and exposed node (EN) problem], which brings great challenges in realizing the optical carrier sense multiple access (CSMA) mechanism. In this paper, the carrier sense process implemented by diffuse reflection light is modeled as the choice of independent sets. We establish an ICS model with the presence of ENs and HNs for the multi-point to multi-point visible light communication (VLC) uplink communications system. Considering the severe optical ICS problem, an optical hard core point process (OHCPP) is developed, which characterizes the optical CSMA for the indoor VLC uplink communications system. Due to the limited coverage of the transmitted optical signal, in our OHCPP, the ENs within the transmitters' carrier sense region could be retained provided that they could not corrupt the ongoing communications. Moreover, because of the directionality of both light emitting diode (LED) transmitters and receivers, theoretical analysis of the HN problem becomes difficult. In this paper, we derive the closed-form expression for approximating the outage probability and transmission capacity of VLC networks with the presence of HNs and ENs. Simulation results validate the analysis and also show the existence of an optimal physical carrier-sensing threshold that maximizes the transmission capacity for a given emission angle of LED.

Bridging the Scales from Field to Region with Practical Tools to Couple Time- and Space-Synchronized Data from Flux Towers and Networks with Proximal and Remote Sensing Data

Science.gov (United States)

Burba, G. G.; Avenson, T.; Burkart, A.; Gamon, J. A.; Guan, K.; Julitta, T.; Pastorello, G.; Sakowska, K.

2017-12-01

Many hundreds of flux towers are presently operational as standalone projects and as parts of regional networks. However, the vast majority of these towers do not allow straightforward coupling with remote sensing (drone, aircraft, satellite, etc.) data, and even fewer have optical sensors for validation of remote sensing products, and upscaling from field to regional levels. In 2016-2017, new tools to collect, process, and share time-synchronized flux data from multiple towers were developed and deployed globally. Originally designed to automate site and data management, and to streamline flux data analysis, these tools allow relatively easy matching of tower data with remote sensing data: GPS-driven PTP time protocol synchronizes instrumentation within the station, different stations with each other, and all of these to remote sensing data to precisely align remote sensing and flux data in time Footprint size and coordinates computed and stored with flux data help correctly align tower flux footprints and drone, aircraft or satellite motion to precisely align optical and flux data in space Full snapshot of the remote sensing pixel can then be constructed, including leaf-level, ground optical sensor, and flux tower measurements from the same footprint area, closely coupled with the remote sensing measurements to help interpret remote sensing data, validate models, and improve upscaling Additionally, current flux towers can be augmented with advanced ground optical sensors and can use standard routines to deliver continuous products (e.g. SIF, PRI, NDVI, etc.) based on automated field spectrometers (e.g., FloX and RoX, etc.) and other optical systems. Several dozens of new towers already operational globally can be readily used for the proposed workflow. Over 500 active traditional flux towers can be updated to synchronize their data with remote sensing measurements. This presentation will show how the new tools are used by major networks, and describe how this

Online catalog access and distribution of remotely sensed information

Science.gov (United States)

Lutton, Stephen M.

1997-09-01

Remote sensing is providing voluminous data and value added information products. Electronic sensors, communication electronics, computer software, hardware, and network communications technology have matured to the point where a distributed infrastructure for remotely sensed information is a reality. The amount of remotely sensed data and information is making distributed infrastructure almost a necessity. This infrastructure provides data collection, archiving, cataloging, browsing, processing, and viewing for applications from scientific research to economic, legal, and national security decision making. The remote sensing field is entering a new exciting stage of commercial growth and expansion into the mainstream of government and business decision making. This paper overviews this new distributed infrastructure and then focuses on describing a software system for on-line catalog access and distribution of remotely sensed information.

Automated mode shape estimation in agent-based wireless sensor networks

Science.gov (United States)

Zimmerman, Andrew T.; Lynch, Jerome P.

2010-04-01

Recent advances in wireless sensing technology have made it possible to deploy dense networks of sensing transducers within large structural systems. Because these networks leverage the embedded computing power and agent-based abilities integral to many wireless sensing devices, it is possible to analyze sensor data autonomously and in-network. In this study, market-based techniques are used to autonomously estimate mode shapes within a network of agent-based wireless sensors. Specifically, recent work in both decentralized Frequency Domain Decomposition and market-based resource allocation is leveraged to create a mode shape estimation algorithm derived from free-market principles. This algorithm allows an agent-based wireless sensor network to autonomously shift emphasis between improving mode shape accuracy and limiting the consumption of certain scarce network resources: processing time, storage capacity, and power consumption. The developed algorithm is validated by successfully estimating mode shapes using a network of wireless sensor prototypes deployed on the mezzanine balcony of Hill Auditorium, located on the University of Michigan campus.

Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems

Directory of Open Access Journals (Sweden)

Josu Etxaniz

2017-04-01

Full Text Available Even though home automation is a well-known research and development area, recent technological improvements in different areas such as context recognition, sensing, wireless communications or embedded systems have boosted wireless smart homes. This paper focuses on some of those areas related to home automation. The paper draws attention to wireless communications issues on embedded systems. Specifically, the paper discusses the multi-hop networking together with Bluetooth technology and latency, as a quality of service (QoS metric. Bluetooth is a worldwide standard that provides low power multi-hop networking. It is a radio license free technology and establishes point-to-point and point-to-multipoint links, known as piconets, or multi-hop networks, known as scatternets. This way, many Bluetooth nodes can be interconnected to deploy ambient intelligent networks. This paper introduces the research on multi-hop latency done with park and sniff low power modes of Bluetooth over the test platform developed. Besides, an empirical model is obtained to calculate the latency of Bluetooth multi-hop communications over asynchronous links when links in scatternets are always in sniff or the park mode. Smart home devices and networks designers would take advantage of the models and the estimation of the delay they provide in communications along Bluetooth multi-hop networks.

Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

Even though home automation is a well-known research and development area, recent technological improvements in different areas such as context recognition, sensing, wireless communications or embedded systems have boosted wireless smart homes. This paper focuses on some of those areas related to home automation. The paper draws attention to wireless communications issues on embedded systems. Specifically, the paper discusses the multi-hop networking together with Bluetooth technology and latency, as a quality of service (QoS) metric. Bluetooth is a worldwide standard that provides low power multi-hop networking. It is a radio license free technology and establishes point-to-point and point-to-multipoint links, known as piconets, or multi-hop networks, known as scatternets. This way, many Bluetooth nodes can be interconnected to deploy ambient intelligent networks. This paper introduces the research on multi-hop latency done with park and sniff low power modes of Bluetooth over the test platform developed. Besides, an empirical model is obtained to calculate the latency of Bluetooth multi-hop communications over asynchronous links when links in scatternets are always in sniff or the park mode. Smart home devices and networks designers would take advantage of the models and the estimation of the delay they provide in communications along Bluetooth multi-hop networks. PMID:28468294

Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems.

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-04-30

Even though home automation is a well-known research and development area, recent technological improvements in different areas such as context recognition, sensing, wireless communications or embedded systems have boosted wireless smart homes. This paper focuses on some of those areas related to home automation. The paper draws attention to wireless communications issues on embedded systems. Specifically, the paper discusses the multi-hop networking together with Bluetooth technology and latency, as a quality of service (QoS) metric. Bluetooth is a worldwide standard that provides low power multi-hop networking. It is a radio license free technology and establishes point-to-point and point-to-multipoint links, known as piconets, or multi-hop networks, known as scatternets. This way, many Bluetooth nodes can be interconnected to deploy ambient intelligent networks. This paper introduces the research on multi-hop latency done with park and sniff low power modes of Bluetooth over the test platform developed. Besides, an empirical model is obtained to calculate the latency of Bluetooth multi-hop communications over asynchronous links when links in scatternets are always in sniff or the park mode. Smart home devices and networks designers would take advantage of the models and the estimation of the delay they provide in communications along Bluetooth multi-hop networks.

Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

ZHENG Zhuo

2018-05-01

Full Text Available High resolution remote sensing imagery scene classification is important for automatic complex scene recognition, which is the key technology for military and disaster relief, etc. In this paper, we propose a novel joint multi-scale convolution neural network (JMCNN method using a limited amount of image data for high resolution remote sensing imagery scene classification. Different from traditional convolutional neural network, the proposed JMCNN is an end-to-end training model with joint enhanced high-level feature representation, which includes multi-channel feature extractor, joint multi-scale feature fusion and Softmax classifier. Multi-channel and scale convolutional extractors are used to extract scene middle features, firstly. Then, in order to achieve enhanced high-level feature representation in a limit dataset, joint multi-scale feature fusion is proposed to combine multi-channel and scale features using two feature fusions. Finally, enhanced high-level feature representation can be used for classification by Softmax. Experiments were conducted using two limit public UCM and SIRI datasets. Compared to state-of-the-art methods, the JMCNN achieved improved performance and great robustness with average accuracies of 89.3% and 88.3% on the two datasets.

Large-Scale, Multi-Temporal Remote Sensing of Palaeo-River Networks: A Case Study from Northwest India and its Implications for the Indus Civilisation

Directory of Open Access Journals (Sweden)

Hector A. Orengo

2017-07-01

Full Text Available Remote sensing has considerable potential to contribute to the identification and reconstruction of lost hydrological systems and networks. Remote sensing-based reconstructions of palaeo-river networks have commonly employed single or limited time-span imagery, which limits their capacity to identify features in complex and varied landscape contexts. This paper presents a seasonal multi-temporal approach to the detection of palaeo-rivers over large areas based on long-term vegetation dynamics and spectral decomposition techniques. Twenty-eight years of Landsat 5 data, a total of 1711 multi-spectral images, have been bulk processed using Google Earth Engine© Code Editor and cloud computing infrastructure. The use of multi-temporal data has allowed us to overcome seasonal cultivation patterns and long-term visibility issues related to recent crop selection, extensive irrigation and land-use patterns. The application of this approach on the Sutlej-Yamuna interfluve (northwest India, a core area for the Bronze Age Indus Civilisation, has enabled the reconstruction of an unsuspectedly complex palaeo-river network comprising more than 8000 km of palaeo-channels. It has also enabled the definition of the morphology of these relict courses, which provides insights into the environmental conditions in which they operated. These new data will contribute to a better understanding of the settlement distribution and environmental settings in which this, often considered riverine, civilisation operated.

Silver nanoparticles embedded in amine-functionalized silicate sol–gel network assembly for sensing cysteine, adenosine and NADH

International Nuclear Information System (INIS)

Maduraiveeran, Govindhan; Ramaraj, Ramasamy

2011-01-01

Silver nanoparticles embedded in amine-functionalized silicate sol–gel network were synthesized and used for sensing biomolecules such as cysteine, adenosine, and β-nicotinamide adenine dinucleotide (NADH). The sensing of these biomolecules by the assembly of silver nanoparticles was triggered by the optical response of the surface plasmon resonance (SPR) of the silver nanoparticles. The optical sensor exhibited the lowest detection limit (LOD) of 5, 20, and 5 μM for cysteine, adenosine, and NADH, respectively. The sensing of biomolecules in the micromolar range by using the amine-functionalized silicate sol–gel embedded silver nanoparticles was studied in the presence of interference molecules like uridine, glycine, guanine, and guanosine. Thus, the present approach might open up a new avenue for the development of silver nanoparticles-based optical sensor devices for biomolecules.

Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

Science.gov (United States)

Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian

2017-04-01

Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

Wireless sensing on surface hydrocarbon production systems

International Nuclear Information System (INIS)

Kane, D; McStay, D; Mulholland, J; Costello, L

2009-01-01

The use of wireless sensor networks for monitoring and optimising the performance of surface hydrocarbon production systems is reported. Wireless sensor networks are shown to be able to produce comprehensively instrumented XTs and other equipment that generate the data required by Intelligent Oilfield systems. The information produced by such systems information can be used for real-time operational control, production optimization and troubleshooting.

Soft sensing of system parameters in membrane distillation

KAUST Repository

Laleg-Kirati, Taous-Meriem

2017-01-01

Various examples of methods and systems are provided for soft sensing of system parameters in membrane distillation (MD). In one example, a system includes a MD module comprising a feed side and a permeate side separated by a membrane boundary layer

Multi-Channel Wireless Sensor Networks: Protocols, Design and Evaluation

OpenAIRE

Durmaz, O.

2009-01-01

Pervasive systems, which are described as networked embedded systems integrated with everyday environments, are considered to have the potential to change our daily lives by creating smart surroundings and by their ubiquity, just as the Internet. In the last decade, “Wireless Sensor Networks��? have appeared as one of the real-world examples of pervasive systems by combining automated sensing, embedded computing and wireless networking into tiny embedded devices. A wireless sensor network typ...

High precision relative position sensing system for formation flying spacecraft

Data.gov (United States)

National Aeronautics and Space Administration — We propose to develop and test an optical sensing system that provides high precision relative position sensing for formation flying spacecraft.  A high precision...

Computer Networks A Systems Approach

CERN Document Server

Peterson, Larry L

2011-01-01

This best-selling and classic book teaches you the key principles of computer networks with examples drawn from the real world of network and protocol design. Using the Internet as the primary example, the authors explain various protocols and networking technologies. Their systems-oriented approach encourages you to think about how individual network components fit into a larger, complex system of interactions. Whatever your perspective, whether it be that of an application developer, network administrator, or a designer of network equipment or protocols, you will come away with a "big pictur

Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

Directory of Open Access Journals (Sweden)

Andre Terzic

2009-04-01

Full Text Available Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7 are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network.

System Capacity Limits Introduced by Data Fusion on Cooperative Spectrum Sensing under Correlated Environments

DEFF Research Database (Denmark)

Pratas, Nuno; Marchetti, Nicola; Prasad, Neeli R.

2010-01-01

on cooperative sensing schemes. The analysis is supported by evaluation metrics which accounts for the perceived capacity limits. The analysis is performed along the data fusion chain, comparing several scenarios encompassing different degrees of environment correlation between the cluster nodes, number......Spectrum sensing, the cornerstone of the Cognitive Radio paradigm, has been the focus of intensive research, from which the main conclusion was that its performance can be greatly enhanced through the use of cooperative sensing schemes. Nevertheless, if a proper design of the cooperative scheme...... is not followed, then the use of cooperative schemes will introduce some limitations in the network perceived capacity. In this paper, we analyze the performance of a cooperative spectrum sensing scheme based on Data Fusion, by measuring the perceived capacity limits introduced by the use of Data Fusion...

Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network

Directory of Open Access Journals (Sweden)

Matti Mantere

2013-09-01

Full Text Available The deterministic and restricted nature of industrial control system networks sets them apart from more open networks, such as local area networks in office environments. This improves the usability of network security, monitoring approaches that would be less feasible in more open environments. One of such approaches is machine learning based anomaly detection. Without proper customization for the special requirements of the industrial control system network environment, many existing anomaly or misuse detection systems will perform sub-optimally. A machine learning based approach could reduce the amount of manual customization required for different industrial control system networks. In this paper we analyze a possible set of features to be used in a machine learning based anomaly detection system in the real world industrial control system network environment under investigation. The network under investigation is represented by architectural drawing and results derived from network trace analysis. The network trace is captured from a live running industrial process control network and includes both control data and the data flowing between the control network and the office network. We limit the investigation to the IP traffic in the traces.

Network speech systems technology program

Science.gov (United States)

Weinstein, C. J.

1981-09-01

This report documents work performed during FY 1981 on the DCA-sponsored Network Speech Systems Technology Program. The two areas of work reported are: (1) communication system studies in support of the evolving Defense Switched Network (DSN) and (2) design and implementation of satellite/terrestrial interfaces for the Experimental Integrated Switched Network (EISN). The system studies focus on the development and evaluation of economical and endurable network routing procedures. Satellite/terrestrial interface development includes circuit-switched and packet-switched connections to the experimental wideband satellite network. Efforts in planning and coordination of EISN experiments are reported in detail in a separate EISN Experiment Plan.

Multiparameter fiber optic sensing system for monitoring enhanced geothermal systems

Energy Technology Data Exchange (ETDEWEB)

Challener, William A

2014-12-04

The goal of this project was to design, fabricate and test an optical fiber cable which supports multiple sensing modalities for measurements in the harsh environment of enhanced geothermal systems. To accomplish this task, optical fiber was tested at both high temperatures and strains for mechanical integrity, and in the presence of hydrogen for resistance to darkening. Both single mode (SM) and multimode (MM) commercially available optical fiber were identified and selected for the cable based on the results of these tests. The cable was designed and fabricated using a tube-within-tube construction containing two MM fibers and one SM fiber, and without supporting gel that is not suitable for high temperature environments. Commercial fiber optic sensing instruments using Raman DTS (distributed temperature sensing), Brillouin DTSS (distributed temperature and strain sensing), and Raleigh COTDR (coherent optical time domain reflectometry) were selected for field testing. A microelectromechanical systems (MEMS) pressure sensor was designed, fabricated, packaged, and calibrated for high pressure measurements at high temperatures and spliced to the cable. A fiber Bragg grating (FBG) temperature sensor was also spliced to the cable. A geothermal well was selected and its temperature and pressure were logged. The cable was then deployed in the well in two separate field tests and measurements were made on these different sensing modalities. Raman DTS measurements were found to be accurate to ±5°C, even with some residual hydrogen darkening. Brillouin DTSS measurements were in good agreement with the Raman results. The Rayleigh COTDR instrument was able to detect some acoustic signatures, but was generally disappointing. The FBG sensor was used to determine the effects of hydrogen darkening, but drift over time made it unreliable as a temperature or pressure sensor. The MEMS sensor was found to be highly stable and accurate to better than its 0.1% calibration.

Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG

Directory of Open Access Journals (Sweden)

Wenquan Jin

2018-02-01

Full Text Available Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention. Several solutions are proposed in the literature based on manual interpretation through explicit programming. However, programmatically implementing the interpretation of the data sender and data receiver in the e-Health system for the data transmission is counterproductive as modification will be required for each new device added into the system. In this paper, an e-Health system with the Semantic Sensor Network (SSN is proposed to address the device interoperability issue. In the proposed system, we have used IETF YANG for modeling the semantic e-Health data to represent the information of e-Health sensors. This modeling scheme helps in provisioning semantic interoperability between devices and expressing the sensing data in a user-friendly manner. For this purpose, we have developed an ontology for e-Health data that supports different styles of data formats. The ontology is defined in YANG for provisioning semantic interpretation of sensing data in the system by constructing meta-models of e-Health sensors. The proposed approach assists in the auto-configuration of eHealth sensors and querying the sensor network with semantic interoperability support for the e-Health system.

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

Science.gov (United States)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

Networks as systems.

Science.gov (United States)

Best, Allan; Berland, Alex; Greenhalgh, Trisha; Bourgeault, Ivy L; Saul, Jessie E; Barker, Brittany

2018-03-19

Purpose The purpose of this paper is to present a case study of the World Health Organization's Global Healthcare Workforce Alliance (GHWA). Based on a commissioned evaluation of GHWA, it applies network theory and key concepts from systems thinking to explore network emergence, effectiveness, and evolution to over a ten-year period. The research was designed to provide high-level strategic guidance for further evolution of global governance in human resources for health (HRH). Design/methodology/approach Methods included a review of published literature on HRH governance and current practice in the field and an in-depth case study whose main data sources were relevant GHWA background documents and key informant interviews with GHWA leaders, staff, and stakeholders. Sampling was purposive and at a senior level, focusing on board members, executive directors, funders, and academics. Data were analyzed thematically with reference to systems theory and Shiffman's theory of network development. Findings Five key lessons emerged: effective management and leadership are critical; networks need to balance "tight" and "loose" approaches to their structure and processes; an active communication strategy is key to create and maintain support; the goals, priorities, and membership must be carefully focused; and the network needs to support shared measurement of progress on agreed-upon goals. Shiffman's middle-range network theory is a useful tool when guided by the principles of complex systems that illuminate dynamic situations and shifting interests as global alliances evolve. Research limitations/implications This study was implemented at the end of the ten-year funding cycle. A more continuous evaluation throughout the term would have provided richer understanding of issues. Experience and perspectives at the country level were not assessed. Practical implications Design and management of large, complex networks requires ongoing attention to key issues like leadership

The entire network topology display system of terminal communication access network

OpenAIRE

An Yi

2016-01-01

Now order terminal communication access network is network technology in Shanxi Province is diversiform, device type complex, lack of unified technical standard, the terminal communication access network management system of construction constitutes a great obstacle. Need to build a “unified communication interface and communication standard, unified communications network management” of the terminal communication access network cut in the integrated network management system, for the termina...

Observing Arctic Ecology using Networked Infomechanical Systems

Science.gov (United States)

Healey, N. C.; Oberbauer, S. F.; Hollister, R. D.; Tweedie, C. E.; Welker, J. M.; Gould, W. A.

2012-12-01

Understanding ecological dynamics is important for investigation into the potential impacts of climate change in the Arctic. Established in the early 1990's, the International Tundra Experiment (ITEX) began observational inquiry of plant phenology, plant growth, community composition, and ecosystem properties as part of a greater effort to study changes across the Arctic. Unfortunately, these observations are labor intensive and time consuming, greatly limiting their frequency and spatial coverage. We have expanded the capability of ITEX to analyze ecological phenomenon with improved spatial and temporal resolution through the use of Networked Infomechanical Systems (NIMS) as part of the Arctic Observing Network (AON) program. The systems exhibit customizable infrastructure that supports a high level of versatility in sensor arrays in combination with information technology that allows for adaptable configurations to numerous environmental observation applications. We observe stereo and static time-lapse photography, air and surface temperature, incoming and outgoing long and short wave radiation, net radiation, and hyperspectral reflectance that provides critical information to understanding how vegetation in the Arctic is responding to ambient climate conditions. These measurements are conducted concurrent with ongoing manual measurements using ITEX protocols. Our NIMS travels at a rate of three centimeters per second while suspended on steel cables that are ~1 m from the surface spanning transects ~50 m in length. The transects are located to span soil moisture gradients across a variety of land cover types including dry heath, moist acidic tussock tundra, shrub tundra, wet meadows, dry meadows, and water tracks. We have deployed NIMS at four locations on the North Slope of Alaska, USA associated with 1 km2 ARCSS vegetation study grids including Barrow, Atqasuk, Toolik Lake, and Imnavait Creek. A fifth system has been deployed in Thule, Greenland beginning in

Ship detection in optical remote sensing images based on deep convolutional neural networks

Science.gov (United States)

Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Zhao, Danpei; Cai, Bowen

2017-10-01

Automatic ship detection in optical remote sensing images has attracted wide attention for its broad applications. Major challenges for this task include the interference of cloud, wave, wake, and the high computational expenses. We propose a fast and robust ship detection algorithm to solve these issues. The framework for ship detection is designed based on deep convolutional neural networks (CNNs), which provide the accurate locations of ship targets in an efficient way. First, the deep CNN is designed to extract features. Then, a region proposal network (RPN) is applied to discriminate ship targets and regress the detection bounding boxes, in which the anchors are designed by intrinsic shape of ship targets. Experimental results on numerous panchromatic images demonstrate that, in comparison with other state-of-the-art ship detection methods, our method is more efficient and achieves higher detection accuracy and more precise bounding boxes in different complex backgrounds.

Toward a Nationwide Mobile-Based Public Healthcare Service System with Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Chien-wen Shen

2016-01-01

Full Text Available This paper describes the development of a nationwide public healthcare service system with the integration of cloud technology, wireless sensor networks, and mobile technology to provide citizens with convenient and professional healthcare services. The basic framework of the system includes the architectures for the user end of wireless physiological examinations, for the regional healthcare cloud, and for national public healthcare service system. Citizens with chronic conditions or elderly people who are living alone can use the wireless physiological sensing devices to keep track of their health conditions and get warning if the system detects abnormal signals. Through mobile devices, citizens are able to get real-time health advice, prompt warning, health information, feedback, personalized support, and intervention ubiquitously. With the long-term tracking data for physiological sensing, reliable prediction models for epidemic diseases and chronic diseases can be developed for the government to respond to and control diseases immediately. Besides, such a nationwide approach enables government to have a holistic understanding of the public health information in real time, which is helpful to establish effective policies or strategies to prevent epidemic diseases or chronic diseases.

Large scale network-centric distributed systems

CERN Document Server

Sarbazi-Azad, Hamid

2014-01-01

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

Seamless integrated network system for wireless communication systems

NARCIS (Netherlands)

Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

2006-01-01

To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

Seamless integrated network system for wireless communication systems

NARCIS (Netherlands)

Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

2002-01-01

To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

Impact of dam failure-induced flood on road network using combined remote sensing and geospatial approach

Science.gov (United States)

Foumelis, Michael

2017-01-01

The applicability of the normalized difference water index (NDWI) to the delineation of dam failure-induced floods is demonstrated for the case of the Sparmos dam (Larissa, Central Greece). The approach followed was based on the differentiation of NDWI maps to accurately define the extent of the inundated area over different time spans using multimission Earth observation optical data. Besides using Landsat data, for which the index was initially designed, higher spatial resolution data from Sentinel-2 mission were also successfully exploited. A geospatial analysis approach was then introduced to rapidly identify potentially affected segments of the road network. This allowed for further correlation to actual damages in the following damage assessment and remediation activities. The proposed combination of geographic information systems and remote sensing techniques can be easily implemented by local authorities and civil protection agencies for mapping and monitoring flood events.

Opportunistic Carrier Sensing for Energy-Efficient Information Retrieval in Sensor Networks

Directory of Open Access Journals (Sweden)

Zhao Qing

2005-01-01

Full Text Available We consider distributed information retrieval for sensor networks with cluster heads or mobile access points. The performance metric used in the design is energy efficiency defined as the ratio of the average number of bits reliably retrieved by the access point to the total amount of energy consumed. A distributed opportunistic transmission protocol is proposed using a combination of carrier sensing and backoff strategy that incorporates channel state information (CSI of individual sensors. By selecting a set of sensors with the best channel states to transmit, the proposed protocol achieves the upper bound on energy efficiency when the signal propagation delay is negligible. For networks with substantial propagation delays, a backoff function optimized for energy efficiency is proposed. The design of this backoff function utilizes properties of extreme statistics and is shown to have mild performance loss in practical scenarios. We also demonstrate that opportunistic strategies that use CSI may not be optimal when channel acquisition at individual sensors consumes substantial energy. We show further that there is an optimal sensor density for which the opportunistic information retrieval is the most energy efficient. This observation leads to the design of the optimal sensor duty cycle.

A Fine-Grained Data Access Control System in Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Boniface K. Alese

2015-12-01

Full Text Available The evolving realities of Wireless Sensor Network (WSN deployed to various terrain of life require serving multiple applications. As large amount of sensed data are distributed and stored in individual sensors nodes, the illegal access to these sensitive data can be devastating. Consequently, data insecurity becomes a big concern. This study, therefore, proposes a fine-grained access control system which only requires the right set of users to access a particular data, based on their access privileges in the sensor networks. It is designed using Priccess Protocol with Access policy formulation adopting the principle of Bell Lapadula model as well as Attribute-Based Encryption (ABE to control access to sensor data. The functionality of the proposed system is simulated using Netbeans. The performance analysis of the proposed system using execution time and size of the key show that the higher the key size, the harder it becomes for the attacker to hack the system. Additionally, the time taken for the proposed work is lesser which makes the work faster than the existing work. Consequently, a well secure interactive web-based application that could facilitates the field officers access to stored data in safe and secure manner is developed.

LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

Science.gov (United States)

Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

2014-11-01

The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product

Communicating embedded systems networks applications

CERN Document Server

Krief, Francine

2013-01-01

Embedded systems become more and more complex and require having some knowledge in various disciplines such as electronics, data processing, telecommunications and networks. Without detailing all the aspects related to the design of embedded systems, this book, which was written by specialists in electronics, data processing and telecommunications and networks, gives an interesting point of view of communication techniques and problems in embedded systems. This choice is easily justified by the fact that embedded systems are today massively communicating and that telecommunications and network

Efficient Wideband Spectrum Sensing with Maximal Spectral Efficiency for LEO Mobile Satellite Systems

Directory of Open Access Journals (Sweden)

Feilong Li

2017-01-01

Full Text Available The usable satellite spectrum is becoming scarce due to static spectrum allocation policies. Cognitive radio approaches have already demonstrated their potential towards spectral efficiency for providing more spectrum access opportunities to secondary user (SU with sufficient protection to licensed primary user (PU. Hence, recent scientific literature has been focused on the tradeoff between spectrum reuse and PU protection within narrowband spectrum sensing (SS in terrestrial wireless sensing networks. However, those narrowband SS techniques investigated in the context of terrestrial CR may not be applicable for detecting wideband satellite signals. In this paper, we mainly investigate the problem of joint designing sensing time and hard fusion scheme to maximize SU spectral efficiency in the scenario of low earth orbit (LEO mobile satellite services based on wideband spectrum sensing. Compressed detection model is established to prove that there indeed exists one optimal sensing time achieving maximal spectral efficiency. Moreover, we propose novel wideband cooperative spectrum sensing (CSS framework where each SU reporting duration can be utilized for its following SU sensing. The sensing performance benefits from the novel CSS framework because the equivalent sensing time is extended by making full use of reporting slot. Furthermore, in respect of time-varying channel, the spatiotemporal CSS (ST-CSS is presented to attain space and time diversity gain simultaneously under hard decision fusion rule. Computer simulations show that the optimal sensing settings algorithm of joint optimization of sensing time, hard fusion rule and scheduling strategy achieves significant improvement in spectral efficiency. Additionally, the novel ST-CSS scheme performs much higher spectral efficiency than that of general CSS framework.

Mobile Networked Sensors for Environmental Observatories

Science.gov (United States)

Kaiser, W. J.

2005-12-01

The development of the first embedded networked sensing (ENS) systems has been rapidly followed by their successful deployment for investigations in environments ranging from forest ecosystems, to rivers and lakes, and to subsurface soil observations. As ENS systems have been deployed, many technology challenges have been successfully addressed. For example, the requirements for local and remote data access and long operating life have been encountered and solved with a novel hierarchical network architecture and unique, low power platforms. This presentation will describe this progress and also the development and applications of a new ENS system addressing the most current challenges: A robotic ENS platform providing precise, reliable, and sustained observation capability with diverse sensing capabilities that may adapt to environmental dynamics. In the development of methods for autonomous observation by networked sensors, many applications have emerged requiring spatially and temporally intensive data sampling. Examples include the mapping of forest understory solar radiation, autonomous acquisition of imaging for plant phenology, and mapping of contaminant concentration in aquatic systems. Common to these applications is the need to actively and continuously configure the location and orientation of sensors for high fidelity mapping of the spatial distribution of phenomena. To address this primary environmental observation need, a new sensing platform, Networked Infomechanical Systems (NIMS) has been developed. NIMS relies on deployed aerial infrastructure (for example, cable suspension systems) in the natural environment to permit robotic devices to precisely and reliably move or remain stationary as required at elevations that may lie directly in or above the forest canopy or within a river or stream. NIMS systems are suspended to allow devices to translate a sensor node horizontally, and also to raise and lower devices. Examples of sensors that are now

From biological and social network metaphors to coupled bio-social wireless networks

Science.gov (United States)

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462

A COMPARATIVE STUDY OF SYSTEM NETWORK ARCHITECTURE Vs DIGITAL NETWORK ARCHITECTURE

OpenAIRE

Seema; Mukesh Arya

2011-01-01

The efficient managing system of sources is mandatory for the successful running of any network. Here this paper describes the most popular network architectures one of developed by IBM, System Network Architecture (SNA) and other is Digital Network Architecture (DNA). As we know that the network standards and protocols are needed for the network developers as well as users. Some standards are The IEEE 802.3 standards (The Institute of Electrical and Electronics Engineers 1980) (LAN), IBM Sta...

Development of Light Powered Sensor Networks for Thermal Comfort Measurement

Directory of Open Access Journals (Sweden)

Dasheng Lee

2008-10-01

Full Text Available Recent technological advances in wireless communications have enabled easy installation of sensor networks with air conditioning equipment control applications. However, the sensor node power supply, through either power lines or battery power, still presents obstacles to the distribution of the sensing systems. In this study, a novel sensor network, powered by the artificial light, was constructed to achieve wireless power transfer and wireless data communications for thermal comfort measurements. The sensing node integrates an IC-based temperature sensor, a radiation thermometer, a relative humidity sensor, a micro machined flow sensor and a microprocessor for predicting mean vote (PMV calculation. The 935 MHz band RF module was employed for the wireless data communication with a specific protocol based on a special energy beacon enabled mode capable of achieving zero power consumption during the inactive periods of the nodes. A 5W spotlight, with a dual axis tilt platform, can power the distributed nodes over a distance of up to 5 meters. A special algorithm, the maximum entropy method, was developed to estimate the sensing quantity of climate parameters if the communication module did not receive any response from the distributed nodes within a certain time limit. The light-powered sensor networks were able to gather indoor comfort-sensing index levels in good agreement with the comfort-sensing vote (CSV preferred by a human being and the experimental results within the environment suggested that the sensing system could be used in air conditioning systems to implement a comfort-optimal control strategy.

Delays and networked control systems

CERN Document Server

Hetel, Laurentiu; Daafouz, Jamal; Johansson, Karl

2016-01-01

This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students. .

RoboSmith: Wireless Networked Architecture for Multiagent Robotic System

Directory of Open Access Journals (Sweden)

Florin Moldoveanu

2010-11-01

Full Text Available In this paper is presented an architecture for a flexible mini robot for a multiagent robotic system. In a multiagent system the value of an individual agent is negligible since the goal of the system is essential. Thus, the agents (robots need to be small, low cost and cooperative. RoboSmith are designed based on these conditions. The proposed architecture divide a robot into functional modules such as locomotion, control, sensors, communication, and actuation. Any mobile robot can be constructed by combining these functional modules for a specific application. An embedded software with dynamic task uploading and multi-tasking abilities is developed in order to create better interface between robots and the command center and among the robots. The dynamic task uploading allows the robots change their behaviors in runtime. The flexibility of the robots is given by facts that the robots can work in multiagent system, as master-slave, or hybrid mode, can be equipped with different modules and possibly be used in other applications such as mobile sensor networks remote sensing, and plant monitoring.

Network Intrusion Detection System using Apache Storm

Directory of Open Access Journals (Sweden)

Muhammad Asif Manzoor

2017-06-01

Full Text Available Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various systems are proposed to enhance the network security. We are proposing to use anomaly based network intrusion detection system in this work. Anomaly based intrusion detection system can identify the new network threats. We also propose to use Real-time Big Data Stream Processing Framework, Apache Storm, for the implementation of network intrusion detection system. Apache Storm can help to manage the network traffic which is generated at enormous speed and size and the network traffic speed and size is constantly increasing. We have used Support Vector Machine in this work. We use Knowledge Discovery and Data Mining 1999 (KDD’99 dataset to test and evaluate our proposed solution.

NASDA knowledge-based network planning system

Science.gov (United States)

Yamaya, K.; Fujiwara, M.; Kosugi, S.; Yambe, M.; Ohmori, M.

1993-01-01

One of the SODS (space operation and data system) sub-systems, NP (network planning) was the first expert system used by NASDA (national space development agency of Japan) for tracking and control of satellite. The major responsibilities of the NP system are: first, the allocation of network and satellite control resources and, second, the generation of the network operation plan data (NOP) used in automated control of the stations and control center facilities. Up to now, the first task of network resource scheduling was done by network operators. NP system automatically generates schedules using its knowledge base, which contains information on satellite orbits, station availability, which computer is dedicated to which satellite, and how many stations must be available for a particular satellite pass or a certain time period. The NP system is introduced.

Autonomous power networks based power system

International Nuclear Information System (INIS)

Jokic, A.; Van den Bosch, P.P.J.

2006-01-01

This paper presented the concept of autonomous networks to cope with this increased complexity in power systems while enhancing market-based operation. The operation of future power systems will be more challenging and demanding than present systems because of increased uncertainties, less inertia in the system, replacement of centralized coordinating activities by decentralized parties and the reliance on dynamic markets for both power balancing and system reliability. An autonomous network includes the aggregation of networked producers and consumers in a relatively small area with respect to the overall system. The operation of an autonomous network is coordinated and controlled with one central unit acting as an interface between internal producers/consumers and the rest of the power system. In this study, the power balance problem and system reliability through provision of ancillary services was formulated as an optimization problem for the overall autonomous networks based power system. This paper described the simulation of an optimal autonomous network dispatching in day ahead markets, based on predicted spot prices for real power, and two ancillary services. It was concluded that large changes occur in a power systems structure and operation, most of them adding to the uncertainty and complexity of the system. The introduced concept of an autonomous power network-based power system was shown to be a realistic and consistent approach to formulate and operate a market-based dispatch of both power and ancillary services. 9 refs., 4 figs

Advanced feed-through systems for in-well optical fibre sensing

International Nuclear Information System (INIS)

Shiach, G; Nolan, A; McAvoy, S; McStay, D; Prel, C; Smith, M

2007-01-01

A new optical fibre feed-through for use in subsea in-well optical fibre sensing systems is reported. The new feed-through is compatible for use with standard subsea Christmas Tree penetrators and allows multiple re-mating of the feed-through over the lifetime of the device. The system has been extensively tested under in-well conditions and found to conform to the performance requirements. The new feed-through is planned to be used in one of the first subsea optical fibre in-well sensing systems

The organophosphate malathion disturbs gut microbiome development and the quorum-Sensing system.

Science.gov (United States)

Gao, Bei; Chi, Liang; Tu, Pengcheng; Bian, Xiaoming; Thomas, Jesse; Ru, Hongyu; Lu, Kun

2018-02-01

The gut microbiome has tremendous potential to impact health and disease. Various environmental toxicants, including insecticides, have been shown to alter gut microbiome community structures. However, the mechanism that compositionally and functionally regulates gut microbiota remains unclear. Quorum sensing is known to modulate intra- and interspecies gene expression and coordinate population responses. It is unknown whether quorum sensing is disrupted when environmental toxicants cause perturbations in the gut microbiome community structure. To reveal the response of the quorum-sensing system to environmental exposure, we use a combination of Illumina-based 16S rRNA gene amplicon and shotgun metagenome sequencing to examine the impacts of a widely used organophosphate insecticide, malathion, on the gut microbiome trajectory, quorum sensing system and behaviors related to quorum sensing, such as motility and pathogenicity. Our results demonstrated that malathion perturbed the gut microbiome development, quorum sensing and quorum sensing related behaviors. These findings may provide a novel mechanistic understanding of the role of quorum-sensing in the gut microbiome toxicity of malathion. Copyright © 2017. Published by Elsevier B.V.

A Real-Time Smooth Weighted Data Fusion Algorithm for Greenhouse Sensing Based on Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Tengyue Zou

2017-11-01

Full Text Available Wireless sensor networks are widely used to acquire environmental parameters to support agricultural production. However, data variation and noise caused by actuators often produce complex measurement conditions. These factors can lead to nonconformity in reporting samples from different nodes and cause errors when making a final decision. Data fusion is well suited to reduce the influence of actuator-based noise and improve automation accuracy. A key step is to identify the sensor nodes disturbed by actuator noise and reduce their degree of participation in the data fusion results. A smoothing value is introduced and a searching method based on Prim’s algorithm is designed to help obtain stable sensing data. A voting mechanism with dynamic weights is then proposed to obtain the data fusion result. The dynamic weighting process can sharply reduce the influence of actuator noise in data fusion and gradually condition the data to normal levels over time. To shorten the data fusion time in large networks, an acceleration method with prediction is also presented to reduce the data collection time. A real-time system is implemented on STMicroelectronics STM32F103 and NORDIC nRF24L01 platforms and the experimental results verify the improvement provided by these new algorithms.

Matching of Remote Sensing Images with Complex Background Variations via Siamese Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Haiqing He

2018-02-01

Full Text Available Feature-based matching methods have been widely used in remote sensing image matching given their capability to achieve excellent performance despite image geometric and radiometric distortions. However, most of the feature-based methods are unreliable for complex background variations, because the gradient or other image grayscale information used to construct the feature descriptor is sensitive to image background variations. Recently, deep learning-based methods have been proven suitable for high-level feature representation and comparison in image matching. Inspired by the progresses made in deep learning, a new technical framework for remote sensing image matching based on the Siamese convolutional neural network is presented in this paper. First, a Siamese-type network architecture is designed to simultaneously learn the features and the corresponding similarity metric from labeled training examples of matching and non-matching true-color patch pairs. In the proposed network, two streams of convolutional and pooling layers sharing identical weights are arranged without the manually designed features. The number of convolutional layers is determined based on the factors that affect image matching. The sigmoid function is employed to compute the matching and non-matching probabilities in the output layer. Second, a gridding sub-pixel Harris algorithm is used to obtain the accurate localization of candidate matches. Third, a Gaussian pyramid coupling quadtree is adopted to gradually narrow down the searching space of the candidate matches, and multiscale patches are compared synchronously. Subsequently, a similarity measure based on the output of the sigmoid is adopted to find the initial matches. Finally, the random sample consensus algorithm and the whole-to-local quadratic polynomial constraints are used to remove false matches. In the experiments, different types of satellite datasets, such as ZY3, GF1, IKONOS, and Google Earth images

ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

Directory of Open Access Journals (Sweden)

Santosh Kumar Chaudhari

2011-06-01

Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

Energy Harvesting for Structural Health Monitoring Sensor Networks

Energy Technology Data Exchange (ETDEWEB)

Park, G.; Farrar, C. R.; Todd, M. D.; Hodgkiss, T.; Rosing, T.

2007-02-26

This report has been developed based on information exchanges at a 2.5-day workshop on energy harvesting for embedded structural health monitoring (SHM) sensing systems that was held June 28-30, 2005, at Los Alamos National Laboratory. The workshop was hosted by the LANL/UCSD Engineering Institute (EI). This Institute is an education- and research-focused collaboration between Los Alamos National Laboratory (LANL) and the University of California, San Diego (UCSD), Jacobs School of Engineering. A Statistical Pattern Recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portion of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized, followed by a discussion of SHM sensor network paradigms, power requirements for these networks and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. This discussion also addresses current energy harvesting applications and system integration issues. The report concludes by defining some future research directions and possible technology demonstrations that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes.

THE NEED AND KEYS FOR A NEW GENERATION NETWORK ADJUSTMENT SOFTWARE

Directory of Open Access Journals (Sweden)

I. Colomina

2012-07-01

Full Text Available Orientation and calibration of photogrammetric and remote sensing instruments is a fundamental capacity of current mapping systems and a fundamental research topic. Neither digital remote sensing acquisition systems nor direct orientation gear, like INS and GNSS technologies, made block adjustment obsolete. On the contrary, the continuous flow of new primary data acquisition systems has challenged the capacity of the legacy block adjustment systems – in general network adjustment systems – in many aspects: extensibility, genericity, portability, large data sets capacity, metadata support and many others. In this article, we concentrate on the extensibility and genericity challenges that current and future network systems shall face. For this purpose we propose a number of software design strategies with emphasis on rigorous abstract modeling that help in achieving simplicity, genericity and extensibility together with the protection of intellectual proper rights in a flexible manner. We illustrate our suggestions with the general design approach of GENA, the generic extensible network adjustment system of GeoNumerics.

3D Convolutional Neural Networks for Crop Classification with Multi-Temporal Remote Sensing Images

Directory of Open Access Journals (Sweden)

Shunping Ji

2018-01-01

Full Text Available This study describes a novel three-dimensional (3D convolutional neural networks (CNN based method that automatically classifies crops from spatio-temporal remote sensing images. First, 3D kernel is designed according to the structure of multi-spectral multi-temporal remote sensing data. Secondly, the 3D CNN framework with fine-tuned parameters is designed for training 3D crop samples and learning spatio-temporal discriminative representations, with the full crop growth cycles being preserved. In addition, we introduce an active learning strategy to the CNN model to improve labelling accuracy up to a required threshold with the most efficiency. Finally, experiments are carried out to test the advantage of the 3D CNN, in comparison to the two-dimensional (2D CNN and other conventional methods. Our experiments show that the 3D CNN is especially suitable in characterizing the dynamics of crop growth and outperformed the other mainstream methods.

Plantar Pressure Detection with Fiber Bragg Gratings Sensing System

Directory of Open Access Journals (Sweden)

Tsair-Chun Liang

2016-10-01

Full Text Available In this paper, a novel fiber-optic sensing system based on fiber Bragg gratings (FBGs to measure foot plantar pressure is proposed. This study first explores the Pedar-X insole foot pressure types of the adult-size chart and then defines six measurement areas to effectively identify four foot types: neutral foot, cavus foot, supinated foot and flat foot. The plantar pressure signals are detected by only six FBGs, which are embedded in silicone rubber. The performance of the fiber optic sensing is examined and compared with a digital pressure plate of i-Step P1000 with 1024 barometric sensors. In the experiment, there are 11 participants with different foot types to participate in the test. The Pearson correlation coefficient, which is determined from the measured results of the homemade fiber-optic plantar pressure system and i-Step P1000 plantar pressure plate, reaches up to 0.671 (p < 0.01. According to the measured results from the plantar pressure data, the proposed fiber optic sensing system can successfully identify the four different foot types. Measurements of this study have demonstrated the feasibility of the proposed system so that it can be an alternative for plantar pressure detection systems.

Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

Directory of Open Access Journals (Sweden)

Wang Chao

2016-03-01

Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

CERN Document Server

Su, Housheng

2013-01-01

Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

A Privacy-Preserving Incentive Mechanism for Participatory Sensing Systems

Directory of Open Access Journals (Sweden)

Xiaoguang Niu

2018-01-01

Full Text Available The proliferation of mobile devices has facilitated the prevalence of participatory sensing applications in which participants collect and share information in their environments. The design of a participatory sensing application confronts two challenges: “privacy” and “incentive” which are two conflicting objectives and deserve deeper attention. Inspired by physical currency circulation system, this paper introduces the notion of E-cent, an exchangeable unit bearer currency. Participants can use the E-cent to take part in tasks anonymously. By employing E-cent, we propose an E-cent-based privacy-preserving incentive mechanism, called EPPI. As a dynamic balance regulatory mechanism, EPPI can not only protect the privacy of participant, but also adjust the whole system to the ideal situation, under which the rated tasks can be finished at minimal cost. To the best of our knowledge, EPPI is the first attempt to build an incentive mechanism while maintaining the desired privacy in participatory sensing systems. Extensive simulation and analysis results show that EPPI can achieve high anonymity level and remarkable incentive effects.

H∞ Filtering for Networked Markovian Jump Systems with Multiple Stochastic Communication Delays

Directory of Open Access Journals (Sweden)

Hui Dong

2015-01-01

Full Text Available This paper is concerned with the H∞ filtering for a class of networked Markovian jump systems with multiple communication delays. Due to the existence of communication constraints, the measurement signal cannot arrive at the filter completely on time, and the stochastic communication delays are considered in the filter design. Firstly, a set of stochastic variables is introduced to model the occurrence probabilities of the delays. Then based on the stochastic system approach, a sufficient condition is obtained such that the filtering error system is stable in the mean-square sense and with a prescribed H∞ disturbance attenuation level. The optimal filter gain parameters can be determined by solving a convex optimization problem. Finally, a simulation example is given to show the effectiveness of the proposed filter design method.

Healthcare regions and their care networks: an organizational-systemic model for SUS.

Science.gov (United States)

Santos, Lenir

2017-04-01

This paper describes a comprehensive effort to develop studies regarding Brazil's Unified Healthcare System (SUS), as a result of the combination of public services in a network that follows a region-based rationale (tripartite organization). The SUS emerges from such an integration and should be organized as such. The intention is to demonstrate that this type of organization is essential, given that Brazil is organized as a Federation, and all three governmental levels are, in a broad sense, equally responsible for healthcare. Healthcare services and actions are a complex set of activities that are interconnected on behalf of citizen health, which is a global concept that cannot be split up. Services must follow this rationale and be organized as such. Thus, healthcare services must be systematically organized to serve everyone equally, regardless of where a citizen lives. This systemic organization requires permanent interaction between federative units to discuss and operationalize reference services, funding and other technical and administrative aspects. These are the essential elements that make the SUS so complex and demand it be organized regionally, as a network of healthcare services.

Energy-Efficient Distributed Filtering in Sensor Networks: A Unified Switched System Approach.

Science.gov (United States)

Zhang, Dan; Shi, Peng; Zhang, Wen-An; Yu, Li

2016-04-21

This paper is concerned with the energy-efficient distributed filtering in sensor networks, and a unified switched system approach is proposed to achieve this goal. For the system under study, the measurement is first sampled under nonuniform sampling periods, then the local measurement elements are selected and quantized for transmission. Then, the transmission rate is further reduced to save constrained power in sensors. Based on the switched system approach, a unified model is presented to capture the nonuniform sampling, the measurement size reduction, the transmission rate reduction, the signal quantization, and the measurement missing phenomena. Sufficient conditions are obtained such that the filtering error system is exponentially stable in the mean-square sense with a prescribed H∞ performance level. Both simulation and experiment studies are given to show the effectiveness of the proposed new design technique.

ISTA-Net: Iterative Shrinkage-Thresholding Algorithm Inspired Deep Network for Image Compressive Sensing

KAUST Repository

Zhang, Jian

2017-06-24

Traditional methods for image compressive sensing (CS) reconstruction solve a well-defined inverse problem that is based on a predefined CS model, which defines the underlying structure of the problem and is generally solved by employing convergent iterative solvers. These optimization-based CS methods face the challenge of choosing optimal transforms and tuning parameters in their solvers, while also suffering from high computational complexity in most cases. Recently, some deep network based CS algorithms have been proposed to improve CS reconstruction performance, while dramatically reducing time complexity as compared to optimization-based methods. Despite their impressive results, the proposed networks (either with fully-connected or repetitive convolutional layers) lack any structural diversity and they are trained as a black box, void of any insights from the CS domain. In this paper, we combine the merits of both types of CS methods: the structure insights of optimization-based method and the performance/speed of network-based ones. We propose a novel structured deep network, dubbed ISTA-Net, which is inspired by the Iterative Shrinkage-Thresholding Algorithm (ISTA) for optimizing a general $l_1$ norm CS reconstruction model. ISTA-Net essentially implements a truncated form of ISTA, where all ISTA-Net parameters are learned end-to-end to minimize a reconstruction error in training. Borrowing more insights from the optimization realm, we propose an accelerated version of ISTA-Net, dubbed FISTA-Net, which is inspired by the fast iterative shrinkage-thresholding algorithm (FISTA). Interestingly, this acceleration naturally leads to skip connections in the underlying network design. Extensive CS experiments demonstrate that the proposed ISTA-Net and FISTA-Net outperform existing optimization-based and network-based CS methods by large margins, while maintaining a fast runtime.

Networking systems design and development

CERN Document Server

Chao, Lee

2009-01-01

Effectively integrating theory and hands-on practice, Networking Systems Design and Development provides students and IT professionals with the knowledge and skills needed to design, implement, and manage fully functioning network systems using readily available Linux networking tools. Recognizing that most students are beginners in the field of networking, the text provides step-by-step instruction for setting up a virtual lab environment at home. Grounded in real-world applications, this book provides the ideal blend of conceptual instruction and lab work to give students and IT professional

A distributed monitoring system for photovoltaic arrays based on a two-level wireless sensor network

Science.gov (United States)

Su, F. P.; Chen, Z. C.; Zhou, H. F.; Wu, L. J.; Lin, P. J.; Cheng, S. Y.; Li, Y. F.

2017-11-01

In this paper, a distributed on-line monitoring system based on a two-level wireless sensor network (WSN) is proposed for real time status monitoring of photovoltaic (PV) arrays to support the fine management and maintenance of PV power plants. The system includes the sensing nodes installed on PV modules (PVM), sensing and routing nodes installed on combiner boxes of PV sub-arrays (PVA), a sink node and a data management centre (DMC) running on a host computer. The first level WSN is implemented by the low-cost wireless transceiver nRF24L01, and it is used to achieve single hop communication between the PVM nodes and their corresponding PVA nodes. The second level WSN is realized by the CC2530 based ZigBee network for multi-hop communication among PVA nodes and the sink node. The PVM nodes are used to monitor the PVM working voltage and backplane temperature, and they send the acquired data to their PVA node via the nRF24L01 based first level WSN. The PVA nodes are used to monitor the array voltage, PV string current and environment irradiance, and they send the acquired and received data to the DMC via the ZigBee based second level WSN. The DMC is designed using the MATLAB GUIDE and MySQL database. Laboratory experiment results show that the system can effectively acquire, display, store and manage the operating and environment parameters of PVA in real time.

Multilevel Complex Networks and Systems

Science.gov (United States)

Caldarelli, Guido

2014-03-01

Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.

[Network structures in biological systems].

Science.gov (United States)

Oleskin, A V

2013-01-01

Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

Directory of Open Access Journals (Sweden)

Tong Liu

2017-12-01

Full Text Available This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF links for path-dependent walker classification. The fluctuated received signal strength (RSS sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ and hidden Markov models (HMMs are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS and non-line-of-sight (NLOS scenarios are conducted to validate the proposed method.

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links.

Science.gov (United States)

Liu, Tong; Liang, Zhuo-Qian

2017-12-05

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method.

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

Science.gov (United States)

Liang, Zhuo-qian

2017-01-01

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method. PMID:29206188

Adaptive Multipath Key Reinforcement for Energy Harvesting Wireless Sensor Networks

DEFF Research Database (Denmark)

Di Mauro, Alessio; Dragoni, Nicola

2015-01-01

Energy Harvesting - Wireless Sensor Networks (EH-WSNs) constitute systems of networked sensing nodes that are capable of extracting energy from the environment and that use the harvested energy to operate in a sustainable state. Sustainability, seen as design goal, has a significant impact...

Network Frontier Workshop 2013

Science.gov (United States)

2014-11-11

systems (the We Sport social network) to musical phenomena (the history of the MiTo Settembre Musica musical festival ). Particular attention will be then...practice characterizes most trades, from sport to music , poetry or engineering, and common sense suggests this to be true in science as well. This prompts

The layered sensing operations center: a modeling and simulation approach to developing complex ISR networks

Science.gov (United States)

Curtis, Christopher; Lenzo, Matthew; McClure, Matthew; Preiss, Bruce

2010-04-01

In order to anticipate the constantly changing landscape of global warfare, the United States Air Force must acquire new capabilities in the field of Intelligence, Surveillance, and Reconnaissance (ISR). To meet this challenge, the Air Force Research Laboratory (AFRL) is developing a unifying construct of "Layered Sensing" which will provide military decision-makers at all levels with the timely, actionable, and trusted information necessary for complete battlespace awareness. Layered Sensing is characterized by the appropriate combination of sensors and platforms (including those for persistent sensing), infrastructure, and exploitation capabilities to enable this synergistic awareness. To achieve the Layered Sensing vision, AFRL is pursuing a Modeling & Simulation (M&S) strategy through the Layered Sensing Operations Center (LSOC). An experimental ISR system-of-systems test-bed, the LSOC integrates DoD standard simulation tools with commercial, off-the-shelf video game technology for rapid scenario development and visualization. These tools will help facilitate sensor management performance characterization, system development, and operator behavioral analysis. Flexible and cost-effective, the LSOC will implement a non-proprietary, open-architecture framework with well-defined interfaces. This framework will incentivize the transition of current ISR performance models to service-oriented software design for maximum re-use and consistency. This paper will present the LSOC's development and implementation thus far as well as a summary of lessons learned and future plans for the LSOC.

Interorganizational Innovation in Systemic Networks

DEFF Research Database (Denmark)

Seemann, Janne; Dinesen, Birthe; Gustafsson, Jeppe

2013-01-01

patients with chronic obstructive pulmonary disease (COPD) to avoid readmission, perform self monitoring and to maintain rehabilitation in their homes. The aim of the paper is to identify, analyze and discuss innovation dynamics in the COPD network and on a preliminary basis to identify implications...... for managing innovations in systemic networks. The main argument of this paper is that innovation dynamics in systemic networks should be understood as a complex interplay of four logics: 1) Fragmented innovation, 2) Interface innovation, 3) Competing innovation, 4) Co-innovation. The findings indicate...... that linear n-stage models by reducing complexity and flux end up focusing only on the surface of the network and are thus unable to grasp important aspects of network dynamics. The paper suggests that there is a need for a more dynamic innovation model able to grasp the whole picture of dynamics in systemic...

Network systems security analysis

Science.gov (United States)

Yilmaz, Ä.°smail

2015-05-01

Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.

Local-area communication networks - An overview

International Nuclear Information System (INIS)

Kuemmerle, K.

1982-01-01

Local-area communication networks represent a new field of activity. In this paper we first describe three scenarios for the use of these networks, and then discuss various technical approaches. Particular emphasis is put on bus and ring systems with various media access control mechanisms. Specifically, we compare the delay-throughput characteristic of two access methods, carrier-sense multiple access with collision detection and token passing, and discuss some significant differences of bus and ring systems concerning wiring, media, transmission, and reliability. (orig.)

Rational Design of an Ultrasensitive Quorum-Sensing Switch.

Science.gov (United States)

Zeng, Weiqian; Du, Pei; Lou, Qiuli; Wu, Lili; Zhang, Haoqian M; Lou, Chunbo; Wang, Hongli; Ouyang, Qi

2017-08-18

One of the purposes of synthetic biology is to develop rational methods that accelerate the design of genetic circuits, saving time and effort spent on experiments and providing reliably predictable circuit performance. We applied a reverse engineering approach to design an ultrasensitive transcriptional quorum-sensing switch. We want to explore how systems biology can guide synthetic biology in the choice of specific DNA sequences and their regulatory relations to achieve a targeted function. The workflow comprises network enumeration that achieves the target function robustly, experimental restriction of the obtained candidate networks, global parameter optimization via mathematical analysis, selection and engineering of parts based on these calculations, and finally, circuit construction based on the principles of standardization and modularization. The performance of realized quorum-sensing switches was in good qualitative agreement with the computational predictions. This study provides practical principles for the rational design of genetic circuits with targeted functions.

Remote Sensing Image Classification Based on Stacked Denoising Autoencoder

Directory of Open Access Journals (Sweden)

Peng Liang

2017-12-01

Full Text Available Focused on the issue that conventional remote sensing image classification methods have run into the bottlenecks in accuracy, a new remote sensing image classification method inspired by deep learning is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder. Then, with noised input, the unsupervised Greedy layer-wise training algorithm is used to train each layer in turn for more robust expressing, characteristics are obtained in supervised learning by Back Propagation (BP neural network, and the whole network is optimized by error back propagation. Finally, Gaofen-1 satellite (GF-1 remote sensing data are used for evaluation, and the total accuracy and kappa accuracy reach 95.7% and 0.955, respectively, which are higher than that of the Support Vector Machine and Back Propagation neural network. The experiment results show that the proposed method can effectively improve the accuracy of remote sensing image classification.

Financial Network Systemic Risk Contributions

NARCIS (Netherlands)

Hautsch, N.; Schaumburg, J.; Schienle, M.

2015-01-01

We propose the realized systemic risk beta as a measure of financial companies' contribution to systemic risk, given network interdependence between firms' tail risk exposures. Conditional on statistically pre-identified network spillover effects and market and balance sheet information, we define

Signal-regulated systems and networks

CSIR Research Space (South Africa)

Van Zyl, TL

2010-07-01

Full Text Available The article presents the use of signal regulatory networks (SRNs), a biologically inspired model based on gene regulatory networks. SRNs are a way of understanding a class of self-organizing IT systems, signal-regulated systems (SRSs). This article...

Cluster-based single-sink wireless sensor networks and passive optical network converged network incorporating sideband modulation schemes

Science.gov (United States)

Kumar, Love; Sharma, Vishal; Singh, Amarpal

2018-02-01

Wireless sensor networks have tremendous applications, such as civil, military, and environmental monitoring. In most of the applications, sensor data are required to be propagated over the internet/core networks, which result in backhaul setback. Subsequently, there is a necessity to backhaul the sensed information of such networks together with prolonging of the transmission link. Passive optical network (PON) is next-generation access technology emerging as a potential candidate for convergence of the sensed data to the core system. Earlier, the work with single-optical line terminal-PON was demonstrated and investigated merely analytically. This work is an attempt to demonstrate a practical model of a bidirectional single-sink wireless sensor network-PON converged network in which the collected data from cluster heads are transmitted over PON networks. Further, modeled converged structure has been investigated under the influence of double, single, and tandem sideband modulation schemes incorporating a corresponding phase-delay to the sensor data entities that have been overlooked in the past. The outcome illustrates the successful fusion of the sensor data entities over PON with acceptable bit error rate and signal to noise ratio serving as a potential development in the sphere of such converged networks. It has also been revealed that the data entities treated with tandem side band modulation scheme help in improving the performance of the converged structure. Additionally, analysis for uplink transmission reported with queue theory in terms of time cycle, average time delay, data packet generation, and bandwidth utilization. An analytical analysis of proposed converged network shows that average time delay for data packet transmission is less as compared with time cycle delay.

Design of Compressed Sensing Algorithm for Coal Mine IoT Moving Measurement Data Based on a Multi-Hop Network and Total Variation

Directory of Open Access Journals (Sweden)

Gang Wang

2018-05-01

Full Text Available As the application of a coal mine Internet of Things (IoT, mobile measurement devices, such as intelligent mine lamps, cause moving measurement data to be increased. How to transmit these large amounts of mobile measurement data effectively has become an urgent problem. This paper presents a compressed sensing algorithm for the large amount of coal mine IoT moving measurement data based on a multi-hop network and total variation. By taking gas data in mobile measurement data as an example, two network models for the transmission of gas data flow, namely single-hop and multi-hop transmission modes, are investigated in depth, and a gas data compressed sensing collection model is built based on a multi-hop network. To utilize the sparse characteristics of gas data, the concept of total variation is introduced and a high-efficiency gas data compression and reconstruction method based on Total Variation Sparsity based on Multi-Hop (TVS-MH is proposed. According to the simulation results, by using the proposed method, the moving measurement data flow from an underground distributed mobile network can be acquired and transmitted efficiently.

Design of Compressed Sensing Algorithm for Coal Mine IoT Moving Measurement Data Based on a Multi-Hop Network and Total Variation.

Science.gov (United States)

Wang, Gang; Zhao, Zhikai; Ning, Yongjie

2018-05-28

As the application of a coal mine Internet of Things (IoT), mobile measurement devices, such as intelligent mine lamps, cause moving measurement data to be increased. How to transmit these large amounts of mobile measurement data effectively has become an urgent problem. This paper presents a compressed sensing algorithm for the large amount of coal mine IoT moving measurement data based on a multi-hop network and total variation. By taking gas data in mobile measurement data as an example, two network models for the transmission of gas data flow, namely single-hop and multi-hop transmission modes, are investigated in depth, and a gas data compressed sensing collection model is built based on a multi-hop network. To utilize the sparse characteristics of gas data, the concept of total variation is introduced and a high-efficiency gas data compression and reconstruction method based on Total Variation Sparsity based on Multi-Hop (TVS-MH) is proposed. According to the simulation results, by using the proposed method, the moving measurement data flow from an underground distributed mobile network can be acquired and transmitted efficiently.

Hybrid Arrays for Chemical Sensing

Science.gov (United States)

Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

In recent years, multisensory approaches to environment monitoring for chemical detection as well as other forms of situational awareness have become increasingly popular. A hybrid sensor is a multimodal system that incorporates several sensing elements and thus produces data that are multivariate in nature and may be significantly increased in complexity compared to data provided by single-sensor systems. Though a hybrid sensor is itself an array, hybrid sensors are often organized into more complex sensing systems through an assortment of network topologies. Part of the reason for the shift to hybrid sensors is due to advancements in sensor technology and computational power available for processing larger amounts of data. There is also ample evidence to support the claim that a multivariate analytical approach is generally superior to univariate measurements because it provides additional redundant and complementary information (Hall, D. L.; Linas, J., Eds., Handbook of Multisensor Data Fusion, CRC, Boca Raton, FL, 2001). However, the benefits of a multisensory approach are not automatically achieved. Interpretation of data from hybrid arrays of sensors requires the analyst to develop an application-specific methodology to optimally fuse the disparate sources of data generated by the hybrid array into useful information characterizing the sample or environment being observed. Consequently, multivariate data analysis techniques such as those employed in the field of chemometrics have become more important in analyzing sensor array data. Depending on the nature of the acquired data, a number of chemometric algorithms may prove useful in the analysis and interpretation of data from hybrid sensor arrays. It is important to note, however, that the challenges posed by the analysis of hybrid sensor array data are not unique to the field of chemical sensing. Applications in electrical and process engineering, remote sensing, medicine, and of course, artificial

Tenet: An Architecture for Tiered Embedded Networks

OpenAIRE

Ramesh Govindan; Eddie Kohler; Deborah Estrin; Fang Bian; Krishna Chintalapudi; Om Gnawali; Sumit Rangwala; Ramakrishna Gummadi; Thanos Stathopoulos

2005-01-01

Future large-scale sensor network deployments will be tiered, with the motes providing dense sensing and a higher tier of 32-bit master nodes with more powerful radios providing increased overall network capacity. In this paper, we describe a functional architecture for wireless sensor networks that leverages this structure to simplify the overall system. Our Tenet architecture has the nice property that the mote-layer software is generic and reusable, and all application functionality reside...

Remote control of Alfven eigenmode sensing system on the large helical device

International Nuclear Information System (INIS)

Ito, T.; Toi, K.; Matsunaga, G.

2008-01-01

An active sensing system of Alfven eigenmodes (AEs), which consists of a set of toroidally distributed loop antennas and several bi-polar power supplies, has been developed in the large helical device (LHD). The power supplies are controlled with a function generator receiving a control pattern of antenna current and the driving frequency from a personal computer (PC) in an LHD control room. This sensing method is based on the analysis of the frequency dependence of a transfer function that is derived by the ratio of the Fourier-transformed magnetic probe signal ('plasma response') to antenna current one ('exciter signal'). Typically, the driving frequency of the antenna current is swept linearly in time from 10 kHz to 500 kHz for 2 s in the LHD experiment. The sensing system is fully controlled through Ethernet LAN with easy extendable GUI. Configuration and control scheme of the active sensing system of AEs are presented in this paper. An initial result of the system operation is also described

Context Sensing System Analysis for Privacy Preservation Based on Game Theory.

Science.gov (United States)

Wang, Shengling; Li, Luyun; Sun, Weiman; Guo, Junqi; Bie, Rongfang; Lin, Kai

2017-02-10

In a context sensing system in which a sensor-equipped mobile phone runs an unreliable context-aware application, the application can infer the user's contexts, based on which it provides personalized services. However, the application may sell the user's contexts to some malicious adversaries to earn extra profits, which will hinder its widespread use. In the real world, the actions of the user, the application and the adversary in the context sensing system affect each other, so that their payoffs are constrained mutually. To figure out under which conditions they behave well (the user releases, the application does not leak and the adversary does not retrieve the context), we take advantage of game theory to analyze the context sensing system. We use the extensive form game and the repeated game, respectively, to analyze two typical scenarios, single interaction and multiple interaction among three players, from which Nash equilibriums and cooperation conditions are obtained. Our results show that the reputation mechanism for the context-sensing system in the former scenario is crucial to privacy preservation, so is the extent to which the participants are concerned about future payoffs in the latter one.

Exploring network organization in practice

DEFF Research Database (Denmark)

Hu, Yimei; Sørensen, Olav Jull

Constructing a network organization for global R&D is presented as a common sense practice in existing literature. However, there are still queries about the network organization, such as the persistence of hierarchies which make a network organization merely a “bureaucracy-lite” organization....... Furthermore, in practice, we rarely see radical organizational change towards a network organization that adopts an internal market. The co-existence of market, hierarchy and network triggered research interest. A multiple case study of three transnational corporations’ global R&D organization shows...... that there are different logical considerations when designing a network organization to facilitate innovation. I identify three types of network organizations: market-led, directed and culture-led network organizations. Different types of network organizations show that organizations are dual and even ternary systems...

Asynchronous control for networked systems

CERN Document Server

Rubio, Francisco; Bencomo, Sebastián

2015-01-01

This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

Unmanned aerial systems for photogrammetry and remote sensing: A review

OpenAIRE

Colomina, Ismael; Molina, Pere

2014-01-01

We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last...

Operating systems and network protocols for wireless sensor networks.

Science.gov (United States)

Dutta, Prabal; Dunkels, Adam

2012-01-13

Sensor network protocols exist to satisfy the communication needs of diverse applications, including data collection, event detection, target tracking and control. Network protocols to enable these services are constrained by the extreme resource scarcity of sensor nodes-including energy, computing, communications and storage-which must be carefully managed and multiplexed by the operating system. These challenges have led to new protocols and operating systems that are efficient in their energy consumption, careful in their computational needs and miserly in their memory footprints, all while discovering neighbours, forming networks, delivering data and correcting failures.

The APS control system network upgrade

International Nuclear Information System (INIS)

Sidorowicz, K. v.; Leibfritz, D.; McDowell, W. P.

1999-01-01

When it was installed,the Advanced Photon Source (APS) control system network was at the state-of-the-art. Different aspects of the system have been reported at previous meetings [1,2]. As loads on the controls network have increased due to newer and faster workstations and front-end computers, we have found performance of the system declining and have implemented an upgraded network. There have been dramatic advances in networking hardware in the last several years. The upgraded APS controls network replaces the original FDDI backbone and shared Ethernet hubs with redundant gigabit uplinks and fully switched 10/100 Ethernet switches with backplane fabrics in excess of 20 Gbits/s (Gbps). The central collapsed backbone FDDI concentrator has been replaced with a Gigabit Ethernet switch with greater than 30 Gbps backplane fabric. Full redundancy of the system has been maintained. This paper will discuss this upgrade and include performance data and performance comparisons with the original network

Scalability Issues for Remote Sensing Infrastructure: A Case Study

Directory of Open Access Journals (Sweden)

Yang Liu

2017-04-01

Full Text Available For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging. Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system’s memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.

Filtering and control of wireless networked systems

CERN Document Server

Zhang, Dan; Yu, Li

2017-01-01

This self-contained book, written by leading experts, offers a cutting-edge, in-depth overview of the filtering and control of wireless networked systems. It addresses the energy constraint and filter/controller gain variation problems, and presents both the centralized and the distributed solutions. The first two chapters provide an introduction to networked control systems and basic information on system analysis. Chapters (3–6) then discuss the centralized filtering of wireless networked systems, presenting different approaches to deal with energy efficiency and filter/controller gain variation problems. The next part (chapters 7–10) explores the distributed filtering of wireless networked systems, addressing the main problems of energy constraint and filter gain variation. The final part (chapters 11–14) focuses on the distributed control of wireless networked systems. networked systems for communication and control applications, the bo...

Social sensing building reliable systems on unreliable data

CERN Document Server

Wang, Dong; Kaplan, Lance

2015-01-01

Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individu

Opportunistic Relay Selection in Multicast Relay Networks using Compressive Sensing

KAUST Repository

Elkhalil, Khalil

2014-12-01

Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. However, for relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. In this paper, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback. Following that, the CSI of the selected relays is estimated using linear minimum mean square error estimation. To minimize the effect of noise on the fed back CSI, we introduce a back-off strategy that optimally backs-off on the noisy estimated CSI. For a fixed group size, we provide closed form expressions for the scaling law of the maximum equivalent SNR for both Decode and Forward (DF) and Amplify and Forward (AF) cases. Numerical results show that the proposed algorithm drastically reduces the feedback air-time and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback channels.

The enhanced alcohol sensing response of multiwalled carbon nanotube networks induced by alkyl diamine treatment

Czech Academy of Sciences Publication Activity Database

Benlikaya, R.; Slobodian, P.; Říha, Pavel; Olejník, R.

2014-01-01

Roč. 201, October (2014), s. 122-130 ISSN 0925-4005 R&D Projects: GA MŠk(CZ) CZ.1.07/2.3.00/20.0104 Grant - others:UTB Zlín(CZ) IGA/FT/2013/018; GA MŠk(CZ) ED2.1.00/03.0111 Institutional research plan: CEZ:AV0Z20600510 Institutional support: RVO:67985874 Keywords : carbon nanotubes * multiwalled carbon nanotube networks * vapor sensing * linear alcohols * alkyl diamine treatment Subject RIV: BK - Fluid Dynamics Impact factor: 4.097, year: 2014

The enhanced alcohol sensing response of multiwalled carbon nanotube networks induced by alkyl diamine treatment

Czech Academy of Sciences Publication Activity Database

Benlikaya, R.; Slobodian, P.; Říha, Pavel; Olejník, R.

2014-01-01

Roč. 201, October (2014), s. 122-130 ISSN 0925-4005 R&D Projects: GA MŠk(CZ) CZ.1.07/2.3.00/20.0104 Grant - others:UTB Zlín(CZ) IGA/FT/2013/018; GA MŠk(CZ) ED2.1.00/03.0111 Institutional research plan: CEZ:AV0Z20600510 Institutional support: RVO:67985874 Keywords : carbon nanotubes * multiwalled carbon nanotube networks * vapor sensing * linear alcohol s * alkyl diamine treatment Subject RIV: BK - Fluid Dynamics Impact factor: 4.097, year: 2014

Identifying Chaotic FitzHugh–Nagumo Neurons Using Compressive Sensing

Directory of Open Access Journals (Sweden)

Ri-Qi Su

2014-07-01

Full Text Available We develop a completely data-driven approach to reconstructing coupled neuronal networks that contain a small subset of chaotic neurons. Such chaotic elements can be the result of parameter shift in their individual dynamical systems and may lead to abnormal functions of the network. To accurately identify the chaotic neurons may thus be necessary and important, for example, applying appropriate controls to bring the network to a normal state. However, due to couplings among the nodes, the measured time series, even from non-chaotic neurons, would appear random, rendering inapplicable traditional nonlinear time-series analysis, such as the delay-coordinate embedding method, which yields information about the global dynamics of the entire network. Our method is based on compressive sensing. In particular, we demonstrate that identifying chaotic elements can be formulated as a general problem of reconstructing the nodal dynamical systems, network connections and all coupling functions, as well as their weights. The working and efficiency of the method are illustrated by using networks of non-identical FitzHugh–Nagumo neurons with randomly-distributed coupling weights.

Design principles in biological networks

Science.gov (United States)

Goyal, Sidhartha

Much of biology emerges from networks of interactions. Even in a single bacterium such as Escherichia coli, there are hundreds of coexisting gene and protein networks. Although biological networks are the outcome of evolution, various physical and biological constraints limit their functional capacity. The focus of this thesis is to understand how functional constraints such as optimal growth in mircoorganisms and information flow in signaling pathways shape the metabolic network of bacterium E. coli and the quorum sensing network of marine bacterium Vibrio harveyi, respectively. Metabolic networks convert basic elemental sources into complex building-blocks eventually leading to cell's growth. Therefore, typically, metabolic pathways are often coupled both by the use of a common substrate and by stoichiometric utilization of their products for cell growth. We showed that such a coupled network with product-feedback inhibition may exhibit limit-cycle oscillations which arise via a Hopf bifurcation. Furthermore, we analyzed several representative metabolic modules and find that, in all cases, simple product-feedback inhibition allows nearly optimal growth, in agreement with the predicted growth-rate by the flux-balance analysis (FBA). Bacteria have fascinating and diverse social lives. They display coordinated group behaviors regulated by quorum sensing (QS) systems. The QS circuit of V. harveyi integrates and funnels different ecological information through a common phosphorelay cascade to a set of small regulatory RNAs (sRNAs) that enables collective behavior. We analyzed the signaling properties and information flow in the QS circuit, which provides a model for information flow in signaling networks more generally. A comparative study of post-transcriptional and conventional transcriptional regulation suggest a niche for sRNAs in allowing cells to transition quickly yet reliably between distinct states. Furthermore, we develop a new framework for analyzing signal

RECOMMENDER SYSTEMS IN SOCIAL NETWORKS

Directory of Open Access Journals (Sweden)

Cleomar Valois Batista Jr

2011-12-01

Full Text Available The continued and diversified growth of social networks has changed the way in which users interact with them. With these changes, what once was limited to social contact is now used for exchanging ideas and opinions, creating the need for new features. Users have so much information at their fingertips that they are unable to process it by themselves; hence, the need to develop new tools. Recommender systems were developed to address this need and many techniques were used for different approaches to the problem. To make relevant recommendations, these systems use large sets of data, not taking the social network of the user into consideration. Developing a recommender system that takes into account the social network of the user is another way of tackling the problem. The purpose of this project is to use the theory of six degrees of separation (Watts 2003 amongst users of a social network to enhance existing recommender systems.

System-Level Design Methodologies for Networked Multiprocessor Systems-on-Chip

DEFF Research Database (Denmark)

Virk, Kashif Munir

2008-01-01

is the first such attempt in the published literature. The second part of the thesis deals with the issues related to the development of system-level design methodologies for networked multiprocessor systems-on-chip at various levels of design abstraction with special focus on the modeling and design...... at the system-level. The multiprocessor modeling framework is then extended to include models of networked multiprocessor systems-on-chip which is then employed to model wireless sensor networks both at the sensor node level as well as the wireless network level. In the third and the final part, the thesis...... to the transaction-level model. The thesis, as a whole makes contributions by describing a design methodology for networked multiprocessor embedded systems at three layers of abstraction from system-level through transaction-level to the cycle accurate level as well as demonstrating it practically by implementing...

Endogenous network of firms and systemic risk

Science.gov (United States)

Ma, Qianting; He, Jianmin; Li, Shouwei

2018-02-01

We construct an endogenous network characterized by commercial credit relationships connecting the upstream and downstream firms. Simulation results indicate that the endogenous network model displays a scale-free property which exists in real-world firm systems. In terms of the network structure, with the expansion of the scale of network nodes, the systemic risk increases significantly, while the heterogeneities of network nodes have no effect on systemic risk. As for firm micro-behaviors, including the selection range of trading partners, actual output, labor requirement, price of intermediate products and employee salaries, increase of all these parameters will lead to higher systemic risk.

Next Generation RFID-Based Medical Service Management System Architecture in Wireless Sensor Network

Science.gov (United States)

Tolentino, Randy S.; Lee, Kijeong; Kim, Yong-Tae; Park, Gil-Cheol

Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide unlimited future potentials most especially in healthcare systems. RFID is used to detect presence and location of objects while WSN is used to sense and monitor the environment. Integrating RFID with WSN not only provides identity and location of an object but also provides information regarding the condition of the object carrying the sensors enabled RFID tag. However, there isn't any flexible and robust communication infrastructure to integrate these devices into an emergency care setting. An efficient wireless communication substrate for medical devices that addresses ad hoc or fixed network formation, naming and discovery, transmission efficiency of data, data security and authentication, as well as filtration and aggregation of vital sign data need to be study and analyze. This paper proposed an efficient next generation architecture for RFID-based medical service management system in WSN that possesses the essential elements of each future medical application that are integrated with existing medical practices and technologies in real-time, remote monitoring, in giving medication, and patient status tracking assisted by embedded wearable wireless sensors which are integrated in wireless sensor network.

Artificial Neural Network Analysis System

Science.gov (United States)

2001-02-27

Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

Focal-Plane Sensing-Processing: A Power-Efficient Approach for the Implementation of Privacy-Aware Networked Visual Sensors

Directory of Open Access Journals (Sweden)

Jorge Fernández-Berni

2014-08-01

Full Text Available The capture, processing and distribution of visual information is one of the major challenges for the paradigm of the Internet of Things. Privacy emerges as a fundamental barrier to overcome. The idea of networked image sensors pervasively collecting data generates social rejection in the face of sensitive information being tampered by hackers or misused by legitimate users. Power consumption also constitutes a crucial aspect. Images contain a massive amount of data to be processed under strict timing requirements, demanding high-performance vision systems. In this paper, we describe a hardware-based strategy to concurrently address these two key issues. By conveying processing capabilities to the focal plane in addition to sensing, we can implement privacy protection measures just at the point where sensitive data are generated. Furthermore, such measures can be tailored for efficiently reducing the computational load of subsequent processing stages. As a proof of concept, a full-custom QVGA vision sensor chip is presented. It incorporates a mixed-signal focal-plane sensing-processing array providing programmable pixelation of multiple image regions in parallel. In addition to this functionality, the sensor exploits reconfigurability to implement other processing primitives, namely block-wise dynamic range adaptation, integral image computation and multi-resolution filtering. The proposed circuitry is also suitable to build a granular space, becoming the raw material for subsequent feature extraction and recognition of categorized objects.

Focal-plane sensing-processing: a power-efficient approach for the implementation of privacy-aware networked visual sensors.