A reverse localization scheme for underwater acoustic sensor networks.

PubMed

Moradi, Marjan; Rezazadeh, Javad; Ismail, Abdul Samad

2012-01-01

Underwater Wireless Sensor Networks (UWSNs) provide new opportunities to observe and predict the behavior of aquatic environments. In some applications like target tracking or disaster prevention, sensed data is meaningless without location information. In this paper, we propose a novel 3D centralized, localization scheme for mobile underwater wireless sensor network, named Reverse Localization Scheme or RLS in short. RLS is an event-driven localization method triggered by detector sensors for launching localization process. RLS is suitable for surveillance applications that require very fast reactions to events and could report the location of the occurrence. In this method, mobile sensor nodes report the event toward the surface anchors as soon as they detect it. They do not require waiting to receive location information from anchors. Simulation results confirm that the proposed scheme improves the energy efficiency and reduces significantly localization response time with a proper level of accuracy in terms of mobility model of water currents. Major contributions of this method lie on reducing the numbers of message exchange for localization, saving the energy and decreasing the average localization response time.

Distributed Data-aggregation Consensus for Sensor Networks: Global Connectivity Assessment through Local Data Exchange

DTIC Science & Technology

2014-08-01

Distributed data-aggregation consensus for sensor networks Global connectivity assessment through local data exchange A. Ajorlou Concordia...k − i) i = 1, 2, ..., k − 1 3 Acoustic Channel Characterization *! f

Monitoring industrial facilities using principles of integration of fiber classifier and local sensor networks

NASA Astrophysics Data System (ADS)

Korotaev, Valery V.; Denisov, Victor M.; Rodrigues, Joel J. P. C.; Serikova, Mariya G.; Timofeev, Andrey V.

2015-05-01

The paper deals with the creation of integrated monitoring systems. They combine fiber-optic classifiers and local sensor networks. These systems allow for the monitoring of complex industrial objects. Together with adjacent natural objects, they form the so-called geotechnical systems. An integrated monitoring system may include one or more spatially continuous fiber-optic classifiers based on optic fiber and one or more arrays of discrete measurement sensors, which are usually combined in sensor networks. Fiber-optic classifiers are already widely used for the control of hazardous extended objects (oil and gas pipelines, railways, high-rise buildings, etc.). To monitor local objects, discrete measurement sensors are generally used (temperature, pressure, inclinometers, strain gauges, accelerometers, sensors measuring the composition of impurities in the air, and many others). However, monitoring complex geotechnical systems require a simultaneous use of continuous spatially distributed sensors based on fiber-optic cable and connected local discrete sensors networks. In fact, we are talking about integration of the two monitoring methods. This combination provides an additional way to create intelligent monitoring systems. Modes of operation of intelligent systems can automatically adapt to changing environmental conditions. For this purpose, context data received from one sensor (e.g., optical channel) may be used to change modes of work of other sensors within the same monitoring system. This work also presents experimental results of the prototype of the integrated monitoring system.

Wireless Cooperative Networks: Self-Configuration and Optimization

DTIC Science & Technology

2011-09-09

TERMS wireless sensor networks , wireless cooperative networks, resource optimization, ultra-wideband, localization, ranging 16. SECURITY...Communications We consider two prevalent relay protocols for wireless sensor networks : decode-and-forward (DF) and amplify-and-forward (AF). To... sensor networks where each node may have its own sensing data to transmit, since they can maximally conserve energy while helping others as relays

Parametric Loop Division for 3D Localization in Wireless Sensor Networks

PubMed Central

Ahmad, Tanveer

2017-01-01

Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m. PMID:28737714

Fiber-connected position localization sensor networks

NASA Astrophysics Data System (ADS)

Pan, Shilong; Zhu, Dan; Fu, Jianbin; Yao, Tingfeng

2014-11-01

Position localization has drawn great attention due to its wide applications in radars, sonars, electronic warfare, wireless communications and so on. Photonic approaches to realize position localization can achieve high-resolution, which also provides the possibility to move the signal processing from each sensor node to the central station, thanks to the low loss, immunity to electromagnetic interference (EMI) and broad bandwidth brought by the photonic technologies. In this paper, we present a review on the recent works of position localization based on photonic technologies. A fiber-connected ultra-wideband (UWB) sensor network using optical time-division multiplexing (OTDM) is proposed to realize high-resolution localization and moving the signal processing to the central station. A 3.9-cm high spatial resolution is achieved. A wavelength-division multiplexed (WDM) fiber-connected sensor network is also demonstrated to realize location which is independent of the received signal format.

Event Detection in Aerospace Systems using Centralized Sensor Networks: A Comparative Study of Several Methodologies

NASA Technical Reports Server (NTRS)

Mehr, Ali Farhang; Sauvageon, Julien; Agogino, Alice M.; Tumer, Irem Y.

2006-01-01

Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.

Cross-coherent vector sensor processing for spatially distributed glider networks.

PubMed

Nichols, Brendan; Sabra, Karim G

2015-09-01

Autonomous underwater gliders fitted with vector sensors can be used as a spatially distributed sensor array to passively locate underwater sources. However, to date, the positional accuracy required for robust array processing (especially coherent processing) is not achievable using dead-reckoning while the gliders remain submerged. To obtain such accuracy, the gliders can be temporarily surfaced to allow for global positioning system contact, but the acoustically active sea surface introduces locally additional sensor noise. This letter demonstrates that cross-coherent array processing, which inherently mitigates the effects of local noise, outperforms traditional incoherent processing source localization methods for this spatially distributed vector sensor network.

Collaborative Localization Algorithms for Wireless Sensor Networks with Reduced Localization Error

PubMed Central

Sahoo, Prasan Kumar; Hwang, I-Shyan

2011-01-01

Localization is an important research issue in Wireless Sensor Networks (WSNs). Though Global Positioning System (GPS) can be used to locate the position of the sensors, unfortunately it is limited to outdoor applications and is costly and power consuming. In order to find location of sensor nodes without help of GPS, collaboration among nodes is highly essential so that localization can be accomplished efficiently. In this paper, novel localization algorithms are proposed to find out possible location information of the normal nodes in a collaborative manner for an outdoor environment with help of few beacons and anchor nodes. In our localization scheme, at most three beacon nodes should be collaborated to find out the accurate location information of any normal node. Besides, analytical methods are designed to calculate and reduce the localization error using probability distribution function. Performance evaluation of our algorithm shows that there is a tradeoff between deployed number of beacon nodes and localization error, and average localization time of the network can be increased with increase in the number of normal nodes deployed over a region. PMID:22163738

Biology Inspired Approach for Communal Behavior in Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2006-01-01

Research in wireless sensor network technology has exploded in the last decade. Promises of complex and ubiquitous control of the physical environment by these networks open avenues for new kinds of science and business. Due to the small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors working in concert. Although the reduction in size has been phenomenal it results in severe limitations on the computing, communicating, and power capabilities of these devices. Under these constraints, research efforts have concentrated on developing techniques for performing relatively simple tasks with minimal energy expense assuming some form of centralized control. Unfortunately, centralized control does not scale to massive size networks and execution of simple tasks in sparsely populated networks will not lead to the sophisticated applications predicted. These must be enabled by new techniques dependent on local and autonomous cooperation between sensors to effect global functions. As a step in that direction, in this work we detail a technique whereby a large population of sensors can attain a global goal using only local information and by making only local decisions without any form of centralized control.

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Unmanned Ground Vehicle Navigation and Coverage Hole Patching in Wireless Sensor Networks

ERIC Educational Resources Information Center

Zhang, Guyu

2013-01-01

This dissertation presents a study of an Unmanned Ground Vehicle (UGV) navigation and coverage hole patching in coordinate-free and localization-free Wireless Sensor Networks (WSNs). Navigation and coverage maintenance are related problems since coverage hole patching requires effective navigation in the sensor network environment. A…

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

Experimental damage detection of wind turbine blade using thin film sensor array

NASA Astrophysics Data System (ADS)

Downey, Austin; Laflamme, Simon; Ubertini, Filippo; Sarkar, Partha

2017-04-01

Damage detection of wind turbine blades is difficult due to their large sizes and complex geometries. Additionally, economic restraints limit the viability of high-cost monitoring methods. While it is possible to monitor certain global signatures through modal analysis, obtaining useful measurements over a blade's surface using off-the-shelf sensing technologies is difficult and typically not economical. A solution is to deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel large-area electronic sensor measuring strain over very large surfaces. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a hybrid dense sensor network of soft elastomeric capacitors to detect, localize, and quantify damage, and resistive strain gauges to augment such dense sensor network with high accuracy data at key locations. The proposed hybrid dense sensor network is installed inside a wind turbine blade model and tested in a wind tunnel to simulate an operational environment. Damage in the form of changing boundary conditions is introduced into the monitored section of the blade. Results demonstrate the ability of the hybrid dense sensor network, and associated algorithms, to detect, localize, and quantify damage.

LWT Based Sensor Node Signal Processing in Vehicle Surveillance Distributed Sensor Network

NASA Astrophysics Data System (ADS)

Cha, Daehyun; Hwang, Chansik

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

Role of Vascular Networks in Extending Glucose Sensor Function: Impact of Angiogenesis and Lymphangiogenesis on Continuous Glucose Monitoring in vivo

PubMed Central

Klueh, Ulrike; Antar, Omar; Qiao, Yi; Kreutzer, Donald L.

2014-01-01

The concept of increased blood vessel (BV) density proximal to glucose sensors implanted in the interstitial tissue increases the accuracy and lifespan of sensors is accepted, despite limited existing experimental data. Interestingly, there is no previous data or even conjecture in the literature on the role of lymphatic vessels (LV) alone, or in combination with BV, in enhancing continuous glucose monitoring (CGM) in vivo. To investigate the impact of inducing vascular networks (BV and LV) at sites of glucose sensor implantation, we utilized adenovirus based local gene therapy of vascular endothelial cell growth factor-A (VEGF-A) to induce vessels at sensor implantation sites. The results of these studies demonstrated that 1) VEGF-A based local gene therapy increases vascular networks (blood vessels and lymphatic vessels) at sites of glucose sensor implantation; and 2) this local increase of vascular networks enhances glucose sensor function in vivo from 7 days to greater than 28 days post sensor implantation. This data provides “proof of concept” for the effective usage of local angiogenic factor (AF) gene therapy in mammalian models in an effort to extend CGM in vivo. It also supports the practice of a variety of viral and non-viral vectors as well as gene products (e.g. anti-inflammatory and anti-fibrosis genes) to engineer “implant friendly tissues” for the usage with implantable glucose sensors as well as other implantable devices. PMID:24243850

Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.

Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

PubMed Central

Nguyen, Thu L. N.; Shin, Yoan

2016-01-01

Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378

Energy-aware scheduling of surveillance in wireless multimedia sensor networks.

PubMed

Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao

2010-01-01

Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.

Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion

PubMed Central

Pescaru, Dan; Curiac, Daniel-Ioan

2014-01-01

Distributed sensing, computing and communication capabilities of wireless sensor networks require, in most situations, an efficient node localization procedure. In the case of random deployments in harsh or hostile environments, a general localization process within global coordinates is based on a set of anchor nodes able to determine their own position using GPS receivers. In this paper we propose another anchor node localization technique that can be used when GPS devices cannot accomplish their mission or are considered to be too expensive. This novel technique is based on the fusion of video and compass data acquired by the anchor nodes and is especially suitable for video- or multimedia-based wireless sensor networks. For these types of wireless networks the presence of video cameras is intrinsic, while the presence of digital compasses is also required for identifying the cameras' orientations. PMID:24594614

Three-dimensional ocean sensor networks: A survey

NASA Astrophysics Data System (ADS)

Wang, Yu; Liu, Yingjian; Guo, Zhongwen

2012-12-01

The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research, oceanography, ocean monitoring, offshore exploration, and defense or homeland security. Ocean sensor networks are generally formed with various ocean sensors, autonomous underwater vehicles, surface stations, and research vessels. To make ocean sensor network applications viable, efficient communication among all devices and components is crucial. Due to the unique characteristics of underwater acoustic channels and the complex deployment environment in three dimensional (3D) ocean spaces, new efficient and reliable communication and networking protocols are needed in design of ocean sensor networks. In this paper, we aim to provide an overview of the most recent advances in network design principles for 3D ocean sensor networks, with focuses on deployment, localization, topology design, and position-based routing in 3D ocean spaces.

Method and apparatus of assessing down-hole drilling conditions

DOEpatents

Hall, David R [Provo, UT; Pixton, David S [Lehl, UT; Johnson, Monte L [Orem, UT; Bartholomew, David B [Springville, UT; Fox, Joe [Spanish Fork, UT

2007-04-24

A method and apparatus for use in assessing down-hole drilling conditions are disclosed. The apparatus includes a drill string, a plurality of sensors, a computing device, and a down-hole network. The sensors are distributed along the length of the drill string and are capable of sensing localized down-hole conditions while drilling. The computing device is coupled to at least one sensor of the plurality of sensors. The data is transmitted from the sensors to the computing device over the down-hole network. The computing device analyzes data output by the sensors and representative of the sensed localized conditions to assess the down-hole drilling conditions. The method includes sensing localized drilling conditions at a plurality of points distributed along the length of a drill string during drilling operations; transmitting data representative of the sensed localized conditions to a predetermined location; and analyzing the transmitted data to assess the down-hole drilling conditions.

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks.

PubMed

Chen, Pengpeng; Ma, Honglu; Gao, Shouwan; Huang, Yan

2015-11-24

Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes' positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes' positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes' relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks.

Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

PubMed Central

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-01-01

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions. PMID:25658390

Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

PubMed

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-02-04

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Real-time stress monitoring of highway bridges with a secured wireless sensor network.

DOT National Transportation Integrated Search

2011-12-01

"This collaborative research aims to develop a real-time stress monitoring system for highway bridges with a secured wireless sensor network. The near term goal is to collect wireless sensor data under different traffic patterns from local highway br...

Localization with a mobile beacon in underwater acoustic sensor networks.

PubMed

Lee, Sangho; Kim, Kiseon

2012-01-01

Localization is one of the most important issues associated with underwater acoustic sensor networks, especially when sensor nodes are randomly deployed. Given that it is difficult to deploy beacon nodes at predetermined locations, localization schemes with a mobile beacon on the sea surface or along the planned path are inherently convenient, accurate, and energy-efficient. In this paper, we propose a new range-free Localization with a Mobile Beacon (LoMoB). The mobile beacon periodically broadcasts a beacon message containing its location. Sensor nodes are individually localized by passively receiving the beacon messages without inter-node communications. For location estimation, a set of potential locations are obtained as candidates for a node's location and then the node's location is determined through the weighted mean of all the potential locations with the weights computed based on residuals.

Localization with a Mobile Beacon in Underwater Acoustic Sensor Networks

PubMed Central

Lee, Sangho; Kim, Kiseon

2012-01-01

Localization is one of the most important issues associated with underwater acoustic sensor networks, especially when sensor nodes are randomly deployed. Given that it is difficult to deploy beacon nodes at predetermined locations, localization schemes with a mobile beacon on the sea surface or along the planned path are inherently convenient, accurate, and energy-efficient. In this paper, we propose a new range-free Localization with a Mobile Beacon (LoMoB). The mobile beacon periodically broadcasts a beacon message containing its location. Sensor nodes are individually localized by passively receiving the beacon messages without inter-node communications. For location estimation, a set of potential locations are obtained as candidates for a node's location and then the node's location is determined through the weighted mean of all the potential locations with the weights computed based on residuals. PMID:22778597

Performance Evaluation of Localization Accuracy for a Log-Normal Shadow Fading Wireless Sensor Network under Physical Barrier Attacks

PubMed Central

Abdulqader Hussein, Ahmed; Rahman, Tharek A.; Leow, Chee Yen

2015-01-01

Localization is an apparent aspect of a wireless sensor network, which is the focus of much interesting research. One of the severe conditions that needs to be taken into consideration is localizing a mobile target through a dispersed sensor network in the presence of physical barrier attacks. These attacks confuse the localization process and cause location estimation errors. Range-based methods, like the received signal strength indication (RSSI), face the major influence of this kind of attack. This paper proposes a solution based on a combination of multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL), including the fingerprint matching technique and lateration, to provide a robust and accurate localization technique. In addition, this paper proposes a grid coloring algorithm to detect the signal hole map in the network, which refers to the attack-prone regions, in order to carry out corrective actions. The simulation results show the enhancement and robustness of RSS localization performance in the face of log normal shadow fading effects, besides the presence of physical barrier attacks, through detecting, filtering and eliminating the effect of these attacks. PMID:26690159

Performance Evaluation of Localization Accuracy for a Log-Normal Shadow Fading Wireless Sensor Network under Physical Barrier Attacks.

PubMed

Hussein, Ahmed Abdulqader; Rahman, Tharek A; Leow, Chee Yen

2015-12-04

Localization is an apparent aspect of a wireless sensor network, which is the focus of much interesting research. One of the severe conditions that needs to be taken into consideration is localizing a mobile target through a dispersed sensor network in the presence of physical barrier attacks. These attacks confuse the localization process and cause location estimation errors. Range-based methods, like the received signal strength indication (RSSI), face the major influence of this kind of attack. This paper proposes a solution based on a combination of multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL), including the fingerprint matching technique and lateration, to provide a robust and accurate localization technique. In addition, this paper proposes a grid coloring algorithm to detect the signal hole map in the network, which refers to the attack-prone regions, in order to carry out corrective actions. The simulation results show the enhancement and robustness of RSS localization performance in the face of log normal shadow fading effects, besides the presence of physical barrier attacks, through detecting, filtering and eliminating the effect of these attacks.

Underwater Sensor Nodes and Networks

PubMed Central

Lloret, Jaime

2013-01-01

Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field. PMID:24013489

GPS-Free Localization Algorithm for Wireless Sensor Networks

PubMed Central

Wang, Lei; Xu, Qingzheng

2010-01-01

Localization is one of the most fundamental problems in wireless sensor networks, since the locations of the sensor nodes are critical to both network operations and most application level tasks. A GPS-free localization scheme for wireless sensor networks is presented in this paper. First, we develop a standardized clustering-based approach for the local coordinate system formation wherein a multiplication factor is introduced to regulate the number of master and slave nodes and the degree of connectivity among master nodes. Second, using homogeneous coordinates, we derive a transformation matrix between two Cartesian coordinate systems to efficiently merge them into a global coordinate system and effectively overcome the flip ambiguity problem. The algorithm operates asynchronously without a centralized controller; and does not require that the location of the sensors be known a priori. A set of parameter-setting guidelines for the proposed algorithm is derived based on a probability model and the energy requirements are also investigated. A simulation analysis on a specific numerical example is conducted to validate the mathematical analytical results. We also compare the performance of the proposed algorithm under a variety multiplication factor, node density and node communication radius scenario. Experiments show that our algorithm outperforms existing mechanisms in terms of accuracy and convergence time. PMID:22219694

Low Complexity Track Initialization and Fusion for Multi-Modal Sensor Networks

DTIC Science & Technology

2012-11-08

feature was demonstrated via the simulations. Aerospace 2011work further documents our investigation of multiple target tracking filters in...bounds that determine how well a sensor network can resolve and localize multiple targets as a function of the operating parameters such as sensor...probability density (PHD) filter for binary measurements using proximity sensors. 15. SUBJECT TERMS proximity sensors, PHD filter, multiple

Adaptive AOA-aided TOA self-positioning for mobile wireless sensor networks.

PubMed

Wen, Chih-Yu; Chan, Fu-Kai

2010-01-01

Location-awareness is crucial and becoming increasingly important to many applications in wireless sensor networks. This paper presents a network-based positioning system and outlines recent work in which we have developed an efficient principled approach to localize a mobile sensor using time of arrival (TOA) and angle of arrival (AOA) information employing multiple seeds in the line-of-sight scenario. By receiving the periodic broadcasts from the seeds, the mobile target sensors can obtain adequate observations and localize themselves automatically. The proposed positioning scheme performs location estimation in three phases: (I) AOA-aided TOA measurement, (II) Geometrical positioning with particle filter, and (III) Adaptive fuzzy control. Based on the distance measurements and the initial position estimate, adaptive fuzzy control scheme is applied to solve the localization adjustment problem. The simulations show that the proposed approach provides adaptive flexibility and robust improvement in position estimation.

A Mobile Anchor Assisted Localization Algorithm Based on Regular Hexagon in Wireless Sensor Networks

PubMed Central

Rodrigues, Joel J. P. C.

2014-01-01

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints of cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use several mobile anchors which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. This paper proposes a mobile anchor assisted localization algorithm based on regular hexagon (MAALRH) in two-dimensional WSNs, which can cover the whole monitoring area with a boundary compensation method. Unknown nodes calculate their positions by using trilateration. We compare the MAALRH with HILBERT, CIRCLES, and S-CURVES algorithms in terms of localization ratio, localization accuracy, and path length. Simulations show that the MAALRH can achieve high localization ratio and localization accuracy when the communication range is not smaller than the trajectory resolution. PMID:25133212

Teaching the Geoweb: Interdisciplinary Undergraduate Research in Wireless Sensor Networks, Web Mapping, and Geospatial Data Management

ERIC Educational Resources Information Center

Abernathy, David

2011-01-01

This article addresses an effort to incorporate wireless sensor networks and the emerging tools of the Geoweb into undergraduate teaching and research at a small liberal arts college. The primary goal of the research was to identify the hardware, software, and skill sets needed to deploy a local sensor network, collect data, and transmit that data…

A Dependable Localization Algorithm for Survivable Belt-Type Sensor Networks.

PubMed

Zhu, Mingqiang; Song, Fei; Xu, Lei; Seo, Jung Taek; You, Ilsun

2017-11-29

As the key element, sensor networks are widely investigated by the Internet of Things (IoT) community. When massive numbers of devices are well connected, malicious attackers may deliberately propagate fake position information to confuse the ordinary users and lower the network survivability in belt-type situation. However, most existing positioning solutions only focus on the algorithm accuracy and do not consider any security aspects. In this paper, we propose a comprehensive scheme for node localization protection, which aims to improve the energy-efficient, reliability and accuracy. To handle the unbalanced resource consumption, a node deployment mechanism is presented to satisfy the energy balancing strategy in resource-constrained scenarios. According to cooperation localization theory and network connection property, the parameter estimation model is established. To achieve reliable estimations and eliminate large errors, an improved localization algorithm is created based on modified average hop distances. In order to further improve the algorithms, the node positioning accuracy is enhanced by using the steepest descent method. The experimental simulations illustrate the performance of new scheme can meet the previous targets. The results also demonstrate that it improves the belt-type sensor networks' survivability, in terms of anti-interference, network energy saving, etc.

Using Hybrid Angle/Distance Information for Distributed Topology Control in Vehicular Sensor Networks

PubMed Central

Huang, Chao-Chi; Chiu, Yang-Hung; Wen, Chih-Yu

2014-01-01

In a vehicular sensor network (VSN), the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs. PMID:25350506

Decentralized cooperative TOA/AOA target tracking for hierarchical wireless sensor networks.

PubMed

Chen, Ying-Chih; Wen, Chih-Yu

2012-11-08

This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processing is conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for the localization task. The proposed energy-efficient tracking algorithm allows each sub-cluster member to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for object position estimation.

Acoustic Source Localization via Time Difference of Arrival Estimation for Distributed Sensor Networks Using Tera-Scale Optical Core Devices

DOE PAGES

Imam, Neena; Barhen, Jacob

2009-01-01

For real-time acoustic source localization applications, one of the primary challenges is the considerable growth in computational complexity associated with the emergence of ever larger, active or passive, distributed sensor networks. These sensors rely heavily on battery-operated system components to achieve highly functional automation in signal and information processing. In order to keep communication requirements minimal, it is desirable to perform as much processing on the receiver platforms as possible. However, the complexity of the calculations needed to achieve accurate source localization increases dramatically with the size of sensor arrays, resulting in substantial growth of computational requirements that cannot bemore » readily met with standard hardware. One option to meet this challenge builds upon the emergence of digital optical-core devices. The objective of this work was to explore the implementation of key building block algorithms used in underwater source localization on the optical-core digital processing platform recently introduced by Lenslet Inc. This demonstration of considerably faster signal processing capability should be of substantial significance to the design and innovation of future generations of distributed sensor networks.« less

Localization Algorithm Based on a Spring Model (LASM) for Large Scale Wireless Sensor Networks.

PubMed

Chen, Wanming; Mei, Tao; Meng, Max Q-H; Liang, Huawei; Liu, Yumei; Li, Yangming; Li, Shuai

2008-03-15

A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM) method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1) for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

Communal Cooperation in Sensor Networks for Situation Management

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin,Chunsheng

2006-01-01

Situation management is a rapidly evolving science where managed sources are processed as realtime streams of events and fused in a way that maximizes comprehension, thus enabling better decisions for action. Sensor networks provide a new technology that promises ubiquitous input and action throughout an environment, which can substantially improve information available to the process. Here we describe a NASA program that requires improvements in sensor networks and situation management. We present an approach for massively deployed sensor networks that does not rely on centralized control but is founded in lessons learned from the way biological ecosystems are organized. In this approach, fully distributed data aggregation and integration can be performed in a scalable fashion where individual motes operate based on local information, making local decisions that achieve globally-meaningful results. This exemplifies the robust, fault-tolerant infrastructure required for successful situation management systems.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

Barrier Coverage for 3D Camera Sensor Networks

PubMed Central

Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi; Ji, Peng; Chu, Hao

2017-01-01

Barrier coverage, an important research area with respect to camera sensor networks, consists of a number of camera sensors to detect intruders that pass through the barrier area. Existing works on barrier coverage such as local face-view barrier coverage and full-view barrier coverage typically assume that each intruder is considered as a point. However, the crucial feature (e.g., size) of the intruder should be taken into account in the real-world applications. In this paper, we propose a realistic resolution criterion based on a three-dimensional (3D) sensing model of a camera sensor for capturing the intruder’s face. Based on the new resolution criterion, we study the barrier coverage of a feasible deployment strategy in camera sensor networks. Performance results demonstrate that our barrier coverage with more practical considerations is capable of providing a desirable surveillance level. Moreover, compared with local face-view barrier coverage and full-view barrier coverage, our barrier coverage is more reasonable and closer to reality. To the best of our knowledge, our work is the first to propose barrier coverage for 3D camera sensor networks. PMID:28771167

Barrier Coverage for 3D Camera Sensor Networks.

PubMed

Si, Pengju; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi; Ji, Peng; Chu, Hao

2017-08-03

Barrier coverage, an important research area with respect to camera sensor networks, consists of a number of camera sensors to detect intruders that pass through the barrier area. Existing works on barrier coverage such as local face-view barrier coverage and full-view barrier coverage typically assume that each intruder is considered as a point. However, the crucial feature (e.g., size) of the intruder should be taken into account in the real-world applications. In this paper, we propose a realistic resolution criterion based on a three-dimensional (3D) sensing model of a camera sensor for capturing the intruder's face. Based on the new resolution criterion, we study the barrier coverage of a feasible deployment strategy in camera sensor networks. Performance results demonstrate that our barrier coverage with more practical considerations is capable of providing a desirable surveillance level. Moreover, compared with local face-view barrier coverage and full-view barrier coverage, our barrier coverage is more reasonable and closer to reality. To the best of our knowledge, our work is the first to propose barrier coverage for 3D camera sensor networks.

Distributed processing method for arbitrary view generation in camera sensor network

NASA Astrophysics Data System (ADS)

Tehrani, Mehrdad P.; Fujii, Toshiaki; Tanimoto, Masayuki

2003-05-01

Camera sensor network as a new advent of technology is a network that each sensor node can capture video signals, process and communicate them with other nodes. The processing task in this network is to generate arbitrary view, which can be requested from central node or user. To avoid unnecessary communication between nodes in camera sensor network and speed up the processing time, we have distributed the processing tasks between nodes. In this method, each sensor node processes part of interpolation algorithm to generate the interpolated image with local communication between nodes. The processing task in camera sensor network is ray-space interpolation, which is an object independent method and based on MSE minimization by using adaptive filtering. Two methods were proposed for distributing processing tasks, which are Fully Image Shared Decentralized Processing (FIS-DP), and Partially Image Shared Decentralized Processing (PIS-DP), to share image data locally. Comparison of the proposed methods with Centralized Processing (CP) method shows that PIS-DP has the highest processing speed after FIS-DP, and CP has the lowest processing speed. Communication rate of CP and PIS-DP is almost same and better than FIS-DP. So, PIS-DP is recommended because of its better performance than CP and FIS-DP.

An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network.

PubMed

Cheng, Jing; Xia, Linyuan

2016-08-31

Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm.

An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network

PubMed Central

Cheng, Jing; Xia, Linyuan

2016-01-01

Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm. PMID:27589756

Location estimation in wireless sensor networks using spring-relaxation technique.

PubMed

Zhang, Qing; Foh, Chuan Heng; Seet, Boon-Chong; Fong, A C M

2010-01-01

Accurate and low-cost autonomous self-localization is a critical requirement of various applications of a large-scale distributed wireless sensor network (WSN). Due to its massive deployment of sensors, explicit measurements based on specialized localization hardware such as the Global Positioning System (GPS) is not practical. In this paper, we propose a low-cost WSN localization solution. Our design uses received signal strength indicators for ranging, light weight distributed algorithms based on the spring-relaxation technique for location computation, and the cooperative approach to achieve certain location estimation accuracy with a low number of nodes with known locations. We provide analysis to show the suitability of the spring-relaxation technique for WSN localization with cooperative approach, and perform simulation experiments to illustrate its accuracy in localization.

Research Trends in Wireless Visual Sensor Networks When Exploiting Prioritization

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

2015-01-01

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, where many critical topics, such as communication efficiency and energy consumption, have been investigated in the past few years. However, when sensors are endowed with low-power cameras for visual monitoring, a new scope of challenges is raised, demanding new research efforts. In this context, the resource-constrained nature of sensor nodes has demanded the use of prioritization approaches as a practical mechanism to lower the transmission burden of visual data over wireless sensor networks. Many works in recent years have considered local-level prioritization parameters to enhance the overall performance of those networks, but global-level policies can potentially achieve better results in terms of visual monitoring efficiency. In this paper, we make a broad review of some recent works on priority-based optimizations in wireless visual sensor networks. Moreover, we envisage some research trends when exploiting prioritization, potentially fostering the development of promising optimizations for wireless sensor networks composed of visual sensors. PMID:25599425

A Localization-Free Interference and Energy Holes Minimization Routing for Underwater Wireless Sensor Networks.

PubMed

Khan, Anwar; Ahmedy, Ismail; Anisi, Mohammad Hossein; Javaid, Nadeem; Ali, Ihsan; Khan, Nawsher; Alsaqer, Mohammed; Mahmood, Hasan

2018-01-09

Interference and energy holes formation in underwater wireless sensor networks (UWSNs) threaten the reliable delivery of data packets from a source to a destination. Interference also causes inefficient utilization of the limited battery power of the sensor nodes in that more power is consumed in the retransmission of the lost packets. Energy holes are dead nodes close to the surface of water, and their early death interrupts data delivery even when the network has live nodes. This paper proposes a localization-free interference and energy holes minimization (LF-IEHM) routing protocol for UWSNs. The proposed algorithm overcomes interference during data packet forwarding by defining a unique packet holding time for every sensor node. The energy holes formation is mitigated by a variable transmission range of the sensor nodes. As compared to the conventional routing protocols, the proposed protocol does not require the localization information of the sensor nodes, which is cumbersome and difficult to obtain, as nodes change their positions with water currents. Simulation results show superior performance of the proposed scheme in terms of packets received at the final destination and end-to-end delay.

A Localization-Free Interference and Energy Holes Minimization Routing for Underwater Wireless Sensor Networks

PubMed Central

Khan, Anwar; Anisi, Mohammad Hossein; Javaid, Nadeem; Khan, Nawsher; Alsaqer, Mohammed; Mahmood, Hasan

2018-01-01

Interference and energy holes formation in underwater wireless sensor networks (UWSNs) threaten the reliable delivery of data packets from a source to a destination. Interference also causes inefficient utilization of the limited battery power of the sensor nodes in that more power is consumed in the retransmission of the lost packets. Energy holes are dead nodes close to the surface of water, and their early death interrupts data delivery even when the network has live nodes. This paper proposes a localization-free interference and energy holes minimization (LF-IEHM) routing protocol for UWSNs. The proposed algorithm overcomes interference during data packet forwarding by defining a unique packet holding time for every sensor node. The energy holes formation is mitigated by a variable transmission range of the sensor nodes. As compared to the conventional routing protocols, the proposed protocol does not require the localization information of the sensor nodes, which is cumbersome and difficult to obtain, as nodes change their positions with water currents. Simulation results show superior performance of the proposed scheme in terms of packets received at the final destination and end-to-end delay. PMID:29315247

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks.

PubMed

Luo, Junhai; Fan, Liying

2017-03-30

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

PubMed Central

Luo, Junhai; Fan, Liying

2017-01-01

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization. PMID:28358342

Automated general temperature correction method for dielectric soil moisture sensors

NASA Astrophysics Data System (ADS)

Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao

2017-08-01

An effective temperature correction method for dielectric sensors is important to ensure the accuracy of soil water content (SWC) measurements of local to regional-scale soil moisture monitoring networks. These networks are extensively using highly temperature sensitive dielectric sensors due to their low cost, ease of use and less power consumption. Yet there is no general temperature correction method for dielectric sensors, instead sensor or site dependent correction algorithms are employed. Such methods become ineffective at soil moisture monitoring networks with different sensor setups and those that cover diverse climatic conditions and soil types. This study attempted to develop a general temperature correction method for dielectric sensors which can be commonly used regardless of the differences in sensor type, climatic conditions and soil type without rainfall data. In this work an automated general temperature correction method was developed by adopting previously developed temperature correction algorithms using time domain reflectometry (TDR) measurements to ThetaProbe ML2X, Stevens Hydra probe II and Decagon Devices EC-TM sensor measurements. The rainy day effects removal procedure from SWC data was automated by incorporating a statistical inference technique with temperature correction algorithms. The temperature correction method was evaluated using 34 stations from the International Soil Moisture Monitoring Network and another nine stations from a local soil moisture monitoring network in Mongolia. Soil moisture monitoring networks used in this study cover four major climates and six major soil types. Results indicated that the automated temperature correction algorithms developed in this study can eliminate temperature effects from dielectric sensor measurements successfully even without on-site rainfall data. Furthermore, it has been found that actual daily average of SWC has been changed due to temperature effects of dielectric sensors with a significant error factor comparable to ±1% manufacturer's accuracy.

A Dependable Localization Algorithm for Survivable Belt-Type Sensor Networks

PubMed Central

Zhu, Mingqiang; Song, Fei; Xu, Lei; Seo, Jung Taek

2017-01-01

As the key element, sensor networks are widely investigated by the Internet of Things (IoT) community. When massive numbers of devices are well connected, malicious attackers may deliberately propagate fake position information to confuse the ordinary users and lower the network survivability in belt-type situation. However, most existing positioning solutions only focus on the algorithm accuracy and do not consider any security aspects. In this paper, we propose a comprehensive scheme for node localization protection, which aims to improve the energy-efficient, reliability and accuracy. To handle the unbalanced resource consumption, a node deployment mechanism is presented to satisfy the energy balancing strategy in resource-constrained scenarios. According to cooperation localization theory and network connection property, the parameter estimation model is established. To achieve reliable estimations and eliminate large errors, an improved localization algorithm is created based on modified average hop distances. In order to further improve the algorithms, the node positioning accuracy is enhanced by using the steepest descent method. The experimental simulations illustrate the performance of new scheme can meet the previous targets. The results also demonstrate that it improves the belt-type sensor networks’ survivability, in terms of anti-interference, network energy saving, etc. PMID:29186072

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

PubMed Central

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

Resilient Localization for Sensor Networks in Outdoor Environments

DTIC Science & Technology

2004-06-01

Sensor Networks in Outdoor Environments by YoungMin Kwon, Kirill Mechitov, Sameer Sundresh, Wooyoung Kim and Gul Agha June 2004 Report...Environments YoungMin Kwon, Kirill Mechitov, Sameer Sundresh, Wooyoung Kim and Gul Agha Department of Computer Science University of Illinois at Urbana

Using Integer Clocks to Verify the Timing-Sync Sensor Network Protocol

NASA Technical Reports Server (NTRS)

Huang, Xiaowan; Singh, Anu; Smolka, Scott A.

2010-01-01

We use the UPPAAL model checker for Timed Automata to verify the Timing-Sync time-synchronization protocol for sensor networks (TPSN). The TPSN protocol seeks to provide network-wide synchronization of the distributed clocks in a sensor network. Clock-synchronization algorithms for sensor networks such as TPSN must be able to perform arithmetic on clock values to calculate clock drift and network propagation delays. They must be able to read the value of a local clock and assign it to another local clock. Such operations are not directly supported by the theory of Timed Automata. To overcome this formal-modeling obstacle, we augment the UPPAAL specification language with the integer clock derived type. Integer clocks, which are essentially integer variables that are periodically incremented by a global pulse generator, greatly facilitate the encoding of the operations required to synchronize clocks as in the TPSN protocol. With this integer-clock-based model of TPSN in hand, we use UPPAAL to verify that the protocol achieves network-wide time synchronization and is devoid of deadlock. We also use the UPPAAL Tracer tool to illustrate how integer clocks can be used to capture clock drift and resynchronization during protocol execution

A Collaborative Secure Localization Algorithm Based on Trust Model in Underwater Wireless Sensor Networks

PubMed Central

Han, Guangjie; Liu, Li; Jiang, Jinfang; Shu, Lei; Rodrigues, Joel J.P.C.

2016-01-01

Localization is one of the hottest research topics in Underwater Wireless Sensor Networks (UWSNs), since many important applications of UWSNs, e.g., event sensing, target tracking and monitoring, require location information of sensor nodes. Nowadays, a large number of localization algorithms have been proposed for UWSNs. How to improve location accuracy are well studied. However, few of them take location reliability or security into consideration. In this paper, we propose a Collaborative Secure Localization algorithm based on Trust model (CSLT) for UWSNs to ensure location security. Based on the trust model, the secure localization process can be divided into the following five sub-processes: trust evaluation of anchor nodes, initial localization of unknown nodes, trust evaluation of reference nodes, selection of reference node, and secondary localization of unknown node. Simulation results demonstrate that the proposed CSLT algorithm performs better than the compared related works in terms of location security, average localization accuracy and localization ratio. PMID:26891300

Easy Handling of Sensors and Actuators over TCP/IP Networks by Open Source Hardware/Software

PubMed Central

Mejías, Andrés; Herrera, Reyes S.; Márquez, Marco A.; Calderón, Antonio José; González, Isaías; Andújar, José Manuel

2017-01-01

There are several specific solutions for accessing sensors and actuators present in any process or system through a TCP/IP network, either local or a wide area type like the Internet. The usage of sensors and actuators of different nature and diverse interfaces (SPI, I2C, analogue, etc.) makes access to them from a network in a homogeneous and secure way more complex. A framework, including both software and hardware resources, is necessary to simplify and unify networked access to these devices. In this paper, a set of open-source software tools, specifically designed to cover the different issues concerning the access to sensors and actuators, and two proposed low-cost hardware architectures to operate with the abovementioned software tools are presented. They allow integrated and easy access to local or remote sensors and actuators. The software tools, integrated in the free authoring tool Easy Java and Javascript Simulations (EJS) solve the interaction issues between the subsystem that integrates sensors and actuators into the network, called convergence subsystem in this paper, and the Human Machine Interface (HMI)—this one designed using the intuitive graphical system of EJS—located on the user’s computer. The proposed hardware architectures and software tools are described and experimental implementations with the proposed tools are presented. PMID:28067801

Easy Handling of Sensors and Actuators over TCP/IP Networks by Open Source Hardware/Software.

PubMed

Mejías, Andrés; Herrera, Reyes S; Márquez, Marco A; Calderón, Antonio José; González, Isaías; Andújar, José Manuel

2017-01-05

There are several specific solutions for accessing sensors and actuators present in any process or system through a TCP/IP network, either local or a wide area type like the Internet. The usage of sensors and actuators of different nature and diverse interfaces (SPI, I2C, analogue, etc.) makes access to them from a network in a homogeneous and secure way more complex. A framework, including both software and hardware resources, is necessary to simplify and unify networked access to these devices. In this paper, a set of open-source software tools, specifically designed to cover the different issues concerning the access to sensors and actuators, and two proposed low-cost hardware architectures to operate with the abovementioned software tools are presented. They allow integrated and easy access to local or remote sensors and actuators. The software tools, integrated in the free authoring tool Easy Java and Javascript Simulations (EJS) solve the interaction issues between the subsystem that integrates sensors and actuators into the network, called convergence subsystem in this paper, and the Human Machine Interface (HMI)-this one designed using the intuitive graphical system of EJS-located on the user's computer. The proposed hardware architectures and software tools are described and experimental implementations with the proposed tools are presented.

An Enhanced Lightweight Anonymous Authentication Scheme for a Scalable Localization Roaming Service in Wireless Sensor Networks.

PubMed

Chung, Youngseok; Choi, Seokjin; Lee, Youngsook; Park, Namje; Won, Dongho

2016-10-07

More security concerns and complicated requirements arise in wireless sensor networks than in wired networks, due to the vulnerability caused by their openness. To address this vulnerability, anonymous authentication is an essential security mechanism for preserving privacy and providing security. Over recent years, various anonymous authentication schemes have been proposed. Most of them reveal both strengths and weaknesses in terms of security and efficiency. Recently, Farash et al. proposed a lightweight anonymous authentication scheme in ubiquitous networks, which remedies the security faults of previous schemes. However, their scheme still suffers from certain weaknesses. In this paper, we prove that Farash et al.'s scheme fails to provide anonymity, authentication, or password replacement. In addition, we propose an enhanced scheme that provides efficiency, as well as anonymity and security. Considering the limited capability of sensor nodes, we utilize only low-cost functions, such as one-way hash functions and bit-wise exclusive-OR operations. The security and lightness of the proposed scheme mean that it can be applied to roaming service in localized domains of wireless sensor networks, to provide anonymous authentication of sensor nodes.

An Enhanced Lightweight Anonymous Authentication Scheme for a Scalable Localization Roaming Service in Wireless Sensor Networks

PubMed Central

Chung, Youngseok; Choi, Seokjin; Lee, Youngsook; Park, Namje; Won, Dongho

2016-01-01

More security concerns and complicated requirements arise in wireless sensor networks than in wired networks, due to the vulnerability caused by their openness. To address this vulnerability, anonymous authentication is an essential security mechanism for preserving privacy and providing security. Over recent years, various anonymous authentication schemes have been proposed. Most of them reveal both strengths and weaknesses in terms of security and efficiency. Recently, Farash et al. proposed a lightweight anonymous authentication scheme in ubiquitous networks, which remedies the security faults of previous schemes. However, their scheme still suffers from certain weaknesses. In this paper, we prove that Farash et al.’s scheme fails to provide anonymity, authentication, or password replacement. In addition, we propose an enhanced scheme that provides efficiency, as well as anonymity and security. Considering the limited capability of sensor nodes, we utilize only low-cost functions, such as one-way hash functions and bit-wise exclusive-OR operations. The security and lightness of the proposed scheme mean that it can be applied to roaming service in localized domains of wireless sensor networks, to provide anonymous authentication of sensor nodes. PMID:27739417

Bioinspired principles for large-scale networked sensor systems: an overview.

PubMed

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy.

Fusion solution for soldier wearable gunfire detection systems

NASA Astrophysics Data System (ADS)

Cakiades, George; Desai, Sachi; Deligeorges, Socrates; Buckland, Bruce E.; George, Jemin

2012-06-01

Currently existing acoustic based Gunfire Detection Systems (GDS) such as soldier wearable, vehicle mounted, and fixed site devices provide enemy detection and localization capabilities to the user. However, the solution to the problem of portability versus performance tradeoff remains elusive. The Data Fusion Module (DFM), described herein, is a sensor/platform agnostic software supplemental tool that addresses this tradeoff problem by leveraging existing soldier networks to enhance GDS performance across a Tactical Combat Unit (TCU). The DFM software enhances performance by leveraging all available acoustic GDS information across the TCU synergistically to calculate highly accurate solutions more consistently than any individual GDS in the TCU. The networked sensor architecture provides additional capabilities addressing the multiple shooter/fire-fight problems in addition to sniper detection/localization. The addition of the fusion solution to the overall Size, Weight and Power & Cost (SWaP&C) is zero to negligible. At the end of the first-year effort, the DFM integrated sensor network's performance was impressive showing improvements upwards of 50% in comparison to a single sensor solution. Further improvements are expected when the networked sensor architecture created in this effort is fully exploited.

Multiparameter Estimation in Networked Quantum Sensors

NASA Astrophysics Data System (ADS)

Proctor, Timothy J.; Knott, Paul A.; Dunningham, Jacob A.

2018-02-01

We introduce a general model for a network of quantum sensors, and we use this model to consider the following question: When can entanglement between the sensors, and/or global measurements, enhance the precision with which the network can measure a set of unknown parameters? We rigorously answer this question by presenting precise theorems proving that for a broad class of problems there is, at most, a very limited intrinsic advantage to using entangled states or global measurements. Moreover, for many estimation problems separable states and local measurements are optimal, and can achieve the ultimate quantum limit on the estimation uncertainty. This immediately implies that there are broad conditions under which simultaneous estimation of multiple parameters cannot outperform individual, independent estimations. Our results apply to any situation in which spatially localized sensors are unitarily encoded with independent parameters, such as when estimating multiple linear or nonlinear optical phase shifts in quantum imaging, or when mapping out the spatial profile of an unknown magnetic field. We conclude by showing that entangling the sensors can enhance the estimation precision when the parameters of interest are global properties of the entire network.

Scalable Multicast Protocols for Overlapped Groups in Broker-Based Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Chayoung; Ahn, Jinho

In sensor networks, there are lots of overlapped multicast groups because of many subscribers, associated with their potentially varying specific interests, querying every event to sensors/publishers. And gossip based communication protocols are promising as one of potential solutions providing scalability in P(Publish)/ S(Subscribe) paradigm in sensor networks. Moreover, despite the importance of both guaranteeing message delivery order and supporting overlapped multicast groups in sensor or P2P networks, there exist little research works on development of gossip-based protocols to satisfy all these requirements. In this paper, we present two versions of causally ordered delivery guaranteeing protocols for overlapped multicast groups. The one is based on sensor-broker as delegates and the other is based on local views and delegates representing subscriber subgroups. In the sensor-broker based protocol, sensor-broker might lead to make overlapped multicast networks organized by subscriber's interests. The message delivery order has been guaranteed consistently and all multicast messages are delivered to overlapped subscribers using gossip based protocols by sensor-broker. Therefore, these features of the sensor-broker based protocol might be significantly scalable rather than those of the protocols by hierarchical membership list of dedicated groups like traditional committee protocols. And the subscriber-delegate based protocol is much stronger rather than fully decentralized protocols guaranteeing causally ordered delivery based on only local views because the message delivery order has been guaranteed consistently by all corresponding members of the groups including delegates. Therefore, this feature of the subscriber-delegate protocol is a hybrid approach improving the inherent scalability of multicast nature by gossip-based technique in all communications.

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

PubMed

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Novel Re-keying Function Protocol (NRFP) For Wireless Sensor Network Security.

PubMed

Abdullah, Maan Younis; Hua, Gui Wei; Alsharabi, Naif

2008-12-04

This paper describes a novel re-keying function protocol (NRFP) for wireless sensor network security. A re-keying process management system for sensor networks is designed to support in-network processing. The design of the protocol is motivated by decentralization key management for wireless sensor networks (WSNs), covering key deployment, key refreshment, and key establishment. NRFP supports the establishment of novel administrative functions for sensor nodes that derive/re-derive a session key for each communication session. The protocol proposes direct connection, in-direct connection and hybrid connection. NRFP also includes an efficient protocol for local broadcast authentication based on the use of one-way key chains. A salient feature of the authentication protocol is that it supports source authentication without precluding in-network processing. Security and performance analysis shows that it is very efficient in computation, communication and storage and, that NRFP is also effective in defending against many sophisticated attacks.

Semantic Visualization of Wireless Sensor Networks for Elderly Monitoring

NASA Astrophysics Data System (ADS)

Stocklöw, Carsten; Kamieth, Felix

In the area of Ambient Intelligence, Wireless Sensor Networks are commonly used for user monitoring purposes like health monitoring and user localization. Existing work on visualization of wireless sensor networks focuses mainly on displaying individual nodes and logical, graph-based topologies. This way, the relation to the real-world deployment is lost. This paper presents a novel approach for visualization of wireless sensor networks and interaction with complex services on the nodes. The environment is realized as a 3D model, and multiple nodes, that are worn by a single individual, are grouped together to allow an intuitive interface for end users. We describe application examples and show that our approach allows easier access to network information and functionality by comparing it with existing solutions.

On localizing a capsule endoscope using magnetic sensors.

PubMed

Moussakhani, Babak; Ramstad, Tor; Flåm, John T; Balasingham, Ilangko

2012-01-01

In this work, localizing a capsule endoscope within the gastrointestinal tract is addressed. It is assumed that the capsule is equipped with a magnet, and that a magnetic sensor network measures the flux from this magnet. We assume no prior knowledge on the source location, and that the measurements collected by the sensors are corrupted by thermal Gaussian noise only. Under these assumptions, we focus on determining the Cramer-Rao Lower Bound (CRLB) for the location of the endoscope. Thus, we are not studying specific estimators, but rather the theoretical performance of an optimal one. It is demonstrated that the CRLB is a function of the distance and angle between the sensor network and the magnet. By studying the CRLB with respect to different sensor array constellations, we are able to indicate favorable constellations.

Comparison of Event Detection Methods for Centralized Sensor Networks

NASA Technical Reports Server (NTRS)

Sauvageon, Julien; Agogiono, Alice M.; Farhang, Ali; Tumer, Irem Y.

2006-01-01

The development of an Integrated Vehicle Health Management (IVHM) for space vehicles has become a great concern. Smart Sensor Networks is one of the promising technologies that are catching a lot of attention. In this paper, we propose to a qualitative comparison of several local event (hot spot) detection algorithms in centralized redundant sensor networks. The algorithms are compared regarding their ability to locate and evaluate the event under noise and sensor failures. The purpose of this study is to check if the ratio performance/computational power of the Mote Fuzzy Validation and Fusion algorithm is relevant compare to simpler methods.

On computer vision in wireless sensor networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, Nina M.; Ko, Teresa H.

Wireless sensor networks allow detailed sensing of otherwise unknown and inaccessible environments. While it would be beneficial to include cameras in a wireless sensor network because images are so rich in information, the power cost of transmitting an image across the wireless network can dramatically shorten the lifespan of the sensor nodes. This paper describe a new paradigm for the incorporation of imaging into wireless networks. Rather than focusing on transmitting images across the network, we show how an image can be processed locally for key features using simple detectors. Contrasted with traditional event detection systems that trigger an imagemore » capture, this enables a new class of sensors which uses a low power imaging sensor to detect a variety of visual cues. Sharing these features among relevant nodes cues specific actions to better provide information about the environment. We report on various existing techniques developed for traditional computer vision research which can aid in this work.« less

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

PubMed

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

PubMed Central

Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-01-01

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. PMID:29462929

Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks

PubMed Central

Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing

2016-01-01

Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871

Radioactive source localization in urban environments with sensor networks and the Internet of Things

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sullivan, Clair J.

The use of radiation detectors as an element in the so-called “Internet of Things” has recently become viable with the available of low-cost, mobile radiation sensors capable of streaming geo-referenced data. New methods for fusing the data from multiple sensors on such a network is presented. The traditional simple and ordinary Kriging methods present a challenge for such a network since the assumption of a constant mean is not valid in this application. In conclusion, a variety of Kalman filters are introduced in an attempt to solve the problem associated with this variable and unknown mean. Results are presented onmore » a deployed sensor network.« less

Radioactive source localization in urban environments with sensor networks and the Internet of Things

DOE PAGES

Sullivan, Clair J.

2016-01-01

The use of radiation detectors as an element in the so-called “Internet of Things” has recently become viable with the available of low-cost, mobile radiation sensors capable of streaming geo-referenced data. New methods for fusing the data from multiple sensors on such a network is presented. The traditional simple and ordinary Kriging methods present a challenge for such a network since the assumption of a constant mean is not valid in this application. In conclusion, a variety of Kalman filters are introduced in an attempt to solve the problem associated with this variable and unknown mean. Results are presented onmore » a deployed sensor network.« less

Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview

PubMed Central

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy. PMID:22163841

Emergent Adaptive Noise Reduction from Communal Cooperation of Sensor Grid

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Jones, Michael G.; Nark, Douglas M.; Lodding, Kenneth N.

2010-01-01

In the last decade, the realization of small, inexpensive, and powerful devices with sensors, computers, and wireless communication has promised the development of massive sized sensor networks with dense deployments over large areas capable of high fidelity situational assessments. However, most management models have been based on centralized control and research has concentrated on methods for passing data from sensor devices to the central controller. Most implementations have been small but, as it is not scalable, this methodology is insufficient for massive deployments. Here, a specific application of a large sensor network for adaptive noise reduction demonstrates a new paradigm where communities of sensor/computer devices assess local conditions and make local decisions from which emerges a global behaviour. This approach obviates many of the problems of centralized control as it is not prone to single point of failure and is more scalable, efficient, robust, and fault tolerant

Radar coordination and resource management in a distributed sensor network using emergent control

NASA Astrophysics Data System (ADS)

Weir, B. S.; Sokol, T. M.

2009-05-01

As the list of anti-air warfare and ballistic missile defense missions grows, there is an increasing need to coordinate and optimize usage of radar resources across the netted force. Early attempts at this optimization involved top-down control mechanisms whereby sensors accept resource tasking orders from networked tracking elements. These approaches rely heavily on uncertain knowledge of sensor constraints and capabilities. Furthermore, advanced sensor systems may support self-defense missions of the host platform and are therefore unable to relinquish control to an external function. To surmount these issues, the use of bottom-up emergent control techniques is proposed. The information necessary to make quality, network-wide resource allocations is readily available to sensor nodes with access to a netted track picture. By assessing resource priorities relative to the network (versus local) track picture, sensors can understand the contribution of their resources to the netted force. This allows the sensors to apply resources where most needed and remove waste. Furthermore, simple local rules for resource usage, when properly constructed, allow sensors to obtain a globally optimal resource allocation without direct coordination (emergence). These results are robust to partial implementation (i.e., not all nodes upgraded at once) and failures on individual nodes (whether from casualty or reallocation to other sensor missions), and they leave resource control decisions in the hands of the sensor systems instead of an external function. This paper presents independent research and development work on emergent control of sensor resources and the impact to resource allocation and tracking performance.

Communal Sensor Network for Adaptive Noise Reduction in Aircraft Engine Nacelles

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Nark, Douglas M.; Jones, Michael G.

2011-01-01

Emergent behavior, a subject of much research in biology, sociology, and economics, is a foundational element of Complex Systems Science and is apropos in the design of sensor network systems. To demonstrate engineering for emergent behavior, a novel approach in the design of a sensor/actuator network is presented maintaining optimal noise attenuation as an adaptation to changing acoustic conditions. Rather than use the conventional approach where sensors are managed by a central controller, this new paradigm uses a biomimetic model where sensor/actuators cooperate as a community of autonomous organisms, sharing with neighbors to control impedance based on local information. From the combination of all individual actions, an optimal attenuation emerges for the global system.

An Amplitude-Based Estimation Method for International Space Station (ISS) Leak Detection and Localization Using Acoustic Sensor Networks

NASA Technical Reports Server (NTRS)

Tian, Jialin; Madaras, Eric I.

2009-01-01

The development of a robust and efficient leak detection and localization system within a space station environment presents a unique challenge. A plausible approach includes the implementation of an acoustic sensor network system that can successfully detect the presence of a leak and determine the location of the leak source. Traditional acoustic detection and localization schemes rely on the phase and amplitude information collected by the sensor array system. Furthermore, the acoustic source signals are assumed to be airborne and far-field. Likewise, there are similar applications in sonar. In solids, there are specialized methods for locating events that are used in geology and in acoustic emission testing that involve sensor arrays and depend on a discernable phase front to the received signal. These methods are ineffective if applied to a sensor detection system within the space station environment. In the case of acoustic signal location, there are significant baffling and structural impediments to the sound path and the source could be in the near-field of a sensor in this particular setting.

Deploying temporary networks for upscaling of sparse network stations

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

2016-10-01

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network

NASA Astrophysics Data System (ADS)

Friedlander, David; Griffin, Christopher; Jacobson, Noah; Phoha, Shashi; Brooks, Richard R.

2003-12-01

Autonomous networks of sensor platforms can be designed to interact in dynamic and noisy environments to determine the occurrence of specified transient events that define the dynamic process of interest. For example, a sensor network may be used for battlefield surveillance with the purpose of detecting, identifying, and tracking enemy activity. When the number of nodes is large, human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous nodes is necessary to maintain connectivity and sensor coverage and to combine information for better understanding the dynamics of the environment. Resource conservation requires adaptive clustering in the vicinity of the event. This paper presents methods for dynamic distributed signal processing using an ad hoc mobile network of microsensors to detect, identify, and track targets in noisy environments. They seamlessly integrate data from fixed and mobile platforms and dynamically organize platforms into clusters to process local data along the trajectory of the targets. Local analysis of sensor data is used to determine a set of target attribute values and classify the target. Sensor data from a field test in the Marine base at Twentynine Palms, Calif, was analyzed using the techniques described in this paper. The results were compared to "ground truth" data obtained from GPS receivers on the vehicles.

Multiparameter Estimation in Networked Quantum Sensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Proctor, Timothy J.; Knott, Paul A.; Dunningham, Jacob A.

We introduce a general model for a network of quantum sensors, and we use this model to consider the question: When can entanglement between the sensors, and/or global measurements, enhance the precision with which the network can measure a set of unknown parameters? We rigorously answer this question by presenting precise theorems proving that for a broad class of problems there is, at most, a very limited intrinsic advantage to using entangled states or global measurements. Moreover, for many estimation problems separable states and local measurements are optimal, and can achieve the ultimate quantum limit on the estimation uncertainty. Thismore » immediately implies that there are broad conditions under which simultaneous estimation of multiple parameters cannot outperform individual, independent estimations. Our results apply to any situation in which spatially localized sensors are unitarily encoded with independent parameters, such as when estimating multiple linear or non-linear optical phase shifts in quantum imaging, or when mapping out the spatial profile of an unknown magnetic field. We conclude by showing that entangling the sensors can enhance the estimation precision when the parameters of interest are global properties of the entire network.« less

Multiparameter Estimation in Networked Quantum Sensors

DOE PAGES

Proctor, Timothy J.; Knott, Paul A.; Dunningham, Jacob A.

2018-02-21

We introduce a general model for a network of quantum sensors, and we use this model to consider the question: When can entanglement between the sensors, and/or global measurements, enhance the precision with which the network can measure a set of unknown parameters? We rigorously answer this question by presenting precise theorems proving that for a broad class of problems there is, at most, a very limited intrinsic advantage to using entangled states or global measurements. Moreover, for many estimation problems separable states and local measurements are optimal, and can achieve the ultimate quantum limit on the estimation uncertainty. Thismore » immediately implies that there are broad conditions under which simultaneous estimation of multiple parameters cannot outperform individual, independent estimations. Our results apply to any situation in which spatially localized sensors are unitarily encoded with independent parameters, such as when estimating multiple linear or non-linear optical phase shifts in quantum imaging, or when mapping out the spatial profile of an unknown magnetic field. We conclude by showing that entangling the sensors can enhance the estimation precision when the parameters of interest are global properties of the entire network.« less

A Novel Re-keying Function Protocol (NRFP) For Wireless Sensor Network Security

PubMed Central

Abdullah, Maan Younis; Hua, Gui Wei; Alsharabi, Naif

2008-01-01

This paper describes a novel re-keying function protocol (NRFP) for wireless sensor network security. A re-keying process management system for sensor networks is designed to support in-network processing. The design of the protocol is motivated by decentralization key management for wireless sensor networks (WSNs), covering key deployment, key refreshment, and key establishment. NRFP supports the establishment of novel administrative functions for sensor nodes that derive/re-derive a session key for each communication session. The protocol proposes direct connection, in-direct connection and hybrid connection. NRFP also includes an efficient protocol for local broadcast authentication based on the use of one-way key chains. A salient feature of the authentication protocol is that it supports source authentication without precluding innetwork processing. Security and performance analysis shows that it is very efficient in computation, communication and storage and, that NRFP is also effective in defending against many sophisticated attacks. PMID:27873963

Citizen-sensor-networks to confront government decision-makers: Two lessons from the Netherlands.

PubMed

Carton, Linda; Ache, Peter

2017-07-01

This paper presents one emerging social-technical innovation: The evolution of citizen-sensor-networks where citizens organize themselves from the 'bottom up', for the sake of confronting governance officials with measured information about environmental qualities. We have observed how citizen-sensor-networks have been initiated in the Netherlands in cases where official government monitoring and business organizations leave gaps. The formed citizen-sensor-networks collect information about issues that affect the local community in their quality-of-living. In particular, two community initiatives are described where the sensed environmental information, on noise pollution and gas-extraction induced earthquakes respectively, is published through networked geographic information methods. Both community initiatives pioneered in developing an approach that comprises the combined setting-up of sensor data flows, real-time map portals and community organization. Two particular cases are analyzed to trace the emergence and network operation of such 'networked geo-information tools' in practice: (1) The Groningen earthquake monitor, and (2) The Airplane Monitor Schiphol. In both cases, environmental 'externalities' of spatial-economic activities play an important role, having economic dimensions of national importance (e.g. gas extraction and national airport development) while simultaneously affecting the regional community with environmental consequences. The monitoring systems analyzed in this paper are established bottom-up, by citizens for citizens, to serve as 'information power' in dialogue with government institutions. The goal of this paper is to gain insight in how these citizen-sensor-networks come about: how the idea for establishing a sensor network originated, how their value gets recognized and adopted in the overall 'system of governance'; to what extent they bring countervailing power against vested interests and established discourses to the table and influence power-laden conflicts over environmental pressures; and whether or not they achieve (some form of) institutionalization and, ultimately, policy change. We find that the studied-citizen-sensor networks gain strength by uniting efforts and activities in crowdsourcing data, providing factual, 'objectivized data' or 'evidence' of the situation 'on the ground' on a matter of local community-wide concern. By filling an information need of the local community, a process of 'collective sense-making' combined with citizen empowerment could grow, which influenced societal discourse and challenged prevailing truth-claims of public institutions. In both cases similar, 'competing' web-portals were developed in response, both by the gas-extraction company and the airport. But with the citizen-sensor-networks alongside, we conclude there is a shift in power balance involved between government and affected communities, as the government no longer has information monopoly on environmental measurements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Research on Localization Algorithms Based on Acoustic Communication for Underwater Sensor Networks

PubMed Central

Fan, Liying; Wu, Shan; Yan, Xueting

2017-01-01

The water source, as a significant body of the earth, with a high value, serves as a hot topic to study Underwater Sensor Networks (UWSNs). Various applications can be realized based on UWSNs. Our paper mainly concentrates on the localization algorithms based on the acoustic communication for UWSNs. An in-depth survey of localization algorithms is provided for UWSNs. We first introduce the acoustic communication, network architecture, and routing technique in UWSNs. The localization algorithms are classified into five aspects, namely, computation algorithm, spatial coverage, range measurement, the state of the nodes and communication between nodes that are different from all other survey papers. Moreover, we collect a lot of pioneering papers, and a comprehensive comparison is made. In addition, some challenges and open issues are raised in our paper. PMID:29301369

Image sensor system with bio-inspired efficient coding and adaptation.

PubMed

Okuno, Hirotsugu; Yagi, Tetsuya

2012-08-01

We designed and implemented an image sensor system equipped with three bio-inspired coding and adaptation strategies: logarithmic transform, local average subtraction, and feedback gain control. The system comprises a field-programmable gate array (FPGA), a resistive network, and active pixel sensors (APS), whose light intensity-voltage characteristics are controllable. The system employs multiple time-varying reset voltage signals for APS in order to realize multiple logarithmic intensity-voltage characteristics, which are controlled so that the entropy of the output image is maximized. The system also employs local average subtraction and gain control in order to obtain images with an appropriate contrast. The local average is calculated by the resistive network instantaneously. The designed system was successfully used to obtain appropriate images of objects that were subjected to large changes in illumination.

Capacity Limit, Link Scheduling and Power Control in Wireless Networks

ERIC Educational Resources Information Center

Zhou, Shan

2013-01-01

The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different…

Collecting and distributing wearable sensor data: an embedded personal area network to local area network gateway server.

PubMed

Neuhaeuser, Jakob; D'Angelo, Lorenzo T

2013-01-01

The goal of the concept and of the device presented in this contribution is to be able to collect sensor data from wearable sensors directly, automatically and wirelessly and to make them available over a wired local area network. Several concepts in e-health and telemedicine make use of portable and wearable sensors to collect movement or activity data. Usually these data are either collected via a wireless personal area network or using a connection to the user's smartphone. However, users might not carry smartphones on them while inside a residential building such as a nursing home or a hospital, but also within their home. Also, in such areas the use of other wireless communication technologies might be limited. The presented system is an embedded server which can be deployed in several rooms in order to ensure live data collection in bigger buildings. Also, the collection of data batches recorded out of range, as soon as a connection is established, is also possible. Both, the system concept and the realization are presented.

Identification of Hot Moments and Hot Spots for Real-Time Adaptive Control of Multi-scale Environmental Sensor Networks

NASA Astrophysics Data System (ADS)

Wietsma, T.; Minsker, B. S.

2012-12-01

Increased sensor throughput combined with decreasing hardware costs has led to a disruptive growth in data volume. This disruption, popularly termed "the data deluge," has placed new demands for cyberinfrastructure and information technology skills among researchers in many academic fields, including the environmental sciences. Adaptive sampling has been well established as an effective means of improving network resource efficiency (energy, bandwidth) without sacrificing sample set quality relative to traditional uniform sampling. However, using adaptive sampling for the explicit purpose of improving resolution over events -- situations displaying intermittent dynamics and unique hydrogeological signatures -- is relatively new. In this paper, we define hot spots and hot moments in terms of sensor signal activity as measured through discrete Fourier analysis. Following this frequency-based approach, we apply the Nyquist-Shannon sampling theorem, a fundamental contribution from signal processing that led to the field of information theory, for analysis of uni- and multivariate environmental signal data. In the scope of multi-scale environmental sensor networks, we present several sampling control algorithms, derived from the Nyquist-Shannon theorem, that operate at local (field sensor), regional (base station for aggregation of field sensor data), and global (Cloud-based, computationally intensive models) scales. Evaluated over soil moisture data, results indicate significantly greater sample density during precipitation events while reducing overall sample volume. Using these algorithms as indicators rather than control mechanisms, we also discuss opportunities for spatio-temporal modeling as a tool for planning/modifying sensor network deployments. Locally adaptive model based on Nyquist-Shannon sampling theorem Pareto frontiers for local, regional, and global models relative to uniform sampling. Objectives are (1) overall sampling efficiency and (2) sampling efficiency during hot moments as identified using heuristic approach.

Optimal Sensor Fusion for Structural Health Monitoring of Aircraft Composite Components

DTIC Science & Technology

2011-09-01

sensor networks combine or fuse different types of sensors. Fiber Bragg Grating ( FBG ) sensors can be inserted in layers of composite structures to...consideration. This paper describes an example of optimal sensor fusion, which combines FBG sensors and PZT sensors. Optimal sensor fusion tries to find...Fiber Bragg Grating ( FBG ) sensors can be inserted in layers of composite structures to provide local damage detection, while surface mounted

Optimization of wireless sensor networks based on chicken swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Wang, Qingxi; Zhu, Lihua

2017-05-01

In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

Research on sensor design for internet of things and laser manufacturing

NASA Astrophysics Data System (ADS)

Wang, Tao; Yao, Jianquan; Guo, Ling; Zhang, Yanchun

2010-12-01

In this paper, we will introduce the research on sensor design for IOT (Internet of Things) and laser manufacturing, and supporting the establishment of local area IOT. The main contents include studying on the structure designing of silicon micro tilt sensor, data acquisition and processing, addressing implanted and building Local Area IOT with wireless sensor network technology. At last, it is discussed the status and trends of the Internet of Things from the promoters, watchers, pessimists and doers.

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks.

PubMed

Wang, Tian; Wu, Qun; Wen, Sheng; Cai, Yiqiao; Tian, Hui; Chen, Yonghong; Wang, Baowei

2017-01-13

WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator's mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost.

Innovative solutions in monitoring systems in flood protection

NASA Astrophysics Data System (ADS)

Sekuła, Klaudia; Połeć, Marzena; Borecka, Aleksandra

2018-02-01

The article presents the possibilities of ISMOP - IT System of Levee Monitoring. This system is able to collecting data from the reference and experimental control and measurement network. The experimental levee is build in a 1:1 scale and located in the village of Czernichow, near Cracow. The innovation is the utilization of a series of sensors monitoring the changes in the body of levee. It can be done by comparing the results of numerical simulations with results from installed two groups of sensors: reference sensors and experimental sensors. The reference control and measurement sensors create network based on pore pressure and temperature sensors. Additionally, it contains the fiber-optic technology. The second network include design experimental sensors, constructed for the development of solutions that can be used in existing flood embankments. The results are important to create the comprehensive and inexpensive monitoring system, which could be helpful for state authorities and local governments in flood protection.

Routing in Mobile Wireless Sensor Networks: A Leader-Based Approach.

PubMed

Burgos, Unai; Amozarrain, Ugaitz; Gómez-Calzado, Carlos; Lafuente, Alberto

2017-07-07

This paper presents a leader-based approach to routing in Mobile Wireless Sensor Networks (MWSN). Using local information from neighbour nodes, a leader election mechanism maintains a spanning tree in order to provide the necessary adaptations for efficient routing upon the connectivity changes resulting from the mobility of sensors or sink nodes. We present two protocols following the leader election approach, which have been implemented using Castalia and OMNeT++. The protocols have been evaluated, besides other reference MWSN routing protocols, to analyse the impact of network size and node velocity on performance, which has demonstrated the validity of our approach.

High Accuracy Passive Magnetic Field-Based Localization for Feedback Control Using Principal Component Analysis.

PubMed

Foong, Shaohui; Sun, Zhenglong

2016-08-12

In this paper, a novel magnetic field-based sensing system employing statistically optimized concurrent multiple sensor outputs for precise field-position association and localization is presented. This method capitalizes on the independence between simultaneous spatial field measurements at multiple locations to induce unique correspondences between field and position. This single-source-multi-sensor configuration is able to achieve accurate and precise localization and tracking of translational motion without contact over large travel distances for feedback control. Principal component analysis (PCA) is used as a pseudo-linear filter to optimally reduce the dimensions of the multi-sensor output space for computationally efficient field-position mapping with artificial neural networks (ANNs). Numerical simulations are employed to investigate the effects of geometric parameters and Gaussian noise corruption on PCA assisted ANN mapping performance. Using a 9-sensor network, the sensing accuracy and closed-loop tracking performance of the proposed optimal field-based sensing system is experimentally evaluated on a linear actuator with a significantly more expensive optical encoder as a comparison.

Pollution source localization in an urban water supply network based on dynamic water demand.

PubMed

Yan, Xuesong; Zhu, Zhixin; Li, Tian

2017-10-27

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer's water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

Collaborative Monitoring and Hazard Mitigation at Fuego Volcano, Guatemala

NASA Astrophysics Data System (ADS)

Lyons, J. J.; Bluth, G. J.; Rose, W. I.; Patrick, M.; Johnson, J. B.; Stix, J.

2007-05-01

A portable, digital sensor network has been installed to closely monitor changing activity at Fuego volcano, which takes advantage of an international collaborative effort among Guatemala, U.S. and Canadian universities, and the Peace Corps. The goal of this effort is to improve the understanding shallow internal processes, and consequently to more effectively mitigate volcanic hazards. Fuego volcano has had more than 60 historical eruptions and nearly-continuous activity make it an ideal laboratory to study volcanic processes. Close monitoring is needed to identify base-line activity, and rapidly identify and disseminate changes in the activity which might threaten nearby communities. The sensor network is comprised of a miniature DOAS ultraviolet spectrometer fitted with a system for automated plume scans, a digital video camera, and two seismo-acoustic stations and portable dataloggers. These sensors are on loan from scientists who visited Fuego during short field seasons and donated use of their sensors to a resident Peace Corps Masters International student from Michigan Technological University for extended data collection. The sensor network is based around the local volcano observatory maintained by Instituto National de Sismologia, Vulcanologia, Metrologia e Hidrologia (INSIVUMEH). INSIVUMEH provides local support and historical knowledge of Fuego activity as well as a secure location for storage of scientific equipment, data processing, and charging of the batteries that power the sensors. The complete sensor network came online in mid-February 2007 and here we present preliminary results from concurrent gas, seismic, and acoustic monitoring of activity from Fuego volcano.

Multi-mode clustering model for hierarchical wireless sensor networks

NASA Astrophysics Data System (ADS)

Hu, Xiangdong; Li, Yongfu; Xu, Huifen

2017-03-01

The topology management, i.e., clusters maintenance, of wireless sensor networks (WSNs) is still a challenge due to its numerous nodes, diverse application scenarios and limited resources as well as complex dynamics. To address this issue, a multi-mode clustering model (M2 CM) is proposed to maintain the clusters for hierarchical WSNs in this study. In particular, unlike the traditional time-trigger model based on the whole-network and periodic style, the M2 CM is proposed based on the local and event-trigger operations. In addition, an adaptive local maintenance algorithm is designed for the broken clusters in the WSNs using the spatial-temporal demand changes accordingly. Numerical experiments are performed using the NS2 network simulation platform. Results validate the effectiveness of the proposed model with respect to the network maintenance costs, node energy consumption and transmitted data as well as the network lifetime.

Attack Detection in Sensor Network Target Localization Systems With Quantized Data

NASA Astrophysics Data System (ADS)

Zhang, Jiangfan; Wang, Xiaodong; Blum, Rick S.; Kaplan, Lance M.

2018-04-01

We consider a sensor network focused on target localization, where sensors measure the signal strength emitted from the target. Each measurement is quantized to one bit and sent to the fusion center. A general attack is considered at some sensors that attempts to cause the fusion center to produce an inaccurate estimation of the target location with a large mean-square-error. The attack is a combination of man-in-the-middle, hacking, and spoofing attacks that can effectively change both signals going into and coming out of the sensor nodes in a realistic manner. We show that the essential effect of attacks is to alter the estimated distance between the target and each attacked sensor to a different extent, giving rise to a geometric inconsistency among the attacked and unattacked sensors. Hence, with the help of two secure sensors, a class of detectors are proposed to detect the attacked sensors by scrutinizing the existence of the geometric inconsistency. We show that the false alarm and miss probabilities of the proposed detectors decrease exponentially as the number of measurement samples increases, which implies that for sufficiently large number of samples, the proposed detectors can identify the attacked and unattacked sensors with any required accuracy.

Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations

PubMed Central

Zazo, Javier; Valcarcel Macua, Sergio; Zazo, Santiago; Pérez, Marina; Pérez-Álvarez, Iván; Jiménez, Eugenio; Cardona, Laura; Brito, Joaquín Hernández; Quevedo, Eduardo

2016-01-01

In the first part of the paper, we modeled and characterized the underwater radio channel in shallow waters. In the second part, we analyze the application requirements for an underwater wireless sensor network (U-WSN) operating in the same environment and perform detailed simulations. We consider two localization applications, namely self-localization and navigation aid, and propose algorithms that work well under the specific constraints associated with U-WSN, namely low connectivity, low data rates and high packet loss probability. We propose an algorithm where the sensor nodes collaboratively estimate their unknown positions in the network using a low number of anchor nodes and distance measurements from the underwater channel. Once the network has been self-located, we consider a node estimating its position for underwater navigation communicating with neighboring nodes. We also propose a communication system and simulate the whole electromagnetic U-WSN in the Castalia simulator to evaluate the network performance, including propagation impairments (e.g., noise, interference), radio parameters (e.g., modulation scheme, bandwidth, transmit power), hardware limitations (e.g., clock drift, transmission buffer) and complete MAC and routing protocols. We also explain the changes that have to be done to Castalia in order to perform the simulations. In addition, we propose a parametric model of the communication channel that matches well with the results from the first part of this paper. Finally, we provide simulation results for some illustrative scenarios. PMID:27999309

Localization Strategies in WSNs as applied to Landslide Monitoring (Invited)

NASA Astrophysics Data System (ADS)

Massa, A.; Robol, F.; Polo, A.; Giarola, E.; Viani, F.

2013-12-01

In the last years, heterogeneous integrated smart systems based on wireless sensor network (WSN) technology have been developed at the ELEDIA Research Center of the University of Trento [1]. One of the key features of WSNs as applied to distributed monitoring is that, while the capabilities of each single sensor node is limited, the implementation of cooperative schemes throughout the whole network enables the solution of even complex tasks, as the landslide monitoring. The capability of localizing targets respect to the position of the sensor nodes turns out to be fundamental in those application fields where relative movements arise. The main properties like the target typology, the movement characteristics, and the required localization resolution are different changing the reference scenario. However, the common key issue is still the localization of moving targets within the area covered by the sensor network. Many experiences were preparatory for the challenging activities in the field of landslide monitoring where the basic idea is mostly that of detecting slight soil movements. Among them, some examples of WSN-based systems experimentally applied to the localization of people [2] and wildlife [3] have been proposed. More recently, the WSN backbone as well as the investigated sensing technologies have been customized for monitoring superficial movements of the soil. The relative positions of wireless sensor nodes deployed where high probability of landslide exists is carefully monitored to forecast dangerous events. Multiple sensors like ultrasound, laser, high precision GPS, for the precise measurement of relative distances between the nodes of the network and the absolute positions respect to reference targets have been integrated in a prototype system. The millimeter accuracy in the position estimation enables the detection of small soil modifications and to infer the superficial evolution profile of the landslide. This information locally acquired also represent a fine tuning of large scale satellite acquisitions, usually adopted for remote sensing of landslides. The integration of dense and frequent WSN data within satellite image analysis will enhance the sensing capabilities leading to a multi-resolution and an highly space-time calibrated system. The WSN-based system has been preliminary tested in controlled environments in the ELEDIA laboratories and is now installed in a real test site where an active landslide is evolving. Preliminary data are here presented to assess the feasibility of the investigated solution in landslide monitoring and event forecasting. REFERENCES [1] M. Benedetti, L. Ioriatti, M. Martinelli, and F. Viani, 'Wireless sensor network: a pervasive technology for earth observation,' in IEEE Journal of Selected Topics in App. Earth Obs. And Remote Sens., vol. 3, no. 4, pp. 488-497, 2010. [2] F. Viani, M. Donelli, P. Rocca, G. Oliveri, D. Trinchero, and A. Massa, 'Localization, tracking and imaging of targets in wireless sensor networks,' Radio Science, vol. 46, no. 5, 2011. [3] F. Viani, F. Robol, M. Salucci, E. Giarola, S. De Vigili, M. Rocca, F. Boldrini, G. Benedetti, and A. Massa, 'WSN-based early alert system for preventing wildlife-vehicle collisions in Alps regions - From the laboratory test to the real-world implementation,' 7th European Conference on Antennas and Propagation 2013 (EUCAP2013), Gothenburg, Sweden, April 8-12, 2013.

Distributed Spectral Monitoring For Emitter Localization

DTIC Science & Technology

2018-02-12

localization techniques in a DSA sensor network. The results of the research are presented through simulation of localization algorithms, emulation of a...network on a wireless RF environment emulator, and field tests. The results of the various tests in both the lab and field are obtained and analyzed to... are two main classes of localization techniques, and the technique to use will depend on the information available with the emitter. The first class

Location-Aware Dynamic Session-Key Management for Grid-Based Wireless Sensor Networks

PubMed Central

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths. PMID:22163606

Location-aware dynamic session-key management for grid-based Wireless Sensor Networks.

PubMed

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths.

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

PubMed Central

Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

2014-01-01

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. PMID:25390408

Distributed estimation for adaptive sensor selection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

2014-05-01

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

Distributed Transmitter Localization by Power Difference of Arrival (PDOA) on a Network of GNU Radio Sensors

DTIC Science & Technology

2015-02-03

requiring the least hardware investment is to localize by received signal strength [1, 4, 5]. Because our intended scenario of low-complexity...MHz were taken with a spectrum analyzer program on the USRP and a range finder was used to measure the distance between the emitter and sensor

An Ad-hoc Satellite Network to Measure Filamentary Current Structures in the Auroral Zone

NASA Astrophysics Data System (ADS)

Nabong, C.; Fritz, T. A.; Semeter, J. L.

2014-12-01

An ad-hoc cubesat-based satellite network project known as ANDESITE is under development at Boston University. It aims to develop a dense constellation of easy-to-use, rapidly-deployable low-cost wireless sensor nodes in space. The objectives of the project are threefold: 1) Demonstrate viability of satellite based sensor networks by deploying an 8-node miniature sensor network to study the filamentation of the field aligned currents in the auroral zones of the Earth's magnetosphere. 2) Test the scalability of proposed protocols, including localization techniques, tracking, data aggregation, and routing, for a 3 dimensional wireless sensor network using a "flock" of nodes. 3) Construct a 6U Cube-sat running the Android OS as an integrated constellation manager, data mule and sensor node deplorer. This small network of sensor nodes will resolve current densities at different spatial resolutions in the near-Earth magnetosphere using measurements from magnetometers with 1-nT sensitivities and 0.2 nT/√Hz self-noise. Mapping of these currents will provide new constraints for models of auroral particle acceleration, wave-particle interactions, ionospheric destabilization, and other kinetic processes operating in the low-beta plasma of the near Earth magnetosphere.

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks

PubMed Central

Wang, Tian; Wu, Qun; Wen, Sheng; Cai, Yiqiao; Tian, Hui; Chen, Yonghong; Wang, Baowei

2017-01-01

WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator’s mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost. PMID:28098748

Building Intrusion Detection with a Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Wälchli, Markus; Braun, Torsten

This paper addresses the detection and reporting of abnormal building access with a wireless sensor network. A common office room, offering space for two working persons, has been monitored with ten sensor nodes and a base station. The task of the system is to report suspicious office occupation such as office searching by thieves. On the other hand, normal office occupation should not throw alarms. In order to save energy for communication, the system provides all nodes with some adaptive short-term memory. Thus, a set of sensor activation patterns can be temporarily learned. The local memory is implemented as an Adaptive Resonance Theory (ART) neural network. Unknown event patterns detected on sensor node level are reported to the base station, where the system-wide anomaly detection is performed. The anomaly detector is lightweight and completely self-learning. The system can be run autonomously or it could be used as a triggering system to turn on an additional high-resolution system on demand. Our building monitoring system has proven to work reliably in different evaluated scenarios. Communication costs of up to 90% could be saved compared to a threshold-based approach without local memory.

TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks

USGS Publications Warehouse

Song, W.-Z.; Huang, R.; Shirazi, B.; LaHusen, R.

2009-01-01

Earlier sensor network MAC protocols focus on energy conservation in low-duty cycle applications, while some recent applications involve real-time high-data-rate signals. This motivates us to design an innovative localized TDMA MAC protocol to achieve high throughput and low congestion in data collection sensor networks, besides energy conservation. TreeMAC divides a time cycle into frames and each frame into slots. A parent node determines the children's frame assignment based on their relative bandwidth demand, and each node calculates its own slot assignment based on its hop-count to the sink. This innovative 2-dimensional frame-slot assignment algorithm has the following nice theory properties. First, given any node, at any time slot, there is at most one active sender in its neighborhood (including itself). Second, the packet scheduling with TreeMAC is bufferless, which therefore minimizes the probability of network congestion. Third, the data throughput to the gateway is at least 1/3 of the optimum assuming reliable links. Our experiments on a 24-node testbed show that TreeMAC protocol significantly improves network throughput, fairness, and energy efficiency compared to TinyOS's default CSMA MAC protocol and a recent TDMA MAC protocol Funneling-MAC. Partial results of this paper were published in Song, Huang, Shirazi and Lahusen [W.-Z. Song, R. Huang, B. Shirazi, and R. Lahusen, TreeMAC: Localized TDMA MAC protocol for high-throughput and fairness in sensor networks, in: The 7th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom, March 2009]. Our new contributions include analyses of the performance of TreeMAC from various aspects. We also present more implementation detail and evaluate TreeMAC from other aspects. ?? 2009 Elsevier B.V.

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications

PubMed Central

Antolín, Diego; Medrano, Nicolás; Calvo, Belén; Pérez, Francisco

2017-01-01

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers. PMID:28216556

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications.

PubMed

Antolín, Diego; Medrano, Nicolás; Calvo, Belén; Pérez, Francisco

2017-02-14

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO₂ concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.

UGV navigation in wireless sensor and actuator network environments

NASA Astrophysics Data System (ADS)

Zhang, Guyu; Li, Jianfeng; Duncan, Christian A.; Kanno, Jinko; Selmic, Rastko R.

2012-06-01

We consider a navigation problem in a distributed, self-organized and coordinate-free Wireless Sensor and Ac- tuator Network (WSAN). We rst present navigation algorithms that are veried using simulation results. Con- sidering more than one destination and multiple mobile Unmanned Ground Vehicles (UGVs), we introduce a distributed solution to the Multi-UGV, Multi-Destination navigation problem. The objective of the solution to this problem is to eciently allocate UGVs to dierent destinations and carry out navigation in the network en- vironment that minimizes total travel distance. The main contribution of this paper is to develop a solution that does not attempt to localize either the UGVs or the sensor and actuator nodes. Other than some connectivity as- sumptions about the communication graph, we consider that no prior information about the WSAN is available. The solution presented here is distributed, and the UGV navigation is solely based on feedback from neigh- boring sensor and actuator nodes. One special case discussed in the paper, the Single-UGV, Multi-Destination navigation problem, is essentially equivalent to the well-known and dicult Traveling Salesman Problem (TSP). Simulation results are presented that illustrate the navigation distance traveled through the network. We also introduce an experimental testbed for the realization of coordinate-free and localization-free UGV navigation. We use the Cricket platform as the sensor and actuator network and a Pioneer 3-DX robot as the UGV. The experiments illustrate the UGV navigation in a coordinate-free WSAN environment where the UGV successfully arrives at the assigned destinations.

Improved Object Localization Using Accurate Distance Estimation in Wireless Multimedia Sensor Networks

PubMed Central

Ur Rehman, Yasar Abbas; Tariq, Muhammad; Khan, Omar Usman

2015-01-01

Object localization plays a key role in many popular applications of Wireless Multimedia Sensor Networks (WMSN) and as a result, it has acquired a significant status for the research community. A significant body of research performs this task without considering node orientation, object geometry and environmental variations. As a result, the localized object does not reflect the real world scenarios. In this paper, a novel object localization scheme for WMSN has been proposed that utilizes range free localization, computer vision, and principle component analysis based algorithms. The proposed approach provides the best possible approximation of distance between a wmsn sink and an object, and the orientation of the object using image based information. Simulation results report 99% efficiency and an error ratio of 0.01 (around 1 ft) when compared to other popular techniques. PMID:26528919

Assessing the Performance of a Network of Low Cost Particulate Matter Sensors Deployed in Sacramento, California

NASA Astrophysics Data System (ADS)

Mukherjee, A. D.; Brown, S. G.; McCarthy, M. C.

2017-12-01

A new generation of low cost air quality sensors have the potential to provide valuable information on the spatial-temporal variability of air pollution - if the measurements have sufficient quality. This study examined the performance of a particulate matter sensor model, the AirBeam (HabitatMap Inc., Brooklyn, NY), over a three month period in the urban environment of Sacramento, California. Nineteen AirBeam sensors were deployed at a regulatory air monitoring site collocated with meteorology measurements and as a local network over an 80 km2 domain in Sacramento, CA. This study presents the methodology to evaluate the precision, accuracy, and reliability of the sensors over a range of meteorological and aerosol conditions. The sensors demonstrated a robust degree of precision during collocated measurement periods (R2 = 0.98 - 0.99) and a moderate degree of correlation against a Beta Attenuation Monitor PM2.5 monitor (R2 0.6). A normalization correction is applied during the study period so that each AirBeam sensor in the network reports a comparable value. The role of the meteorological environment on the accuracy of the sensor measurements is investigated, along with the possibility of improving the measurements through a meteorology weighted correction. The data quality of the network of sensors is examined, and the spatial variability of particulate matter through the study domain derived from the sensor network is presented.

Application-oriented programming model for sensor networks embedded in the human body.

PubMed

Barbosa, Talles M G de A; Sene, Iwens G; da Rocha, Adson F; Nascimento, Fransisco A de O; Carvalho, Hervaldo S; Camapum, Juliana F

2006-01-01

This work presents a new programming model for sensor networks embedded in the human body which is based on the concept of multi-programming application-oriented software. This model was conceived with a top-down approach of four layers and its main goal is to allow the healthcare professionals to program and to reconfigure the network locally or by the Internet. In order to evaluate this hypothesis, a benchmarking was executed in order to allow the assessment of the mean time spent in the programming of a multi-functional sensor node used for the measurement and transmission of the electrocardiogram.

Anchor-Free Localization Method for Mobile Targets in Coal Mine Wireless Sensor Networks

PubMed Central

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes’ location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines. PMID:22574048

Anchor-free localization method for mobile targets in coal mine wireless sensor networks.

PubMed

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes' location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines.

Whisper: Local Secret Maintenance in Sensor Networks

DTIC Science & Technology

2003-02-01

networks, such as Balfanz et al. [1] and Hubaux et al. [9]; these works also use asymmetric cryptography while we use the less expensive symmetric... Balfanz , D. K. Smetters, P. Stewart and H. Chi Wong. Talking to strangers: authentication in ad-hoc wireless network. Symposium on Network and Distributed

A Low Cost High Density Sensor Network for Air Quality at London Heathrow Airport

NASA Astrophysics Data System (ADS)

Bright, V.; Mead, M. I.; Popoola, O. A.; Baron, R. P.; Saffell, J.; Stewart, G.; Kaye, P.; Jones, R.

2012-12-01

Atmospheric composition within urban areas has a direct effect on the air quality of an environment in which a large majority of people live and work. Atmospheric pollutants including ozone (O3), nitrogen dioxide (NO2), volatile organic compounds (VOCs) and particulate matter (PM) can have a significant effect on human health. As such it is important to determine the potential exposure of individuals to these atmospheric constituents and investigate the processes that lead to the degradation of air quality within the urban environment. Whilst modelled pollutant levels on the local scale often suggest high degrees of spatial and temporal variability, the relatively sparse fixed site automated urban networks only provide low spatial resolution data that do not appear adequate in detecting such small scale variability. In this paper we demonstrate that measurements can now be made using networks of low-cost sensors that utilise a variety of techniques, including electrochemical and optical, to measure concentrations of atmospheric species. Once equipped with GPS and GPRS to determine position and transmit data respectively, these networks have the potential to provide valuable insights into pollutant variability inherent on the local or micro-scale. The methodology has been demonstrated successfully in field campaigns carried out in cities including London and Valencia, and is now being deployed as part of the Sensor Networks for Air Quality currently deployed at London Heathrow airport (SNAQ-Heathrow) which is outlined in the partner paper presented by Mead et al. (this conference). The SNAQ-Heathrow network of 50 sensor nodes will provide an unprecedented data set that includes measurements of O3, NO, NO2, CO, CO2, SO2, total VOCs, size-speciated PM as well as meteorological variables that include temperature, relative humidity, wind speed and direction. This network will provide high temporal (20 second intervals) and spatial (50 sites within the airport area) resolution data over a 12 month period with data transmitted back to a server every 2 hours. In this paper we present the data capture and storage, data accessibility, data mining and visualisation techniques applied to the measurements of the SNAQ Heathrow high density sensor network, the preliminary results of which provide an insight into the potential use of such networks in characterising air quality, emissions and validating dispersion models on local scales. We also present a web based interface developed for the sensor network that allows users to access archived data and assess meteorological conditions, atmospheric dispersion, pollutant levels and emission rates.

Automated Information System (AIS) Alarm System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunteman, W.

1997-05-01

The Automated Information Alarm System is a joint effort between Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratory to demonstrate and implement, on a small-to-medium sized local area network, an automated system that detects and automatically responds to attacks that use readily available tools and methodologies. The Alarm System will sense or detect, assess, and respond to suspicious activities that may be detrimental to information on the network or to continued operation of the network. The responses will allow stopping, isolating, or ejecting the suspicious activities. The number of sensors, the sensitivity of the sensors, themore » assessment criteria, and the desired responses may be set by the using organization to meet their local security policies.« less

Energy efficient wireless sensor network for structural health monitoring using distributed embedded piezoelectric transducers

NASA Astrophysics Data System (ADS)

Li, Peng; Olmi, Claudio; Song, Gangbing

2010-04-01

Piezoceramic based transducers are widely researched and used for structural health monitoring (SHM) systems due to the piezoceramic material's inherent advantage of dual sensing and actuation. Wireless sensor network (WSN) technology benefits from advances made in piezoceramic based structural health monitoring systems, allowing easy and flexible installation, low system cost, and increased robustness over wired system. However, piezoceramic wireless SHM systems still faces some drawbacks, one of these is that the piezoceramic based SHM systems require relatively high computational capabilities to calculate damage information, however, battery powered WSN sensor nodes have strict power consumption limitation and hence limited computational power. On the other hand, commonly used centralized processing networks require wireless sensors to transmit all data back to the network coordinator for analysis. This signal processing procedure can be problematic for piezoceramic based SHM applications as it is neither energy efficient nor robust. In this paper, we aim to solve these problems with a distributed wireless sensor network for piezoceramic base structural health monitoring systems. Three important issues: power system, waking up from sleep impact detection, and local data processing, are addressed to reach optimized energy efficiency. Instead of sweep sine excitation that was used in the early research, several sine frequencies were used in sequence to excite the concrete structure. The wireless sensors record the sine excitations and compute the time domain energy for each sine frequency locally to detect the energy change. By comparing the data of the damaged concrete frame with the healthy data, we are able to find out the damage information of the concrete frame. A relative powerful wireless microcontroller was used to carry out the sampling and distributed data processing in real-time. The distributed wireless network dramatically reduced the data transmission between wireless sensor and the wireless coordinator, which in turn reduced the power consumption of the overall system.

Estimation of distributed Fermat-point location for wireless sensor networking.

PubMed

Huang, Po-Hsian; Chen, Jiann-Liang; Larosa, Yanuarius Teofilus; Chiang, Tsui-Lien

2011-01-01

This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.

Imaging the atmosphere using volcanic infrasound recorded on a dense local sensor network

NASA Astrophysics Data System (ADS)

Marcillo, O. E.; Johnson, J. B.; Johnson, R.

2010-12-01

We deployed a 47-node infrasound sensor network around Kilauea’s Halemaumau Vent to image the atmospheric conditions of the near-surface. This active vent is a persistent radiator of energetic infrasound enabling us to probe atmospheric winds and temperatures. This research builds upon a previous experiment that recorded infrasound on a three-node network, to determine relative phase delay and invert for atmospheric wind. The technique developed for this previous analysis assumed the intrinsic sound speed and was able to track the evolution of the average wind field in a large area (around 10 km2) and was largely insensitive to local meteorological effects, caused by topography and vegetation. The results of this previous experiment showed the potential of this technique for atmospheric studies and called for a following experiment with a denser sensor network over a larger area. During the summer 2010, we returned to Kilauea and deployed a 47-sensor network in three different configurations around Kilauea summit and down the volcano’s flanks. Persistent infrasonic tremor was ‘loud’ with excess pressures up to 10 Pa (when scaled to 1 km) and periods of high acoustic emissions that lasted from hours to days. The instrumentation for this experiment was composed of single-channel RefTek RT125A Texan digitizers and InfraNMT infrasound sensors. The Texan digitizers provide high-resolution 24-bit analog to digital conversion and can operate continuously for approximately five days with two D-cell batteries. The InfraNMT sensor is based on a piezo-electric transducer and was developed at the Infrasound Laboratory at New Mexico Tech. This sensor features low power (< 3 mA at 9 V) and flat response between 0.02 to 50 Hz. Three different network topologies were tested during this two-week experiment. For the first and second topologies, the sensors were deployed along established roads on two almost perpendicular sensor lines centered at the Halema’uma’u crater. The furthest sensors were located at ~24 km and ~10 km from the vent respectively. Numerical analysis indicates that these two configurations will be able to probe the atmospheric conditions up to 2 km above the ground. The third topology featured most of the sensors on the summit crater at similar radial distances (2-4 km) and different azimuths. The data collected with the third topology is expected to provide detailed information of the very-local infrasonic field. Each configuration was on the ground and operational for around 84 hours. This full dataset will provide an opportunity to investigate source phenomenology and/or propagation effects of the infrasonic field. Tomographic studies of the atmosphere are expected to provide meteorological data that will be of value for ash and gas propagation models.

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

PubMed Central

Teng, Rui; Leibnitz, Kenji; Miura, Ryu

2013-01-01

An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner. PMID:23748172

A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications.

PubMed

Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

2016-08-06

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.

A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications

PubMed Central

Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

2016-01-01

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively. PMID:27509495

Local Spatial Obesity Analysis and Estimation Using Online Social Network Sensors.

PubMed

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

2018-03-15

Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively. Copyright © 2018. Published by Elsevier Inc.

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks.

PubMed

Zhang, Jing; Liu, Shi-Jian; Tsai, Pei-Wei; Zou, Fu-Min; Ji, Xiao-Rong

2018-01-01

Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods.

TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks

USGS Publications Warehouse

Song, W.-Z.; Huang, R.; Shirazi, B.; Husent, R.L.

2009-01-01

Earlier sensor network MAC protocols focus on energy conservation in low-duty cycle applications, while some recent applications involve real-time high-data-rate signals. This motivates us to design an innovative localized TDMA MAC protocol to achieve high throughput and low congestion in data collection sensor networks, besides energy conservation. TreeMAC divides a time cycle into frames and frame into slots. Parent determines children's frame assigmnent based on their relative bandwidth demand, and each node calculates its own slot assignment based on its hop-count to the sink. This innovative 2-dimensional frame-slot assignment algorithm has the following nice theory properties. Firstly, given any node, at any time slot, there is at most one active sender in its neighborhood (includ ing itself). Secondly, the packet scheduling with TreelMAC is bufferless, which therefore minimizes the probability of network congestion. Thirdly, the data throughput to gateway is at least 1/3 of the optimum assuming reliable links. Our experiments on a 24 node test bed demonstrate that TreeMAC protocol significantly improves network throughput and energy efficiency, by comparing to the TinyOS's default CSMA MAC protocol and a recent TDMA MAC protocol Funneling-MAC[8]. ?? 2009 IEEE.

Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge

PubMed Central

Ding, Chao; Yang, Lijun; Wu, Meng

2017-01-01

Due to the unattended nature and poor security guarantee of the wireless sensor networks (WSNs), adversaries can easily make replicas of compromised nodes, and place them throughout the network to launch various types of attacks. Such an attack is dangerous because it enables the adversaries to control large numbers of nodes and extend the damage of attacks to most of the network with quite limited cost. To stop the node replica attack, we propose a location similarity-based detection scheme using deployment knowledge. Compared with prior solutions, our scheme provides extra functionalities that prevent replicas from generating false location claims without deploying resource-consuming localization techniques on the resource-constraint sensor nodes. We evaluate the security performance of our proposal under different attack strategies through heuristic analysis, and show that our scheme achieves secure and robust replica detection by increasing the cost of node replication. Additionally, we evaluate the impact of network environment on the proposed scheme through theoretic analysis and simulation experiments, and indicate that our scheme achieves effectiveness and efficiency with substantially lower communication, computational, and storage overhead than prior works under different situations and attack strategies. PMID:28098846

Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

NASA Astrophysics Data System (ADS)

Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

2015-06-01

Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge.

PubMed

Ding, Chao; Yang, Lijun; Wu, Meng

2017-01-15

Due to the unattended nature and poor security guarantee of the wireless sensor networks (WSNs), adversaries can easily make replicas of compromised nodes, and place them throughout the network to launch various types of attacks. Such an attack is dangerous because it enables the adversaries to control large numbers of nodes and extend the damage of attacks to most of the network with quite limited cost. To stop the node replica attack, we propose a location similarity-based detection scheme using deployment knowledge. Compared with prior solutions, our scheme provides extra functionalities that prevent replicas from generating false location claims without deploying resource-consuming localization techniques on the resource-constraint sensor nodes. We evaluate the security performance of our proposal under different attack strategies through heuristic analysis, and show that our scheme achieves secure and robust replica detection by increasing the cost of node replication. Additionally, we evaluate the impact of network environment on the proposed scheme through theoretic analysis and simulation experiments, and indicate that our scheme achieves effectiveness and efficiency with substantially lower communication, computational, and storage overhead than prior works under different situations and attack strategies.

Community Air Sensor Network (CAIRSENSE) project ...

EPA Pesticide Factsheets

Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorihm to im

Mobile Context Provider for Social Networking

NASA Astrophysics Data System (ADS)

Santos, André C.; Cardoso, João M. P.; Ferreira, Diogo R.; Diniz, Pedro C.

The ability to infer user context based on a mobile device together with a set of external sensors opens up the way to new context-aware services and applications. In this paper, we describe a mobile context provider that makes use of sensors available in a smartphone as well as sensors externally connected via bluetooth. We describe the system architecture from sensor data acquisition to feature extraction, context inference and the publication of context information to well-known social networking services such as Twitter and Hi5. In the current prototype, context inference is based on decision trees, but the middleware allows the integration of other inference engines. Experimental results suggest that the proposed solution is a promising approach to provide user context to both local and network-level services.

Information-Theoretic Performance Analysis of Sensor Networks via Markov Modeling of Time Series Data.

PubMed

Li, Yue; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Yue Li; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Wettergren, Thomas A; Li, Yue; Ray, Asok; Jha, Devesh K

2018-06-01

This paper presents information-theoretic performance analysis of passive sensor networks for detection of moving targets. The proposed method falls largely under the category of data-level information fusion in sensor networks. To this end, a measure of information contribution for sensors is formulated in a symbolic dynamics framework. The network information state is approximately represented as the largest principal component of the time series collected across the network. To quantify each sensor's contribution for generation of the information content, Markov machine models as well as x-Markov (pronounced as cross-Markov) machine models, conditioned on the network information state, are constructed; the difference between the conditional entropies of these machines is then treated as an approximate measure of information contribution by the respective sensors. The x-Markov models represent the conditional temporal statistics given the network information state. The proposed method has been validated on experimental data collected from a local area network of passive sensors for target detection, where the statistical characteristics of environmental disturbances are similar to those of the target signal in the sense of time scale and texture. A distinctive feature of the proposed algorithm is that the network decisions are independent of the behavior and identity of the individual sensors, which is desirable from computational perspectives. Results are presented to demonstrate the proposed method's efficacy to correctly identify the presence of a target with very low false-alarm rates. The performance of the underlying algorithm is compared with that of a recent data-driven, feature-level information fusion algorithm. It is shown that the proposed algorithm outperforms the other algorithm.

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

NASA Astrophysics Data System (ADS)

Downey, Austin; Laflamme, Simon; Ubertini, Filippo

2016-12-01

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.

Time-optimum packet scheduling for many-to-one routing in wireless sensor networks

USGS Publications Warehouse

Song, W.-Z.; Yuan, F.; LaHusen, R.; Shirazi, B.

2007-01-01

This paper studies the wireless sensor networks (WSN) application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is time-optimum and costs [image omitted], N(u0)-1) time slots, assuming each node reports one unit of data in each round. Here [image omitted] is the total number of sensors, while [image omitted] denotes the number of sensors in a sink's largest branch subtree. With a few adjustments, we then show that our algorithm also achieves time-optimum scheduling in heterogeneous scenarios, where each sensor reports a heterogeneous amount of data in each round. Then we give a distributed implementation to let each node calculate its duty-cycle locally and maximize efficiency globally. In this packet-scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also mitigated. Finally, simulations are conducted to evaluate network performance using the Qualnet simulator. Among other contributions, our study also identifies the maximum reporting frequency that a deployed sensor network can handle.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology.

PubMed

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W; Navarro, Miguel; Li, Yimei; Slater, Thomas A; Liang, Yao; Liang, Xu

2017-03-20

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology

PubMed Central

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W.; Navarro, Miguel; Li, Yimei; Slater, Thomas A.; Liang, Yao; Liang, Xu

2017-01-01

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments. PMID:28335534

Learning a detection map for a network of unattended ground sensors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Hung D.; Koch, Mark William

2010-03-01

We have developed algorithms to automatically learn a detection map of a deployed sensor field for a virtual presence and extended defense (VPED) system without apriori knowledge of the local terrain. The VPED system is an unattended network of sensor pods, with each pod containing acoustic and seismic sensors. Each pod has the ability to detect and classify moving targets at a limited range. By using a network of pods we can form a virtual perimeter with each pod responsible for a certain section of the perimeter. The site's geography and soil conditions can affect the detection performance of themore » pods. Thus, a network in the field may not have the same performance as a network designed in the lab. To solve this problem we automatically estimate a network's detection performance as it is being installed at a site by a mobile deployment unit (MDU). The MDU will wear a GPS unit, so the system not only knows when it can detect the MDU, but also the MDU's location. In this paper, we demonstrate how to handle anisotropic sensor-configurations, geography, and soil conditions.« less

Distributed wireless sensing for methane leak detection technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Levente; van Kesse, Theodor

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Distributed wireless sensing for fugitive methane leak detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Distributed wireless sensing for fugitive methane leak detection

DOE PAGES

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv; ...

2017-12-11

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Investigation of the infrasound produced by geophysical events such as volcanoes, thunder, and avalanches: the case for local infrasound monitoring (Invited)

NASA Astrophysics Data System (ADS)

Johnson, J. B.; Marcillo, O. E.; Arechiga, R. O.; Johnson, R.; Edens, H. E.; Marshall, H.; Havens, S.; Waite, G. P.

2010-12-01

Volcanoes, lightning, and mass wasting events generate substantial infrasonic energy that propagates for long distances through the atmosphere with generally low intrinsic attenuation. Although such sources are often studied with regional infrasound arrays that provide important records of their occurrence, position, and relative magnitudes these signals recorded at tens to hundreds of kilometers are often significantly affected by propagation effects. Complex atmospheric structure, due to heterogeneous winds and temperatures, and intervening topography can be responsible for multi-pathing, signal attenuation, and focusing or, alternatively, information loss (i.e., a shadow zone). At far offsets, geometric spreading diminishes signal amplitude requiring low noise recording sites and high fidelity microphones. In contrast recorded excess pressures at local distances are much higher in amplitude and waveforms are more representative of source phenomena. We report on recent studies of volcanoes, thunder, and avalanches made with networks and arrays of infrasound sensors deployed local (within a few km) to the source. At Kilauea Volcano (Hawaii) we deployed a network of ~50 infrasound sensitive sensors (flat from 50 s to 50 Hz) to track the coherence of persistent infrasonic tremor signals in the near-field (out to a few tens of kilometers). During periods of high winds (> 5-10 m/s) we found significant atmospheric influence for signals recorded at stations only a few kilometers from the source. Such observations have encouraged us to conduct a range of volcano, thunder, and snow avalanche studies with networks of small infrasound arrays (~30 m aperture) deployed close to the source region. We present results from local microphone deployments (12 sensors) at Santiaguito Volcano (Guatemala) where we are able to precisely (~10 m resolution) locate acoustic sources from explosions and rock falls. We also present results from our thunder mapping acoustic arrays (15 sensors) in the Magdalena Mountains of New Mexico capable of mapping lightning channels more than 10 km in extent whose positions are corroborated by the radio wave detecting lightning mapping array. We also discuss the recent implementation of a network of snow avalanche detection arrays (12 sensors) in Idaho that are used to monitor and track and map infrasound produced by moving sources. We contend that local infrasound deployment is analogous to local seismic monitoring in that it enables precision localization and interpretation of source phenomena.

Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

NASA Astrophysics Data System (ADS)

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 of sensor positioning for measuring soil moisture are scopes of this work and initial results of these issues will be presented.

Underwater Threat Source Localization: Processing Sensor Network TDOAs with a Terascale Optical Core Device

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barhen, Jacob; Imam, Neena

2007-01-01

Revolutionary computing technologies are defined in terms of technological breakthroughs, which leapfrog over near-term projected advances in conventional hardware and software to produce paradigm shifts in computational science. For underwater threat source localization using information provided by a dynamical sensor network, one of the most promising computational advances builds upon the emergence of digital optical-core devices. In this article, we present initial results of sensor network calculations that focus on the concept of signal wavefront time-difference-of-arrival (TDOA). The corresponding algorithms are implemented on the EnLight processing platform recently introduced by Lenslet Laboratories. This tera-scale digital optical core processor is optimizedmore » for array operations, which it performs in a fixed-point-arithmetic architecture. Our results (i) illustrate the ability to reach the required accuracy in the TDOA computation, and (ii) demonstrate that a considerable speed-up can be achieved when using the EnLight 64a prototype processor as compared to a dual Intel XeonTM processor.« less

Networked gamma radiation detection system for tactical deployment

NASA Astrophysics Data System (ADS)

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.

System identification of a tied arch bridge using reference-based wireless sensor networks

NASA Astrophysics Data System (ADS)

Hietbrink, Colby; Whelan, Matthew J.

2012-04-01

Vibration-based methods of structural health monitoring are generally founded on the principle that localized damage to a structure would exhibit changes within the global dynamic response. Upon this basis, accelerometers provide a unique health monitoring strategy in that a distributed network of sensors provides the technical feasibility to isolate the onset of damage without requiring that any sensor be located exactly on or in close proximity to the damage. While in theory this may be sufficient, practical experience has shown significant improvement in the application of damage diagnostic routines when mode shapes characterized by strongly localized behavior of specific elements are captured by the instrumentation array. In traditional applications, this presents a challenge since the cost and complexity of cable-based systems often effectively limits the number of instrumented locations thereby constraining the modal parameter extraction to only global modal responses. The advent of the low-cost RF chip transceiver with wireless networking capabilities has afforded a means by which a substantial number of output locations can be measured through referencebased testing using large-scale wireless sensor networks. In the current study, this approach was applied to the Prairie du Chien Bridge over the Mississippi River to extract operational mode shapes with high spatial reconstruction, including strongly localized modes. The tied arch bridge was instrumented at over 230 locations with single-axis accelerometers conditioned and acquired over a high-rate lossless wireless sensor network with simultaneous sampling capabilities. Acquisition of the dynamic response of the web plates of the arch rib was specifically targeted within the instrumentation array for diagnostic purposes. Reference-based operational modal analysis of the full structure through data-driven stochastic subspace identification is presented alongside finite element analysis results for confirmation of modal parameter plausibility. Particular emphasis is placed on the identification and reconstruction of modal response with large contribution from the arch rib web plates.

Localization under Adversary Misdirection

DTIC Science & Technology

2014-10-01

0.5 1 −1 −0.5 0 0.5 1 x [meters] y [m et er s ] (a) eadv = [0 0.05] (b) eadv= [0 0.36] ( c ) eadv = [0 1] Figure 18: Maximum distance...2009. [47] C . Meesookho, U. Mitra, and S . Narayanan. On energy-based acoustic source localization for sensor networks. IEEE Transactions on Signal...Processing, 56(1):365–377, 2008. [48] C . Meng, Z. Ding, and S . Dasgupta. A semidefinite programming approach to source localization in wireless sensor

Localization in Self-Healing Autonomous Sensor Networks (SASNet): Studies on Cooperative Localization of Sensor Nodes using Distributed Maps

DTIC Science & Technology

2008-01-01

CCA-MAP algorithm are analyzed. Further, we discuss the design considerations of the discussed cooperative localization algorithms to compare and...MAP and CCA-MAP to compare and evaluate their performance. Then a preliminary design analysis is given to address the implementation requirements and...plus précis, avec un nombre inférieur de nœuds ancres, comparativement aux autres types de schémas de localisation. En réalité, les algorithmes de

Potentials and Limitations of Wireless Sensor Networks for Environmental

NASA Astrophysics Data System (ADS)

Bumberger, J.; Remmler, P.; Hutschenreuther, T.; Toepfer, H.; Dietrich, P.

2013-12-01

Understanding and dealing with environmental challenges worldwide requires suitable interdisciplinary methods and a level of expertise to be able to implement these solutions, so that the lifestyles of future generations can be secured in the years to come. To characterize environmental systems it is necessary to identify and describe processes with suitable methods. Environmental systems are often characterized by their high heterogeneity, so individual measurements for their complete representation are often not sufficient. The application of wireless sensor networks in terrestrial and aquatic ecosystems offer significant benefits as a better consideration of the local test conditions becomes possible. This can be essential for the monitoring of heterogeneous environmental systems. Significant advantages in the application of wireless sensor networks are their self-organizing behaviour, resulting in a major reduction in installation and operation costs and time. In addition, a point measurement with a sensor is significantly improved by measuring at several points. It is also possible to perform analog and digital signal processing and computation on the basis of the measured data close to the sensor. Hence, a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of sensor nodes. Furthermore, their localization via satellite, the miniaturization of the nodes and long-term energy self-sufficiency are current topics under investigation. In this presentation, the possibilities and limitations of the applicability of wireless sensor networks for long-term environmental monitoring are presented. To underline the importance of this future technology, example concepts are given in the field of near-surface geothermics, groundwater observation, measurement of spatial radiation intensity and air humidity on soils, measurement of matter fluxes, greenhouse gas measurement, and landslide monitoring.

Wake-up transceivers for structural health monitoring of bridges

NASA Astrophysics Data System (ADS)

Kumberg, T.; Kokert, J.; Younesi, V.; Koenig, S.; Reindl, L. M.

2016-04-01

In this article we present a wireless sensor network to monitor the structural health of a large-scale highway bridge in Germany. The wireless sensor network consists of several sensor nodes that use wake-up receivers to realize latency free and low-power communication. The sensor nodes are either equipped with very accurate tilt sensor developed by Northrop Grumman LITEF GmbH or with a Novatel OEM615 GNSS receiver. Relay nodes are required to forward measurement data to a base station located on the bridge. The base station is a gateway that transmits the local measurement data to a remote server where it can be further analyzed and processed. Further on, we present an energy harvesting system to supply the energy demanding GNSS sensor nodes to realize long term monitoring.

Chain-Based Communication in Cylindrical Underwater Wireless Sensor Networks

PubMed Central

Javaid, Nadeem; Jafri, Mohsin Raza; Khan, Zahoor Ali; Alrajeh, Nabil; Imran, Muhammad; Vasilakos, Athanasios

2015-01-01

Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs). Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS) and Congestion adjusted PEGASIS (C-PEGASIS). Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate. PMID:25658394

Real-time indoor monitoring system based on wireless sensor networks

NASA Astrophysics Data System (ADS)

Wu, Zhengzhong; Liu, Zilin; Huang, Xiaowei; Liu, Jun

2008-10-01

Wireless sensor networks (WSN) greatly extend our ability to monitor and control the physical world. It can collaborate and aggregate a huge amount of sensed data to provide continuous and spatially dense observation of environment. The control and monitoring of indoor atmosphere conditions represents an important task with the aim of ensuring suitable working and living spaces to people. However, the comprehensive air quality, which includes monitoring of humidity, temperature, gas concentrations, etc., is not so easy to be monitored and controlled. In this paper an indoor WSN monitoring system was developed. In the system several sensors such as temperature sensor, humidity sensor, gases sensor, were built in a RF transceiver board for monitoring indoor environment conditions. The indoor environmental monitoring parameters can be transmitted by wireless to database server and then viewed throw PC or PDA accessed to the local area networks by administrators. The system, which was also field-tested and showed a reliable and robust characteristic, is significant and valuable to people.

Rapid-response Sensor Networks Leveraging Open Standards and the Internet of Things

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Lieberman, J. E.; Lewis, L.; Botts, M.; Liang, S.

2016-12-01

New sensor technologies provide an unparalleled capability to collect large numbers of diverse observations about the world around us. Networks of such sensors are especially effective for capturing and analyzing unexpected, fast moving events if they can be deployed with a minimum of time, effort, and cost. A rapid-response sensing and processing capability is extremely important in quickly unfolding events not only to collect data for future research.but also to support response efforts that may be needed by providing up-to-date knowledge of the situation. A recent pilot activity coordinated by the Open Geospatial Consortium combined Sensor Web Enablement (SWE) standards with Internet of Things (IoT) practices to understand better how to set up rapid-response sensor networks in comparable event situations involving accidents or disasters. The networks included weather and environmental sensors, georeferenced UAV and PTZ imagery collectors, and observations from "citizen sensors", as well as virtual observations generated by predictive models. A key feature of each "SWE-IoT" network was one or more Sensor Hubs that connected local, often proprietary sensor device protocols to a common set of standard SWE data types and standard Web interfaces on an IP-based internetwork. This IoT approach provided direct, common, interoperable access to all sensor readings from anywhere on the internetwork of sensors, Hubs, and applications. Sensor Hubs also supported an automated discovery protocol in which activated Hubs registered themselves with a canonical catalog service. As each sensor (wireless or wired) was activated within range of an authorized Hub, it registered itself with that Hub, which in turn registered the sensor and its capabilities with the catalog. Sensor Hub functions were implemented in a range of component types, from personal devices such as smartphones and Raspberry Pi's to full cloud-based sensor services platforms. Connected into a network "constellation" the Hubs also enabled reliable exchange and persistence of sensor data in constrained communications environments. Pilot results are being documented in public OGC engineering reports and are feeding into improved standards to support SWE-IoT networks for a range of domains and applications.

Analysis of Energy Consumption for Ad Hoc Wireless Sensor Networks Using a Bit-Meter-per-Joule Metric

NASA Astrophysics Data System (ADS)

Gao, J. L.

2002-04-01

In this article, we present a system-level characterization of the energy consumption for sensor network application scenarios. We compute a power efficiency metric -- average watt-per-meter -- for each radio transmission and extend this local metric to find the global energy consumption. This analysis shows how overall energy consumption varies with transceiver characteristics, node density, data traffic distribution, and base-station location.

Sensor network based solar forecasting using a local vector autoregressive ridge framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, J.; Yoo, S.; Heiser, J.

2016-04-04

The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations duemore » to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.« less

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks

PubMed Central

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-01-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites’ operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95.1% of the cases. PMID:28368319

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks.

PubMed

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-04-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites' operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95 . 1 % of the cases.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.

PubMed

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-05-21

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-01-01

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods. PMID:29883410

I-DWRL: Improved Dual Wireless Radio Localization Using Magnetometer.

PubMed

Aziz, Abdul; Kumar, Ramesh; Joe, Inwhee

2017-11-15

In the dual wireless radio localization (DWRL) technique each sensor node is equipped with two ultra-wide band (UWB) radios; the distance between the two radios is a few tens of centimeters. For localization, the DWRL technique must use at least two pre-localized nodes to fully localize an unlocalized node. Moreover, in the DWRL technique it is also not possible for two sensor nodes to properly communicate location information unless each of the four UWB radios of two communicating sensor nodes cannot approach the remaining three radios. In this paper, we propose an improved DWRL (I-DWRL) algorithm along with mounting a magnetometer sensor on one of the UWB radios of all sensor nodes. This addition of a magnetometer helps to improve DWRL algorithm such that only one localized sensor node is required for the localization of an unlocalized sensor node, and localization can also be achieved even when some of the four radios of two nodes are unable to communicate with the remaining three radios. The results show that with the use of a magnetometer a greater number of nodes can be localized with a smaller transmission range, less energy and a shorter period of time. In comparison with the conventional DWRL algorithm, our I-DWRL not only maintains the localization error but also requires around half of semi-localizations, 60% of the time, 70% of the energy and a shorter communication range to fully localize an entire network. Moreover, I-DWRL can even localize more nodes while transmission range is not sufficient for DWRL algorithm.

I-DWRL: Improved Dual Wireless Radio Localization Using Magnetometer

PubMed Central

Aziz, Abdul; Kumar, Ramesh; Joe, Inwhee

2017-01-01

In the dual wireless radio localization (DWRL) technique each sensor node is equipped with two ultra-wide band (UWB) radios; the distance between the two radios is a few tens of centimeters. For localization, the DWRL technique must use at least two pre-localized nodes to fully localize an unlocalized node. Moreover, in the DWRL technique it is also not possible for two sensor nodes to properly communicate location information unless each of the four UWB radios of two communicating sensor nodes cannot approach the remaining three radios. In this paper, we propose an improved DWRL (I-DWRL) algorithm along with mounting a magnetometer sensor on one of the UWB radios of all sensor nodes. This addition of a magnetometer helps to improve DWRL algorithm such that only one localized sensor node is required for the localization of an unlocalized sensor node, and localization can also be achieved even when some of the four radios of two nodes are unable to communicate with the remaining three radios. The results show that with the use of a magnetometer a greater number of nodes can be localized with a smaller transmission range, less energy and a shorter period of time. In comparison with the conventional DWRL algorithm, our I-DWRL not only maintains the localization error but also requires around half of semi-localizations, 60% of the time, 70% of the energy and a shorter communication range to fully localize an entire network. Moreover, I-DWRL can even localize more nodes while transmission range is not sufficient for DWRL algorithm. PMID:29140291

Toward controlling perturbations in robotic sensor networks

NASA Astrophysics Data System (ADS)

Banerjee, Ashis G.; Majumder, Saikat R.

2014-06-01

Robotic sensor networks (RSNs), which consist of networks of sensors placed on mobile robots, are being increasingly used for environment monitoring applications. In particular, a lot of work has been done on simultaneous localization and mapping of the robots, and optimal sensor placement for environment state estimation1. The deployment of RSNs, however, remains challenging in harsh environments where the RSNs have to deal with significant perturbations in the forms of wind gusts, turbulent water flows, sand storms, or blizzards that disrupt inter-robot communication and individual robot stability. Hence, there is a need to be able to control such perturbations and bring the networks to desirable states with stable nodes (robots) and minimal operational performance (environment sensing). Recent work has demonstrated the feasibility of controlling the non-linear dynamics in other communication networks like emergency management systems and power grids by introducing compensatory perturbations to restore network stability and operation2. In this paper, we develop a computational framework to investigate the usefulness of this approach for RSNs in marine environments. Preliminary analysis shows promising performance and identifies bounds on the original perturbations within which it is possible to control the networks.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

Distributed fault detection over sensor networks with Markovian switching topologies

NASA Astrophysics Data System (ADS)

Ge, Xiaohua; Han, Qing-Long

2014-05-01

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.

3D electrode localization on wireless sensor networks for wearable BCI.

PubMed

Figueiredo, C P; Dias, N S; Hoffmann, K P; Mendes, P M

2008-01-01

This paper presents a solution for electrode localization on wearable BCI radio-enabled electrodes. Electrode positioning is a common issue in any electrical physiological recording. Although wireless node localization is a very active research topic, a precise method with few centimeters of range and a resolution in the order of millimeters is still to be found, since far-field measurements are very prone to error. The calculation of 3D coordinates for each electrode is based on anchorless range-based localization algorithms such as Multidimensional Scaling and Self-Positioning Algorithm. The implemented solution relies on the association of a small antenna to measure the magnetic field and a microcontroller to each electrode, which will be part of the wireless sensor network module. The implemented solution is suitable for EEG applications, namely the wearable BCI, with expected range of 20 cm and resolution of 5 mm.

A Hybrid DV-Hop Algorithm Using RSSI for Localization in Large-Scale Wireless Sensor Networks.

PubMed

Cheikhrouhou, Omar; M Bhatti, Ghulam; Alroobaea, Roobaea

2018-05-08

With the increasing realization of the Internet-of-Things (IoT) and rapid proliferation of wireless sensor networks (WSN), estimating the location of wireless sensor nodes is emerging as an important issue. Traditional ranging based localization algorithms use triangulation for estimating the physical location of only those wireless nodes that are within one-hop distance from the anchor nodes. Multi-hop localization algorithms, on the other hand, aim at localizing the wireless nodes that can physically be residing at multiple hops away from anchor nodes. These latter algorithms have attracted a growing interest from research community due to the smaller number of required anchor nodes. One such algorithm, known as DV-Hop (Distance Vector Hop), has gained popularity due to its simplicity and lower cost. However, DV-Hop suffers from reduced accuracy due to the fact that it exploits only the network topology (i.e., number of hops to anchors) rather than the distances between pairs of nodes. In this paper, we propose an enhanced DV-Hop localization algorithm that also uses the RSSI values associated with links between one-hop neighbors. Moreover, we exploit already localized nodes by promoting them to become additional anchor nodes. Our simulations have shown that the proposed algorithm significantly outperforms the original DV-Hop localization algorithm and two of its recently published variants, namely RSSI Auxiliary Ranging and the Selective 3-Anchor DV-hop algorithm. More precisely, in some scenarios, the proposed algorithm improves the localization accuracy by almost 95%, 90% and 70% as compared to the basic DV-Hop, Selective 3-Anchor, and RSSI DV-Hop algorithms, respectively.

Distributed least-squares estimation of a remote chemical source via convex combination in wireless sensor networks.

PubMed

Cao, Meng-Li; Meng, Qing-Hao; Zeng, Ming; Sun, Biao; Li, Wei; Ding, Cheng-Jun

2014-06-27

This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source.

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models

PubMed Central

2018-01-01

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the ‘Internet of Things’ (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds. PMID:29748521

An Efficient Location Verification Scheme for Static Wireless Sensor Networks.

PubMed

Kim, In-Hwan; Kim, Bo-Sung; Song, JooSeok

2017-01-24

In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect location estimation process from attacks, they are not enough to eliminate the wrong location estimations in some situations. The location verification can be the solution to the situations or be the second-line defense. The problem of most of the location verifications is the explicit involvement of many sensors in the verification process and requirements, such as special hardware, a dedicated verifier and the trusted third party, which causes more communication and computation overhead. In this paper, we propose an efficient location verification scheme for static WSN called mutually-shared region-based location verification (MSRLV), which reduces those overheads by utilizing the implicit involvement of sensors and eliminating several requirements. In order to achieve this, we use the mutually-shared region between location claimant and verifier for the location verification. The analysis shows that MSRLV reduces communication overhead by 77% and computation overhead by 92% on average, when compared with the other location verification schemes, in a single sensor verification. In addition, simulation results for the verification of the whole network show that MSRLV can detect the malicious sensors by over 90% when sensors in the network have five or more neighbors.

An Efficient Location Verification Scheme for Static Wireless Sensor Networks

PubMed Central

Kim, In-hwan; Kim, Bo-sung; Song, JooSeok

2017-01-01

In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect location estimation process from attacks, they are not enough to eliminate the wrong location estimations in some situations. The location verification can be the solution to the situations or be the second-line defense. The problem of most of the location verifications is the explicit involvement of many sensors in the verification process and requirements, such as special hardware, a dedicated verifier and the trusted third party, which causes more communication and computation overhead. In this paper, we propose an efficient location verification scheme for static WSN called mutually-shared region-based location verification (MSRLV), which reduces those overheads by utilizing the implicit involvement of sensors and eliminating several requirements. In order to achieve this, we use the mutually-shared region between location claimant and verifier for the location verification. The analysis shows that MSRLV reduces communication overhead by 77% and computation overhead by 92% on average, when compared with the other location verification schemes, in a single sensor verification. In addition, simulation results for the verification of the whole network show that MSRLV can detect the malicious sensors by over 90% when sensors in the network have five or more neighbors. PMID:28125007

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Cheng, M.; Guy, R.; Chandy, M.; Krause, A.; Bunn, J.; Olson, M.; Faulkner, M.

2011-12-01

The CSN is a network of low-cost accelerometers deployed in the Pasadena, CA region. It is a prototype network with the goal of demonstrating the importance of dense measurements in determining the rapid lateral variations in ground motion due to earthquakes. The main product of the CSN is a map of peak ground produced within seconds of significant local earthquakes that can be used as a proxy for damage. Examples of this are shown using data from a temporary network in Long Beach, CA. Dense measurements in buildings are also being used to determine the state of health of structures. In addition to fixed sensors, portable sensors such as smart phones are also used in the network. The CSN has necessitated several changes in the standard design of a seismic network. The first is that the data collection and processing is done in the "cloud" (Google cloud in this case) for robustness and the ability to handle large impulsive loads (earthquakes). Second, the database is highly de-normalized (i.e. station locations are part of waveform and event-detection meta data) because of the mobile nature of the sensors. Third, since the sensors are hosted and/or owned by individuals, the privacy of the data is very important. The location of fixed sensors is displayed on maps as sensor counts in block-wide cells, and mobile sensors are shown in a similar way, with the additional requirement to inhibit tracking that at least two must be present in a particular cell before any are shown. The raw waveform data are only released to users outside of the network after a felt earthquake.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

Adaptive multi-sensor biomimetics for unsupervised submarine hunt (AMBUSH): Early results

NASA Astrophysics Data System (ADS)

Blouin, Stéphane

2014-10-01

Underwater surveillance is inherently difficult because acoustic wave propagation and transmission are limited and unpredictable when targets and sensors move around in the communication-opaque undersea environment. Today's Navy underwater sensors enable the collection of a massive amount of data, often analyzed offtine. The Navy of tomorrow will dominate by making sense of that data in real-time. DRDC's AMBUSH project proposes a new undersea-surveillance network paradigm that will enable such a real-time operation. Nature abounds with examples of collaborative tasks taking place despite limited communication and computational capabilities. This publication describes a year's worth of research efforts finding inspiration in Nature's collaborative tasks such as wolves hunting in packs. This project proposes the utilization of a heterogeneous network combining both static and mobile network nodes. The military objective is to enable an unsupervised surveillance capability while maximizing target localization performance and endurance. The scientific objective is to develop the necessary technology to acoustically and passively localize a noise-source of interest in shallow waters. The project fulfills these objectives via distributed computing and adaptation to changing undersea conditions. Specific research interests discussed here relate to approaches for performing: (a) network self-discovery, (b) network connectivity self-assessment, (c) opportunistic network routing, (d) distributed data-aggregation, and (e) simulation of underwater acoustic propagation. We present early results then followed by a discussion about future work.

Detecting higher-order wavefront errors with an astigmatic hybrid wavefront sensor.

PubMed

Barwick, Shane

2009-06-01

The reconstruction of wavefront errors from measurements over subapertures can be made more accurate if a fully characterized quadratic surface can be fitted to the local wavefront surface. An astigmatic hybrid wavefront sensor with added neural network postprocessing is shown to have this capability, provided that the focal image of each subaperture is sufficiently sampled. Furthermore, complete local curvature information is obtained with a single image without splitting beam power.

Telecommunication Platforms for Transmitting Sensor Data over Communication Networks-State of the Art and Challenges.

PubMed

Staniec, Kamil; Habrych, Marcin

2016-07-19

The importance of constructing wide-area sensor networks for holistic environmental state evaluation has been demonstrated. A general structure of such a network has been presented with distinction of three segments: local (based on ZigBee, Ethernet and ModBus techniques), core (base on cellular technologies) and the storage/application. The implementation of these techniques requires knowledge of their technical limitations and electromagnetic compatibility issues. The former refer to ZigBee performance degradation in multi-hop transmission, whereas the latter are associated with the common electromagnetic spectrum sharing with other existing technologies or with undesired radiated emissions generated by the radio modules of the sensor network. In many cases, it is also necessary to provide a measurement station with autonomous energy source, such as solar. As stems from measurements of the energetic efficiency of these sources, one should apply them with care and perform detailed power budget since their real performance may turn out to be far from expected. This, in turn, may negatively affect-in particular-the operation of chemical sensors implemented in the network as they often require additional heating.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks.

PubMed

Zhang, Guomei; Sun, Hao

2016-12-16

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor's reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

1997-01-01

A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

Aluminum alloy material structure impact localization by using FBG sensors

NASA Astrophysics Data System (ADS)

Zhu, Xiubin

2014-12-01

The aluminum alloy structure impact localization system by using fiber Bragg grating (FBG) sensors and impact localization algorithm was investigated. A four-FBG sensing network was established. And the power intensity demodulation method was initialized employing the narrow-band tunable laser. The wavelet transform was used to weaken the impact signal noise. And the impact signal time difference was extracted to build the time difference localization algorithm. At last, a fiber Bragg grating impact localization system was established and experimentally verified. The experimental results showed that in the aluminum alloy plate with the 500 mm*500 mm*2 mm test area, the maximum and average impact abscissa localization errors were 11 mm and 6.25 mm, and the maximum and average impact ordinate localization errors were 9 mm and 4.25 mm, respectively. The fiber Bragg grating sensors and demodulation system are feasible to realize the aviation aluminum alloy material structure impact localization. The research results provide a reliable method for the aluminum alloy material structure impact localization.

An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor Networks

PubMed Central

Abba, Sani; Lee, Jeong-A

2015-01-01

We propose an autonomous self-aware and adaptive fault-tolerant routing technique (ASAART) for wireless sensor networks. We address the limitations of self-healing routing (SHR) and self-selective routing (SSR) techniques for routing sensor data. We also examine the integration of autonomic self-aware and adaptive fault detection and resiliency techniques for route formation and route repair to provide resilience to errors and failures. We achieved this by using a combined continuous and slotted prioritized transmission back-off delay to obtain local and global network state information, as well as multiple random functions for attaining faster routing convergence and reliable route repair despite transient and permanent node failure rates and efficient adaptation to instantaneous network topology changes. The results of simulations based on a comparison of the ASAART with the SHR and SSR protocols for five different simulated scenarios in the presence of transient and permanent node failure rates exhibit a greater resiliency to errors and failure and better routing performance in terms of the number of successfully delivered network packets, end-to-end delay, delivered MAC layer packets, packet error rate, as well as efficient energy conservation in a highly congested, faulty, and scalable sensor network. PMID:26295236

An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor Networks.

PubMed

Abba, Sani; Lee, Jeong-A

2015-08-18

We propose an autonomous self-aware and adaptive fault-tolerant routing technique (ASAART) for wireless sensor networks. We address the limitations of self-healing routing (SHR) and self-selective routing (SSR) techniques for routing sensor data. We also examine the integration of autonomic self-aware and adaptive fault detection and resiliency techniques for route formation and route repair to provide resilience to errors and failures. We achieved this by using a combined continuous and slotted prioritized transmission back-off delay to obtain local and global network state information, as well as multiple random functions for attaining faster routing convergence and reliable route repair despite transient and permanent node failure rates and efficient adaptation to instantaneous network topology changes. The results of simulations based on a comparison of the ASAART with the SHR and SSR protocols for five different simulated scenarios in the presence of transient and permanent node failure rates exhibit a greater resiliency to errors and failure and better routing performance in terms of the number of successfully delivered network packets, end-to-end delay, delivered MAC layer packets, packet error rate, as well as efficient energy conservation in a highly congested, faulty, and scalable sensor network.

Maturation of Structural Health Management Systems for Solid Rocket Motors

NASA Technical Reports Server (NTRS)

Quing, Xinlin; Beard, Shawn; Zhang, Chang

2011-01-01

Concepts of an autonomous and automated space-compliant diagnostic system were developed for conditioned-based maintenance (CBM) of rocket motors for space exploration vehicles. The diagnostic system will provide real-time information on the integrity of critical structures on launch vehicles, improve their performance, and greatly increase crew safety while decreasing inspection costs. Using the SMART Layer technology as a basis, detailed procedures and calibration techniques for implementation of the diagnostic system were developed. The diagnostic system is a distributed system, which consists of a sensor network, local data loggers, and a host central processor. The system detects external impact to the structure. The major functions of the system include an estimate of impact location, estimate of impact force at impacted location, and estimate of the structure damage at impacted location. This system consists of a large-area sensor network, dedicated multiple local data loggers with signal processing and data analysis software to allow for real-time, in situ monitoring, and longterm tracking of structural integrity of solid rocket motors. Specifically, the system could provide easy installation of large sensor networks, onboard operation under harsh environments and loading, inspection of inaccessible areas without disassembly, detection of impact events and impact damage in real-time, and monitoring of a large area with local data processing to reduce wiring.

An Obstacle-Tolerant Path Planning Algorithm for Mobile-Anchor-Node-Assisted Localization

PubMed Central

Tsai, Rong-Guei

2018-01-01

The location information obtained using a sensor is a critical requirement in wireless sensor networks. Numerous localization schemes have been proposed, among which mobile-anchor-node-assisted localization (MANAL) can reduce costs and overcome environmental constraints. A mobile anchor node (MAN) provides its own location information to assist the localization of sensor nodes. Numerous path planning schemes have been proposed for MANAL, but most scenarios assume the absence of obstacles in the environment. However, in a realistic environment, sensor nodes cannot be located because the obstacles block the path traversed by the MAN, thereby rendering the sensor incapable of receiving sufficient three location information from the MAN. This study proposes the obstacle-tolerant path planning (OTPP) approach to solve the sensor location problem owing to obstacle blockage. OTPP can approximate the optimum beacon point number and path planning, thereby ensuring that all the unknown nodes can receive the three location information from the MAN and reduce the number of MAN broadcast packet times. Experimental results demonstrate that OTPP performs better than Z-curves because it reduces the total number of beacon points utilized and is thus more suitable in an obstacle-present environment. Compared to the Z-curve, OTPP can reduce localization error and improve localization coverage. PMID:29547582

Design optimization of the sensor spatial arrangement in a direct magnetic field-based localization system for medical applications.

PubMed

Marechal, Luc; Shaohui Foong; Zhenglong Sun; Wood, Kristin L

2015-08-01

Motivated by the need for developing a neuronavigation system to improve efficacy of intracranial surgical procedures, a localization system using passive magnetic fields for real-time monitoring of the insertion process of an external ventricular drain (EVD) catheter is conceived and developed. This system operates on the principle of measuring the static magnetic field of a magnetic marker using an array of magnetic sensors. An artificial neural network (ANN) is directly used for solving the inverse problem of magnetic dipole localization for improved efficiency and precision. As the accuracy of localization system is highly dependent on the sensor spatial location, an optimization framework, based on understanding and classification of experimental sensor characteristics as well as prior knowledge of the general trajectory of the localization pathway, for design of such sensing assemblies is described and investigated in this paper. Both optimized and non-optimized sensor configurations were experimentally evaluated and results show superior performance from the optimized configuration. While the approach presented here utilizes ventriculostomy as an illustrative platform, it can be extended to other medical applications that require localization inside the body.

Source Localization in a Cognitive Radio Environment Consisting of Frequency and Spatial Mobility

DTIC Science & Technology

2011-12-01

are designed to track position over time using a wireless RF sensor network, such as Kalman filtering [13]. 74 THIS PAGE INTENTIONALLY LEFT BLANK...Radio,” Proceedings of the IEEE, vol. 97, no. 4, pp. 612–625, Apr. 2009. 80 [12] J. B. Bernthal, T. X. Brown , D. N. Hatfield, D. C. Sicker, P. A... Kalman Filtering in Wireless Sensor Networks,” IEEE Control Systems, vol. 30, no. 2, pp. 66–86, April 2010. [14] J. Nemeroff, L. Garcia, D

A Node Localization Algorithm Based on Multi-Granularity Regional Division and the Lagrange Multiplier Method in Wireless Sensor Networks.

PubMed

Shang, Fengjun; Jiang, Yi; Xiong, Anping; Su, Wen; He, Li

2016-11-18

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed. When the unknown node is inside positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is outside positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

Friend or foe: exploiting sensor failures for transparent object localization and classification

NASA Astrophysics Data System (ADS)

Seib, Viktor; Barthen, Andreas; Marohn, Philipp; Paulus, Dietrich

2017-02-01

In this work we address the problem of detecting and recognizing transparent objects using depth images from an RGB-D camera. Using this type of sensor usually prohibits the localization of transparent objects since the structured light pattern of these cameras is not reflected by transparent surfaces. Instead, transparent surfaces often appear as undefined values in the resulting images. However, these erroneous sensor readings form characteristic patterns that we exploit in the presented approach. The sensor data is fed into a deep convolutional neural network that is trained to classify and localize drinking glasses. We evaluate our approach with four different types of transparent objects. To our best knowledge, no datasets offering depth images of transparent objects exist so far. With this work we aim at closing this gap by providing our data to the public.

Helmet-mounted acoustic array for hostile fire detection and localization in an urban environment

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.

2008-04-01

The detection and localization of hostile weapons firing has been demonstrated successfully with acoustic sensor arrays on unattended ground sensors (UGS), ground-vehicles, and unmanned aerial vehicles (UAVs). Some of the more mature systems have demonstrated significant capabilities and provide direct support to ongoing counter-sniper operations. The Army Research Laboratory (ARL) is conducting research and development for a helmet-mounted system to acoustically detect and localize small arms firing, or other events such as RPG, mortars, and explosions, as well as other non-transient signatures. Since today's soldier is quickly being asked to take on more and more reconnaissance, surveillance, & target acquisition (RSTA) functions, sensor augmentation enables him to become a mobile and networked sensor node on the complex and dynamic battlefield. Having a body-worn threat detection and localization capability for events that pose an immediate danger to the soldiers around him can significantly enhance their survivability and lethality, as well as enable him to provide and use situational awareness clues on the networked battlefield. This paper addresses some of the difficulties encountered by an acoustic system in an urban environment. Complex reverberation, multipath, diffraction, and signature masking by building structures makes this a very harsh environment for robust detection and classification of shockwaves and muzzle blasts. Multifunctional acoustic detection arrays can provide persistent surveillance and enhanced situational awareness for every soldier.

Cellular telephone-based radiation sensor and wide-area detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2006-12-12

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Wi-Fi/MARG Integration for Indoor Pedestrian Localization.

PubMed

Tian, Zengshan; Jin, Yue; Zhou, Mu; Wu, Zipeng; Li, Ze

2016-12-10

With the wide deployment of Wi-Fi networks, Wi-Fi based indoor localization systems that are deployed without any special hardware have caught significant attention and have become a currently practical technology. At the same time, the Magnetic, Angular Rate, and Gravity (MARG) sensors installed in commercial mobile devices can achieve highly-accurate localization in short time. Based on this, we design a novel indoor localization system by using built-in MARG sensors and a Wi-Fi module. The innovative contributions of this paper include the enhanced Pedestrian Dead Reckoning (PDR) and Wi-Fi localization approaches, and an Extended Kalman Particle Filter (EKPF) based fusion algorithm. A new Wi-Fi/MARG indoor localization system, including an Android based mobile client, a Web page for remote control, and a location server, is developed for real-time indoor pedestrian localization. The extensive experimental results show that the proposed system is featured with better localization performance, with the average error 0.85 m, than the one achieved by using the Wi-Fi module or MARG sensors solely.

An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

NASA Astrophysics Data System (ADS)

Leon, Barbara D.; Heller, Paul R.

1987-05-01

A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system, driven by a forward chaining inference engine, makes decisions based on the global database. The global database contains current track and sensor information supplied by the simulation. At present, the rule base emphasizes the surveillance features with rules grouped into three main categories: maintenance and enhancing track on prioritized targets; filling coverage holes and countering jamming; and evaluating sensor status. The paper will describe the architecture used for the expert system and the reasons for selecting the chosen methods. The SM&C simulation produces a graphical representation of sensors and their associated tracks such that the benefits of the sensor management and control expert system are evident. Jammer locations are also part of the display. The paper will describe results from several scenarios that best illustrate the sensor management and control concepts.

A decentralized fuzzy C-means-based energy-efficient routing protocol for wireless sensor networks.

PubMed

Alia, Osama Moh'd

2014-01-01

Energy conservation in wireless sensor networks (WSNs) is a vital consideration when designing wireless networking protocols. In this paper, we propose a Decentralized Fuzzy Clustering Protocol, named DCFP, which minimizes total network energy dissipation to promote maximum network lifetime. The process of constructing the infrastructure for a given WSN is performed only once at the beginning of the protocol at a base station, which remains unchanged throughout the network's lifetime. In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. Subsequently, the protocol runs its rounds where each round is divided into a CH-Election phase and a Data Transmission phase. In the CH-Election phase, the election of new cluster heads is done locally in each cluster where a new multicriteria objective function is proposed to enhance the quality of elected cluster heads. In the Data Transmission phase, the sensing and data transmission from each sensor node to their respective cluster head is performed and cluster heads in turn aggregate and send the sensed data to the base station. Simulation results demonstrate that the proposed protocol improves network lifetime, data delivery, and energy consumption compared to other well-known energy-efficient protocols.

A Decentralized Fuzzy C-Means-Based Energy-Efficient Routing Protocol for Wireless Sensor Networks

PubMed Central

2014-01-01

Energy conservation in wireless sensor networks (WSNs) is a vital consideration when designing wireless networking protocols. In this paper, we propose a Decentralized Fuzzy Clustering Protocol, named DCFP, which minimizes total network energy dissipation to promote maximum network lifetime. The process of constructing the infrastructure for a given WSN is performed only once at the beginning of the protocol at a base station, which remains unchanged throughout the network's lifetime. In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. Subsequently, the protocol runs its rounds where each round is divided into a CH-Election phase and a Data Transmission phase. In the CH-Election phase, the election of new cluster heads is done locally in each cluster where a new multicriteria objective function is proposed to enhance the quality of elected cluster heads. In the Data Transmission phase, the sensing and data transmission from each sensor node to their respective cluster head is performed and cluster heads in turn aggregate and send the sensed data to the base station. Simulation results demonstrate that the proposed protocol improves network lifetime, data delivery, and energy consumption compared to other well-known energy-efficient protocols. PMID:25162060

Localization and Tracking of Implantable Biomedical Sensors

PubMed Central

Umay, Ilknur; Fidan, Barış; Barshan, Billur

2017-01-01

Implantable sensor systems are effective tools for biomedical diagnosis, visualization and treatment of various health conditions, attracting the interest of researchers, as well as healthcare practitioners. These systems efficiently and conveniently provide essential data of the body part being diagnosed, such as gastrointestinal (temperature, pH, pressure) parameter values, blood glucose and pressure levels and electrocardiogram data. Such data are first transmitted from the implantable sensor units to an external receiver node or network and then to a central monitoring and control (computer) unit for analysis, diagnosis and/or treatment. Implantable sensor units are typically in the form of mobile microrobotic capsules or implanted stationary (body-fixed) units. In particular, capsule-based systems have attracted significant research interest recently, with a variety of applications, including endoscopy, microsurgery, drug delivery and biopsy. In such implantable sensor systems, one of the most challenging problems is the accurate localization and tracking of the microrobotic sensor unit (e.g., robotic capsule) inside the human body. This article presents a literature review of the existing localization and tracking techniques for robotic implantable sensor systems with their merits and limitations and possible solutions of the proposed localization methods. The article also provides a brief discussion on the connection and cooperation of such techniques with wearable biomedical sensor systems. PMID:28335384

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

PubMed Central

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

PubMed

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

SoundCompass: A Distributed MEMS Microphone Array-Based Sensor for Sound Source Localization

PubMed Central

Tiete, Jelmer; Domínguez, Federico; da Silva, Bruno; Segers, Laurent; Steenhaut, Kris; Touhafi, Abdellah

2014-01-01

Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass’s hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field. PMID:24463431

Efficient detection of contagious outbreaks in massive metropolitan encounter networks

PubMed Central

Sun, Lijun; Axhausen, Kay W.; Lee, Der-Horng; Cebrian, Manuel

2014-01-01

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the “friend sensor” scheme - a simple, but universal strategy requiring only local information - and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced “global sensor sets”, obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree. PMID:24903017

Time-optimum packet scheduling for many-to-one routing in wireless sensor networks

USGS Publications Warehouse

Song, W.-Z.; Yuan, F.; LaHuser, R.

2007-01-01

This paper studies the WSN application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is time-optimum and costs max(2N(u1) - 1, N(u 0) -1) time slots, assuming each node reports one unit of data in each round. Here N(u0) is the total number of sensors, while N(u 1) denotes the number of sensors in a sink's largest branch subtree. With a few adjustments, we then show that our algorithm also achieves time-optimum scheduling in heterogeneous scenarios, where each sensor reports a heterogeneous amount of data in each round. Then we give a distributed implementation to let each node calculate its duty-cycle locally and maximize efficiency globally. In this packet scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also eliminated. Finally, simulations are conducted to evaluate network performance using the Qualnet simulator. Among other contributions, our study also identifies the maximum reporting frequency that a deployed sensor network can handle. ??2006 IEEE.

Wireless Power Transfer for Distributed Estimation in Sensor Networks

NASA Astrophysics Data System (ADS)

Mai, Vien V.; Shin, Won-Yong; Ishibashi, Koji

2017-04-01

This paper studies power allocation for distributed estimation of an unknown scalar random source in sensor networks with a multiple-antenna fusion center (FC), where wireless sensors are equipped with radio-frequency based energy harvesting technology. The sensors' observation is locally processed by using an uncoded amplify-and-forward scheme. The processed signals are then sent to the FC, and are coherently combined at the FC, at which the best linear unbiased estimator (BLUE) is adopted for reliable estimation. We aim to solve the following two power allocation problems: 1) minimizing distortion under various power constraints; and 2) minimizing total transmit power under distortion constraints, where the distortion is measured in terms of mean-squared error of the BLUE. Two iterative algorithms are developed to solve the non-convex problems, which converge at least to a local optimum. In particular, the above algorithms are designed to jointly optimize the amplification coefficients, energy beamforming, and receive filtering. For each problem, a suboptimal design, a single-antenna FC scenario, and a common harvester deployment for colocated sensors, are also studied. Using the powerful semidefinite relaxation framework, our result is shown to be valid for any number of sensors, each with different noise power, and for an arbitrarily number of antennas at the FC.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

Soil water sensing for climate change studies; Applicability of COSMOS and local sensor networks

USDA-ARS?s Scientific Manuscript database

Soil water sensors are used to characterize water content in the near-surface, the root zone and below for agricultural and ecosystem management, but only a few are capable of sensing soil volumes larger than a few hundred liters. Scientists with the USDA-ARS Conservation & Production Research Labor...

Multiple Event Localization in a Sparse Acoustic Sensor Network Using UAVs as Data Mules

DTIC Science & Technology

2012-12-01

necessarily reflect the position or the policy of the Government , and no official endorsement should be inferred. Path Acoustic Sensor Communication Footprint...a Microhard radio to forward the ToAs to the mule-UAV. Two Procerus Unicorn UAVs were used with different payloads. The imaging- UAV was equipped

Efficient DV-HOP Localization for Wireless Cyber-Physical Social Sensing System: A Correntropy-Based Neural Network Learning Scheme

PubMed Central

Xu, Yang; Luo, Xiong; Wang, Weiping; Zhao, Wenbing

2017-01-01

Integrating wireless sensor network (WSN) into the emerging computing paradigm, e.g., cyber-physical social sensing (CPSS), has witnessed a growing interest, and WSN can serve as a social network while receiving more attention from the social computing research field. Then, the localization of sensor nodes has become an essential requirement for many applications over WSN. Meanwhile, the localization information of unknown nodes has strongly affected the performance of WSN. The received signal strength indication (RSSI) as a typical range-based algorithm for positioning sensor nodes in WSN could achieve accurate location with hardware saving, but is sensitive to environmental noises. Moreover, the original distance vector hop (DV-HOP) as an important range-free localization algorithm is simple, inexpensive and not related to the environment factors, but performs poorly when lacking anchor nodes. Motivated by these, various improved DV-HOP schemes with RSSI have been introduced, and we present a new neural network (NN)-based node localization scheme, named RHOP-ELM-RCC, through the use of DV-HOP, RSSI and a regularized correntropy criterion (RCC)-based extreme learning machine (ELM) algorithm (ELM-RCC). Firstly, the proposed scheme employs both RSSI and DV-HOP to evaluate the distances between nodes to enhance the accuracy of distance estimation at a reasonable cost. Then, with the help of ELM featured with a fast learning speed with a good generalization performance and minimal human intervention, a single hidden layer feedforward network (SLFN) on the basis of ELM-RCC is used to implement the optimization task for obtaining the location of unknown nodes. Since the RSSI may be influenced by the environmental noises and may bring estimation error, the RCC instead of the mean square error (MSE) estimation, which is sensitive to noises, is exploited in ELM. Hence, it may make the estimation more robust against outliers. Additionally, the least square estimation (LSE) in ELM is replaced by the half-quadratic optimization technique. Simulation results show that our proposed scheme outperforms other traditional localization schemes. PMID:28085084

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks.

PubMed

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-03-07

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Cheng, M.; Guy, R.; Chandy, M.; Krause, A.; Bunn, J.; Olson, M.; Faulkner, M.; Liu, A.; Strand, L.

2012-12-01

We report on developments in sensor connectivity, architecture, and data fusion algorithms executed in Cloud computing systems in the Community Seismic Network (CSN), a network of low-cost sensors housed in homes and offices by volunteers in the Pasadena, CA area. The network has over 200 sensors continuously reporting anomalies in local acceleration through the Internet to a Cloud computing service (the Google App Engine) that continually fuses sensor data to rapidly detect shaking from earthquakes. The Cloud computing system consists of data centers geographically distributed across the continent and is likely to be resilient even during earthquakes and other local disasters. The region of Southern California is partitioned in a multi-grid style into sets of telescoping cells called geocells. Data streams from sensors within a geocell are fused to detect anomalous shaking across the geocell. Temporal spatial patterns across geocells are used to detect anomalies across regions. The challenge is to detect earthquakes rapidly with an extremely low false positive rate. We report on two data fusion algorithms, one that tessellates the surface so as to fuse data from a large region around Pasadena and the other, which uses a standard tessellation of equal-sized cells. Since September 2011, the network has successfully detected earthquakes of magnitude 2.5 or higher within 40 Km of Pasadena. In addition to the standard USB device, which connects to the host's computer, we have developed a stand-alone sensor that directly connects to the internet via Ethernet or wifi. This bypasses security concerns that some companies have with the USB-connected devices, and allows for 24/7 monitoring at sites that would otherwise shut down their computers after working hours. In buildings we use the sensors to model the behavior of the structures during weak events in order to understand how they will perform during strong events. Visualization models of instrumented buildings ranging between five and 22 stories tall have been constructed using Google SketchUp. Ambient vibration records are used to identify the first set of horizontal vibrational modal frequencies of the buildings. These frequencies are used to compute the response on every floor of the building, given either observed data or scenario ground motion input at the buildings' base.

An Architecture for Cooperative Localization in Underwater Acoustic Networks

DTIC Science & Technology

2015-10-24

range. (b) Independent navigation and control system onboard Iver AUVs . The cooperative localization process is highlighted in red. Figure 1: Block...Iver2 AUVs (Fig. 3) and a topside ship. While we make spe- cific notes about this three vehicle network, the architecture is vehicle independent. 3.1...Single vehicle subsystem Each vehicle executes several processes including sensor drivers, a pose estimator (Section 2), and, in the case of the AUVs

An efficient genetic algorithm for maximum coverage deployment in wireless sensor networks.

PubMed

Yoon, Yourim; Kim, Yong-Hyuk

2013-10-01

Sensor networks have a lot of applications such as battlefield surveillance, environmental monitoring, and industrial diagnostics. Coverage is one of the most important performance metrics for sensor networks since it reflects how well a sensor field is monitored. In this paper, we introduce the maximum coverage deployment problem in wireless sensor networks and analyze the properties of the problem and its solution space. Random deployment is the simplest way to deploy sensor nodes but may cause unbalanced deployment and therefore, we need a more intelligent way for sensor deployment. We found that the phenotype space of the problem is a quotient space of the genotype space in a mathematical view. Based on this property, we propose an efficient genetic algorithm using a novel normalization method. A Monte Carlo method is adopted to design an efficient evaluation function, and its computation time is decreased without loss of solution quality using a method that starts from a small number of random samples and gradually increases the number for subsequent generations. The proposed genetic algorithms could be further improved by combining with a well-designed local search. The performance of the proposed genetic algorithm is shown by a comparative experimental study. When compared with random deployment and existing methods, our genetic algorithm was not only about twice faster, but also showed significant performance improvement in quality.

Community Seismic Network

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Kohler, M. D.; Massari, A.; Heaton, T. H.; Guy, R.; Chandy, M.; Bunn, J.; Strand, L.

2014-12-01

The CSN is now in its 3rdyear of operation and has expanded to 400 stations in the Los Angeles region. The goal of the network is to produce a map of strong shaking immediately following a major earthquake as a proxy for damage and a guide for first responders. We have also instrumented a number of buildings with the goal of determining the state of health of these structures before and after they have been shaken. In one 15-story structure, our sensors distributed two per floor, and show body waves propagating in the structure after a moderate local earthquake (M4.4 in Encino, CA). Sensors in a 52-story structure, which we plan to instrument with two sensors per floor as well, show the modes of the building (see Figure) down to the fundamental mode at 5 sec due to a M5.1 earthquake in La Habra, CA. The CSN utilizes a number of technologies that will likely be important in building robust low-cost networks. These include: Distributed computing - the sensors themselves are smart-sensors that perform the basic detection and size estimation in the onboard computers and send the results immediately (without packetization latency) to the central facility. Cloud computing - the central facility is housed in the cloud, which means it is more robust than a local site, and has expandable computing resources available so that it can operate with minimal resources during quiet times but still be able to exploit an very large computing facility during an earthquake. Low-cost/low-maintenance sensors - the MEM sensors are capable of staying onscale to +/- 2g, and can measure events in the Los Angeles Basin a low as magnitude 3.

Telecommunication Platforms for Transmitting Sensor Data over Communication Networks—State of the Art and Challenges

PubMed Central

Staniec, Kamil; Habrych, Marcin

2016-01-01

The importance of constructing wide-area sensor networks for holistic environmental state evaluation has been demonstrated. A general structure of such a network has been presented with distinction of three segments: local (based on ZigBee, Ethernet and ModBus techniques), core (base on cellular technologies) and the storage/application. The implementation of these techniques requires knowledge of their technical limitations and electromagnetic compatibility issues. The former refer to ZigBee performance degradation in multi-hop transmission, whereas the latter are associated with the common electromagnetic spectrum sharing with other existing technologies or with undesired radiated emissions generated by the radio modules of the sensor network. In many cases, it is also necessary to provide a measurement station with autonomous energy source, such as solar. As stems from measurements of the energetic efficiency of these sources, one should apply them with care and perform detailed power budget since their real performance may turn out to be far from expected. This, in turn, may negatively affect—in particular—the operation of chemical sensors implemented in the network as they often require additional heating. PMID:27447633

Malfunctions in radioactivity sensors' networks

NASA Astrophysics Data System (ADS)

Khalipova, Veronika; Damart, Guillaume; Beauzamy, Bernard; Bruna, Giovanni

2018-01-01

The capacity to promptly and efficiently detect any source of contamination of the environment (a radioactive cloud) at a local and a country scale is mandatory to a safe and secure exploitation of civil nuclear energy. It must rely upon a robust network of measurement devices, to be optimized vs. several parameters, including the overall reliability, the investment, the operation and maintenance costs. We show that a network can be arranged in different ways, but many of them are inadequate. Through simulations, we test the efficiency of several configurations of sensors, in the same domain. The denser arrangement turns out to be the more efficient, but the efficiency is increased when sensors are non-uniformly distributed over the country, with accumulation at the borders. In the case of France, as radioactive threats are most likely to come from the East, the best solution is densifying the sensors close to the eastern border. Our approach differs from previous work because it is "failure oriented": we determine the laws of probability for all types of failures and deduce in this respect the best organization of the network.

The role of local interaction mechanics in fiber optic smart structures

NASA Astrophysics Data System (ADS)

Sirkis, J. S.; Dasgupta, A.

1993-04-01

The concept of using 'smart' composite materials/structures with built-in self-diagnostic capabilities for health monitoring involves embedding discrete and/or distributed sensory networks in the host composite material, along with a central and/or distributed artificial intelligence capability for signal processing, data collection, interpretation and diagnostic evaluations. This article concentrates on the sensory functions in 'smart' structure applications and concentrates in particular on optical fiber sensors. Specifically, we present an overview of recent research dealing with the basic mechanics of local interactions between the embedded optical fiber sensors and the surrounding host composite. The term 'local' is defined by length scales on the order of several optical fiber diameters. We examine some generic issues, such as the 'calibration' and 'obtrusivity' of the sensor, and the inherent damage caused by the sensor inclusions to the surrounding host and vice-versa under internal and/or external applied loads. Analytical, numerical and experimental results are presented regarding the influence of local strain concentrations caused by the sensory inclusions on sensor and host performance. The important issues examined are the local mechanistic effects of optical fiber coatings on the behavior of the sensor and the host, and mechanical survivability of optical fibers experiencing quasi-static and time-varying thermomechanical loading.

Gaussian process regression for sensor networks under localization uncertainty

USGS Publications Warehouse

Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

2013-01-01

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

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 (based on plastic optical fiber). Data transmitted directly to server where the early warning algorithms monitor the water level variations in real time. Both sensor nodes use power harvesting techniques in order to extend their battery life as much as possible. [1] Yick J.; Mukherjee, B.; Ghosal, D. Wireless sensor network survey. Comput. Netw. 2008, 52, 2292-2330. [2] Garcia, M.; Bri, D.; Boronat, F.; Lloret, J. A new neighbor selection strategy for group-based wireless sensor networks, In The Fourth International Conference on Networking and Services (ICNS 2008), Gosier, Guadalupe, March 16-21, 2008.

ADVANCED SURVEILLANCE OF ENVIROMENTAL RADIATION IN AUTOMATIC NETWORKS.

PubMed

Benito, G; Sáez, J C; Blázquez, J B; Quiñones, J

2018-06-01

The objective of this study is the verification of the operation of a radiation monitoring network conformed by several sensors. The malfunction of a surveillance network has security and economic consequences, which derive from its maintenance and could be avoided with an early detection. The proposed method is based on a kind of multivariate distance, and the verification for the methodology has been tested at CIEMAT's local radiological early warning network.

PADF electromagnetic source localization using extremum seeking control

NASA Astrophysics Data System (ADS)

Al Issa, Huthaifa A.; Ordóñez, Raúl

2014-10-01

Wireless Sensor Networks (WSNs) are a significant technology attracting considerable research interest. Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power and multi-functional sensors that are small in size and communicate over short distances. Most WSN applications require knowing or measuring locations of thousands of sensors accurately. For example, sensing data without knowing the sensor location is often meaningless. Locations of sensor nodes are fundamental to providing location stamps, locating and tracking objects, forming clusters, and facilitating routing. This research focused on the modeling and implementation of distributed, mobile radar sensor networks. In particular, we worked on the problem of Position-Adaptive Direction Finding (PADF), to determine the location of a non- collaborative transmitter, possibly hidden within a structure, by using a team of cooperative intelligent sensor networks. Position-Adaptive radar concepts have been formulated and investigated at the Air Force Research Laboratory (AFRL) within the past few years. In this paper, we present the simulation performance analysis on the application aspect. We apply Extremum Seeking Control (ESC) schemes by using the swarm seeking problem, where the goal is to design a control law for each individual sensor that can minimize the error metric by adapting the sensor positions in real-time, thereby minimizing the unknown estimation error. As a result we achieved source seeking and collision avoidance of the entire group of the sensor positions.

Determining Methane Leak Locations and Rates with a Wireless Network Composed of Low-Cost, Printed Sensors

NASA Astrophysics Data System (ADS)

Smith, C. J.; Kim, B.; Zhang, Y.; Ng, T. N.; Beck, V.; Ganguli, A.; Saha, B.; Daniel, G.; Lee, J.; Whiting, G.; Meyyappan, M.; Schwartz, D. E.

2015-12-01

We will present our progress on the development of a wireless sensor network that will determine the source and rate of detected methane leaks. The targeted leak detection threshold is 2 g/min with a rate estimation error of 20% and localization error of 1 m within an outdoor area of 100 m2. The network itself is composed of low-cost, high-performance sensor nodes based on printed nanomaterials with expected sensitivity below 1 ppmv methane. High sensitivity to methane is achieved by modifying high surface-area-to-volume-ratio single-walled carbon nanotubes (SWNTs) with materials that adsorb methane molecules. Because the modified SWNTs are not perfectly selective to methane, the sensor nodes contain arrays of variously-modified SWNTs to build diversity of response towards gases with adsorption affinity. Methane selectivity is achieved through advanced pattern-matching algorithms of the array's ensemble response. The system is low power and designed to operate for a year on a single small battery. The SWNT sensing elements consume only microwatts. The largest power consumer is the wireless communication, which provides robust, real-time measurement data. Methane leak localization and rate estimation will be performed by machine-learning algorithms built with the aid of computational fluid dynamics simulations of gas plume formation. This sensor system can be broadly applied at gas wells, distribution systems, refineries, and other downstream facilities. It also can be utilized for industrial and residential safety applications, and adapted to other gases and gas combinations.

Location verification algorithm of wearable sensors for wireless body area networks.

PubMed

Wang, Hua; Wen, Yingyou; Zhao, Dazhe

2018-01-01

Knowledge of the location of sensor devices is crucial for many medical applications of wireless body area networks, as wearable sensors are designed to monitor vital signs of a patient while the wearer still has the freedom of movement. However, clinicians or patients can misplace the wearable sensors, thereby causing a mismatch between their physical locations and their correct target positions. An error of more than a few centimeters raises the risk of mistreating patients. The present study aims to develop a scheme to calculate and detect the position of wearable sensors without beacon nodes. A new scheme was proposed to verify the location of wearable sensors mounted on the patient's body by inferring differences in atmospheric air pressure and received signal strength indication measurements from wearable sensors. Extensive two-sample t tests were performed to validate the proposed scheme. The proposed scheme could easily recognize a 30-cm horizontal body range and a 65-cm vertical body range to correctly perform sensor localization and limb identification. All experiments indicate that the scheme is suitable for identifying wearable sensor positions in an indoor environment.

Fuzzy mobile-robot positioning in intelligent spaces using wireless sensor networks.

PubMed

Herrero, David; Martínez, Humberto

2011-01-01

This work presents the development and experimental evaluation of a method based on fuzzy logic to locate mobile robots in an Intelligent Space using wireless sensor networks (WSNs). The problem consists of locating a mobile node using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. The sensor model of these measurements is very noisy and unreliable. The proposed method makes use of fuzzy logic for modeling and dealing with such uncertain information. Besides, the proposed approach is compared with a probabilistic technique showing that the fuzzy approach is able to handle highly uncertain situations that are difficult to manage by well-known localization methods.

netPICOmag: from Design to Network Implementation

NASA Astrophysics Data System (ADS)

Schofield, I.; Connors, M.; Russell, C.

2009-05-01

netPICOmag is the successful conclusion of a design effort involving networking based on Rabbit microcontrollers, PIC microcontrollers, and pulsed magnetometer sensors. GPS timing allows both timestamping of data and the precision counting of the number of pulses produced by the sensor heads in one second. Power over Ethernet, use of DHCP, and broadcast of UDP packets mean a very simple local installation, with one wire leading to a relatively small integrated sensor package which is vertically placed in the ground. Although we continue to make improvements, including through investigating new sensor types, we regard the design as mature and well tested. Here we focus on the need for yet denser magnetometer networks, technological applications which become practical using sensitive yet inexpensive magnetometers, and deployment methods for large numbers of sensors. With careful calibration, netPICOmags overlap with research grade magnetometers. Without it, they still sensitively detect magnetic variations and can be used for an education or outreach program. Due to their low cost, such an application allows many students to be directly involved in gathering data that can be very relevant to them personally when they witness auroras.

PREFACE: Sensors and their Applications XIV

NASA Astrophysics Data System (ADS)

Prosser, S. J.; Al-Shamma'a, A. I.

2007-09-01

The fourteenth conference in the Sensors and their Applications series took place at the Liverpool John Moores University in Liverpool, UK from 11-13 September 2007. The event was organised by the Instrument Science and Technology Group of the Institute of Physics. Previous conferences in this series were held in Manchester (1983 and 1993), Southampton (1985 and 1998), Cambridge (1987), Canterbury (1989), Edinburgh (1991), Dublin (1995), Glasgow (1997), Cardiff (1999), London (2001), Limerick (2003) and Chatham (2005). The event provided a forum for academic researchers and industrial engineers working in all areas of sensors, instrumentation and measurement to update themselves on the latest technical developments and applications, share knowledge and stimulate new ideas. The third decade of this conference series continues to highlight new technologies and applications as the sensor market benefits from enhanced signal processing power and wireless networking. Through presentation of oral papers, discussions at exhibited posters and informal exchanges of ideas, the conference continues to provide excellent knowledge transfer and networking opportunities. The high quality programme, headlined by notable contributions from invited speakers, included microsensors, automotive sensors, gas sensing, non-destructive inspection, food and healthcare, sensor signal processing, wireless sensing, modelling and imaging techniques. As in previous years, this conference was particularly highlighted by a large number of sensor applications papers. We take this opportunity to thank all of those who have contributed to the event. Our thanks also go to our colleagues in the Instrument Science and Technology Group for their support and encouragement, particularly in the refereeing of papers, and to the Sensors and Instrumentation Knowledge Transfer Network. Special thanks go to Claire Garland from the Conferences Department of the Institute of Physics and the local team at Liverpool John Moores University who have expertly managed the planning and organising of this Conference. We hope that these conference proceedings will provide a technical insight into the development of sensors and their applications during 2007. S J Prosser, Conference Chairman TRW Automotive A I Al-Shamma'a, Local Chairman Liverpool John Moores University

Vital signs monitoring and patient tracking over a wireless network.

PubMed

Gao, Tia; Greenspan, Dan; Welsh, Matt; Juang, Radford; Alm, Alex

2005-01-01

Patients at a disaster scene can greatly benefit from technologies that continuously monitor their vital status and track their locations until they are admitted to the hospital. We have designed and developed a real-time patient monitoring system that integrates vital signs sensors, location sensors, ad-hoc networking, electronic patient records, and web portal technology to allow remote monitoring of patient status. This system shall facilitate communication between providers at the disaster scene, medical professionals at local hospitals, and specialists available for consultation from distant facilities.

Implementation of a Localization System for Sensor Networks

DTIC Science & Technology

2006-05-18

its N-point DFT is mathematically formulated as X[k] = N−1∑ n=0 x[n] W nkN , k = 0, 1, . . . , N − 1 (7.1) W knN = e −j(2π/N)kn (7.2) There are two...distributed ad-hoc wireless sensor networks. In Int. Conf. on Acoustics, Speech , and Signal Proc. (ICASSP), pages 2037 – 2040, Salt Lake City, UT. [18] J...Stability of recursive qrd-ls algorithms using finite- precision systolic array implementation. IEEE Trans. on Acoustics, Speech , and Signal Proc., 37(5

All-Direction Random Routing for Source-Location Privacy Protecting against Parasitic Sensor Networks.

PubMed

Wang, Na; Zeng, Jiwen

2017-03-17

Wireless sensor networks are deployed to monitor the surrounding physical environments and they also act as the physical environments of parasitic sensor networks, whose purpose is analyzing the contextual privacy and obtaining valuable information from the original wireless sensor networks. Recently, contextual privacy issues associated with wireless communication in open spaces have not been thoroughly addressed and one of the most important challenges is protecting the source locations of the valuable packages. In this paper, we design an all-direction random routing algorithm (ARR) for source-location protecting against parasitic sensor networks. For each package, the routing process of ARR is divided into three stages, i.e., selecting a proper agent node, delivering the package to the agent node from the source node, and sending it to the final destination from the agent node. In ARR, the agent nodes are randomly chosen in all directions by the source nodes using only local decisions, rather than knowing the whole topology of the networks. ARR can control the distributions of the routing paths in a very flexible way and it can guarantee that the routing paths with the same source and destination are totally different from each other. Therefore, it is extremely difficult for the parasitic sensor nodes to trace the packages back to the source nodes. Simulation results illustrate that ARR perfectly confuses the parasitic nodes and obviously outperforms traditional routing-based schemes in protecting source-location privacy, with a marginal increase in the communication overhead and energy consumption. In addition, ARR also requires much less energy than the cloud-based source-location privacy protection schemes.

Distributed cluster management techniques for unattended ground sensor networks

NASA Astrophysics Data System (ADS)

Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

2005-05-01

Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also simplify multi-target tracking within the cluster.

Sensor networks for optimal target localization with bearings-only measurements in constrained three-dimensional scenarios.

PubMed

Moreno-Salinas, David; Pascoal, Antonio; Aranda, Joaquin

2013-08-12

In this paper, we address the problem of determining the optimal geometric configuration of an acoustic sensor network that will maximize the angle-related information available for underwater target positioning. In the set-up adopted, a set of autonomous vehicles carries a network of acoustic units that measure the elevation and azimuth angles between a target and each of the receivers on board the vehicles. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using tools from estimation theory, the problem is converted into that of minimizing, by proper choice of the sensor positions, the trace of the inverse of the Fisher Information Matrix (also called the Cramer-Rao Bound matrix) to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration of the sensors depends explicitly on the intensity of the measurement noise, the constraints imposed on the sensor configuration, the target depth and the probabilistic distribution that defines the prior uncertainty in the target position. Simulation examples illustrate the key results derived.

Connecting the snowpack to the internet of things: an IPv6 architecture for providing real-time measurements of hydrologic systems

NASA Astrophysics Data System (ADS)

Kerkez, B.; Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.

2012-12-01

We describe our improved, robust, and scalable architecture by which to rapidly instrument large-scale watersheds, while providing the resulting data in real-time. Our system consists of more than twenty wireless sensor networks and thousands of sensors, which will be deployed in the American River basin (5000 sq. km) of California. The core component of our system is known as a mote, a tiny, ultra-low-power, embedded wireless computer that can be used for any number of sensing applications. Our new generation of motes is equipped with IPv6 functionality, effectively giving each sensor in the field its own unique IP address, thus permitting users to remotely interact with the devices without going through intermediary services. Thirty to fifty motes will be deployed across 1-2 square kilometer regions to form a mesh-based wireless sensor network. Redundancy of local wireless links will ensure that data will always be able to traverse the network, even if hash wintertime conditions adversely affect some network nodes. These networks will be used to develop spatial estimates of a number of hydrologic parameters, focusing especially on snowpack. Each wireless sensor network has one main network controller, which is responsible with interacting with an embedded Linux computer to relay information across higher-powered, long-range wireless links (cell modems, satellite, WiFi) to neighboring networks and remote, offsite servers. The network manager is also responsible for providing an Internet connection to each mote. Data collected by the sensors can either be read directly by remote hosts, or stored on centralized servers for future access. With 20 such networks deployed in the American River, our system will comprise an unprecedented cyber-physical architecture for measuring hydrologic parameters in large-scale basins. The spatiotemporal density and real-time nature of the data is also expected to significantly improve operational hydrology and water resource management in the basin.

Optimal Quantization Scheme for Data-Efficient Target Tracking via UWSNs Using Quantized Measurements.

PubMed

Zhang, Senlin; Chen, Huayan; Liu, Meiqin; Zhang, Qunfei

2017-11-07

Target tracking is one of the broad applications of underwater wireless sensor networks (UWSNs). However, as a result of the temporal and spatial variability of acoustic channels, underwater acoustic communications suffer from an extremely limited bandwidth. In order to reduce network congestion, it is important to shorten the length of the data transmitted from local sensors to the fusion center by quantization. Although quantization can reduce bandwidth cost, it also brings about bad tracking performance as a result of information loss after quantization. To solve this problem, this paper proposes an optimal quantization-based target tracking scheme. It improves the tracking performance of low-bit quantized measurements by minimizing the additional covariance caused by quantization. The simulation demonstrates that our scheme performs much better than the conventional uniform quantization-based target tracking scheme and the increment of the data length affects our scheme only a little. Its tracking performance improves by only 4.4% from 2- to 3-bit, which means our scheme weakly depends on the number of data bits. Moreover, our scheme also weakly depends on the number of participate sensors, and it can work well in sparse sensor networks. In a 6 × 6 × 6 sensor network, compared with 4 × 4 × 4 sensor networks, the number of participant sensors increases by 334.92%, while the tracking accuracy using 1-bit quantized measurements improves by only 50.77%. Overall, our optimal quantization-based target tracking scheme can achieve the pursuit of data-efficiency, which fits the requirements of low-bandwidth UWSNs.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks

PubMed Central

Zhang, Guomei; Sun, Hao

2016-01-01

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor’s reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured. PMID:27999282

Enhancing source location protection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Chen, Juan; Lin, Zhengkui; Wu, Di; Wang, Bailing

2015-12-01

Wireless sensor networks are widely deployed in the internet of things to monitor valuable objects. Once the object is monitored, the sensor nearest to the object which is known as the source informs the base station about the object's information periodically. It is obvious that attackers can capture the object successfully by localizing the source. Thus, many protocols have been proposed to secure the source location. However, in this paper, we examine that typical source location protection protocols generate not only near but also highly localized phantom locations. As a result, attackers can trace the source easily from these phantom locations. To address these limitations, we propose a protocol to enhance the source location protection (SLE). With phantom locations far away from the source and widely distributed, SLE improves source location anonymity significantly. Theory analysis and simulation results show that our SLE provides strong source location privacy preservation and the average safety period increases by nearly one order of magnitude compared with existing work with low communication cost.

Wi-Fi/MARG Integration for Indoor Pedestrian Localization

PubMed Central

Tian, Zengshan; Jin, Yue; Zhou, Mu; Wu, Zipeng; Li, Ze

2016-01-01

With the wide deployment of Wi-Fi networks, Wi-Fi based indoor localization systems that are deployed without any special hardware have caught significant attention and have become a currently practical technology. At the same time, the Magnetic, Angular Rate, and Gravity (MARG) sensors installed in commercial mobile devices can achieve highly-accurate localization in short time. Based on this, we design a novel indoor localization system by using built-in MARG sensors and a Wi-Fi module. The innovative contributions of this paper include the enhanced Pedestrian Dead Reckoning (PDR) and Wi-Fi localization approaches, and an Extended Kalman Particle Filter (EKPF) based fusion algorithm. A new Wi-Fi/MARG indoor localization system, including an Android based mobile client, a Web page for remote control, and a location server, is developed for real-time indoor pedestrian localization. The extensive experimental results show that the proposed system is featured with better localization performance, with the average error 0.85 m, than the one achieved by using the Wi-Fi module or MARG sensors solely. PMID:27973412

ARO PECASE: Information Assurance for Energy-Constrained Wireless Sensor Networks

DTIC Science & Technology

2011-12-21

Distribution, 18th Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), September 2007. 2. 2010 IEEE...received the following awards: Student Best Paper Award at the IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC...Localization in Wireless Ad Hoc Networks – Many current and future appli- cations of mobile ad hoc networks, including disaster response and event

Analyses of integrated aircraft cabin contaminant monitoring network based on Kalman consensus filter.

PubMed

Wang, Rui; Li, Yanxiao; Sun, Hui; Chen, Zengqiang

2017-11-01

The modern civil aircrafts use air ventilation pressurized cabins subject to the limited space. In order to monitor multiple contaminants and overcome the hypersensitivity of the single sensor, the paper constructs an output correction integrated sensor configuration using sensors with different measurement theories after comparing to other two different configurations. This proposed configuration works as a node in the contaminant distributed wireless sensor monitoring network. The corresponding measurement error models of integrated sensors are also proposed by using the Kalman consensus filter to estimate states and conduct data fusion in order to regulate the single sensor measurement results. The paper develops the sufficient proof of the Kalman consensus filter stability when considering the system and the observation noises and compares the mean estimation and the mean consensus errors between Kalman consensus filter and local Kalman filter. The numerical example analyses show the effectiveness of the algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Fortified Anonymous Communication Protocol for Location Privacy in WSN: A Modular Approach

PubMed Central

Abuzneid, Abdel-Shakour; Sobh, Tarek; Faezipour, Miad; Mahmood, Ausif; James, John

2015-01-01

Wireless sensor network (WSN) consists of many hosts called sensors. These sensors can sense a phenomenon (motion, temperature, humidity, average, max, min, etc.) and represent what they sense in a form of data. There are many applications for WSNs including object tracking and monitoring where in most of the cases these objects need protection. In these applications, data privacy itself might not be as important as the privacy of source location. In addition to the source location privacy, sink location privacy should also be provided. Providing an efficient end-to-end privacy solution would be a challenging task to achieve due to the open nature of the WSN. The key schemes needed for end-to-end location privacy are anonymity, observability, capture likelihood, and safety period. We extend this work to allow for countermeasures against multi-local and global adversaries. We present a network model protected against a sophisticated threat model: passive /active and local/multi-local/global attacks. This work provides a solution for end-to-end anonymity and location privacy as well. We will introduce a framework called fortified anonymous communication (FAC) protocol for WSN. PMID:25763649

Distributed policy based access to networked heterogeneous ISR data sources

NASA Astrophysics Data System (ADS)

Bent, G.; Vyvyan, D.; Wood, David; Zerfos, Petros; Calo, Seraphin

2010-04-01

Within a coalition environment, ad hoc Communities of Interest (CoI's) come together, perhaps for only a short time, with different sensors, sensor platforms, data fusion elements, and networks to conduct a task (or set of tasks) with different coalition members taking different roles. In such a coalition, each organization will have its own inherent restrictions on how it will interact with the others. These are usually stated as a set of policies, including security and privacy policies. The capability that we want to enable for a coalition operation is to provide access to information from any coalition partner in conformance with the policies of all. One of the challenges in supporting such ad-hoc coalition operations is that of providing efficient access to distributed sources of data, where the applications requiring the data do not have knowledge of the location of the data within the network. To address this challenge the International Technology Alliance (ITA) program has been developing the concept of a Dynamic Distributed Federated Database (DDFD), also know as a Gaian Database. This type of database provides a means for accessing data across a network of distributed heterogeneous data sources where access to the information is controlled by a mixture of local and global policies. We describe how a network of disparate ISR elements can be expressed as a DDFD and how this approach enables sensor and other information sources to be discovered autonomously or semi-autonomously and/or combined, fused formally defined local and global policies.

Technical report: The design and evaluation of a basin-scale wireless sensor network for mountain hydrology

NASA Astrophysics Data System (ADS)

Zhang, Ziran; Glaser, Steven D.; Bales, Roger C.; Conklin, Martha; Rice, Robert; Marks, Danny G.

2017-05-01

A network of sensors for spatially representative water-balance measurements was developed and deployed across the 2000 km2 snow-dominated portion of the upper American River basin, primarily to measure changes in snowpack and soil-water storage, air temperature, and humidity. This wireless sensor network (WSN) consists of 14 sensor clusters, each with 10 measurement nodes that were strategically placed within a 1 km2 area, across different elevations, aspects, slopes, and canopy covers. Compared to existing operational sensor installations, the WSN reduces hydrologic uncertainty in at least three ways. First, redundant measurements improved estimation of lapse rates for air and dew-point temperature. Second, distributed measurements captured local variability and constrained uncertainty in air and dew-point temperature, snow accumulation, and derived hydrologic attributes important for modeling and prediction. Third, the distributed relative-humidity measurements offer a unique capability to monitor upper-basin patterns in dew-point temperature and characterize elevation gradient of water vapor-pressure deficit across steep, variable topography. Network statistics during the first year of operation demonstrated that the WSN was robust for cold, wet, and windy conditions in the basin. The electronic technology used in the WSN-reduced adverse effects, such as high current consumption, multipath signal fading, and clock drift, seen in previous remote WSNs.

Percutaneous window chamber method for chronic intravital microscopy of sensor-tissue interactions.

PubMed

Koschwanez, Heidi E; Klitzman, Bruce; Reichert, W Monty

2008-11-01

A dorsal, two-sided skin-fold window chamber model was employed previously by Gough in glucose sensor research to characterize poorly understood physiological factors affecting sensor performance. We have extended this work by developing a percutaneous one-sided window chamber model for the rodent dorsum that offers both a larger subcutaneous area and a less restrictive tissue space than previous animal models. A surgical procedure for implanting a sensor into the subcutis beneath an acrylic window (15 mm diameter) is presented. Methods to quantify changes in the microvascular network and red blood cell perfusion around the sensors using noninvasive intravital microscopy and laser Doppler flowmetry are described. The feasibility of combining interstitial glucose monitoring from an implanted sensor with intravital fluorescence microscopy was explored using a bolus injection of fluorescein and dextrose to observe real-time mass transport of a small molecule at the sensor-tissue interface. The percutaneous window chamber provides an excellent model for assessing the influence of different sensor modifications, such as surface morphologies, on neovascularization using real-time monitoring of the microvascular network and tissue perfusion. However, the tissue response to an implanted sensor was variable, and some sensors migrated entirely out of the field of view and could not be observed adequately. A percutaneous optical window provides direct, real-time images of the development and dynamics of microvascular networks, microvessel patency, and fibrotic encapsulation at the tissue-sensor interface. Additionally, observing microvessels following combined bolus injections of a fluorescent dye and glucose in the local sensor environment demonstrated a valuable technique to visualize mass transport at the sensor surface.

Bridge damage detection using spatiotemporal patterns extracted from dense sensor network

NASA Astrophysics Data System (ADS)

Liu, Chao; Gong, Yongqiang; Laflamme, Simon; Phares, Brent; Sarkar, Soumik

2017-01-01

The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. With the advent of ubiquitous sensing and communication capabilities, scalable data-driven approaches is of great interest, as it can utilize large volume of streaming data without requiring detailed physical models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is proposed to explore spatiotemporal behaviors in a bridge network. Data from strain gauges installed on two bridges are generated using finite element simulation for three types of sensor networks from a density perspective (dense, nominal, sparse). Causal relationships among spatially distributed strain data streams are extracted and analyzed for vehicle identification and detection, and for localization of structural degradation in bridges. Multiple case studies show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, (iii) detecting and localizing damage via comparison of bridge responses to similar vehicle loads, and (iv) implementing real-time health monitoring and decision making work flow for bridge networks. Also, the results demonstrate increased sensitivity in detecting damages and higher reliability in quantifying the damage level with increase in sensor network density.

A Distributed Data Acquisition System for the Sensor Network of the TAWARA_RTM Project

NASA Astrophysics Data System (ADS)

Fontana, Cristiano Lino; Donati, Massimiliano; Cester, Davide; Fanucci, Luca; Iovene, Alessandro; Swiderski, Lukasz; Moretto, Sandra; Moszynski, Marek; Olejnik, Anna; Ruiu, Alessio; Stevanato, Luca; Batsch, Tadeusz; Tintori, Carlo; Lunardon, Marcello

This paper describes a distributed Data Acquisition System (DAQ) developed for the TAWARA_RTM project (TAp WAter RAdioactivity Real Time Monitor). The aim is detecting the presence of radioactive contaminants in drinking water; in order to prevent deliberate or accidental threats. Employing a set of detectors, it is possible to detect alpha, beta and gamma radiations, from emitters dissolved in water. The Sensor Network (SN) consists of several heterogeneous nodes controlled by a centralized server. The SN cyber-security is guaranteed in order to protect it from external intrusions and malicious acts. The nodes were installed in different locations, along the water treatment processes, in the waterworks plant supplying the aqueduct of Warsaw, Poland. Embedded computers control the simpler nodes, and are directly connected to the SN. Local-PCs (LPCs) control the more complex nodes that consist signal digitizers acquiring data from several detectors. The DAQ in the LPC is split in several processes communicating with sockets in a local sub-network. Each process is dedicated to a very simple task (e.g. data acquisition, data analysis, hydraulics management) in order to have a flexible and fault-tolerant system. The main SN and the local DAQ networks are separated by data routers to ensure the cyber-security.

MB-OFDM-UWB Based Wireless Multimedia Sensor Networks for Underground Coalmine: A Survey.

PubMed

Han, Ruisong; Yang, Wei; You, Kaiming

2016-12-16

Safety production of coalmines is a task of top priority which plays an important role in guaranteeing, supporting and promoting the continuous development of the coal industry. Since traditional wireless sensor networks (WSNs) cannot fully meet the requirements of comprehensive environment monitoring of underground coalmines, wireless multimedia sensor networks (WMSNs), enabling the retrieval of multimedia information, are introduced to realize fine-grained and precise environment surveillance. In this paper, a framework for designing underground coalmine WMSNs based on Multi-Band Orthogonal Frequency-Division Multiplexing Ultra-wide Band (MB-OFDM-UWB) is presented. The selection of MB-OFDM-UWB wireless transmission solution is based on the characteristics of underground coalmines. Network structure and design challenges are analyzed first, which is the foundation for further discussion. Then, key supporting technologies and open research areas in different layers are surveyed, and we provide a detailed literature review of the state of the art strategies, algorithms and general solutions in these issues. Finally, other research issues like localization, information processing, and network management are discussed.

MB-OFDM-UWB Based Wireless Multimedia Sensor Networks for Underground Coalmine: A Survey

PubMed Central

Han, Ruisong; Yang, Wei; You, Kaiming

2016-01-01

Safety production of coalmines is a task of top priority which plays an important role in guaranteeing, supporting and promoting the continuous development of the coal industry. Since traditional wireless sensor networks (WSNs) cannot fully meet the requirements of comprehensive environment monitoring of underground coalmines, wireless multimedia sensor networks (WMSNs), enabling the retrieval of multimedia information, are introduced to realize fine-grained and precise environment surveillance. In this paper, a framework for designing underground coalmine WMSNs based on Multi-Band Orthogonal Frequency-Division Multiplexing Ultra-wide Band (MB-OFDM-UWB) is presented. The selection of MB-OFDM-UWB wireless transmission solution is based on the characteristics of underground coalmines. Network structure and design challenges are analyzed first, which is the foundation for further discussion. Then, key supporting technologies and open research areas in different layers are surveyed, and we provide a detailed literature review of the state of the art strategies, algorithms and general solutions in these issues. Finally, other research issues like localization, information processing, and network management are discussed. PMID:27999258

SoilNet - A Zigbee based soil moisture sensor network

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

2007-12-01

Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25 end devices each consisting of 6 vertically arranged soil moisture sensors. The next step will be the instrumentation of two small catchments (~30 ha) with a 30 m spacing of the end devices. juelich.de/icg/icg-4/index.php?index=739

A Novel Topology Control Approach to Maintain the Node Degree in Dynamic Wireless Sensor Networks

PubMed Central

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-01-01

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power. PMID:24608008

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

PubMed Central

González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

2017-01-01

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage. PMID:28075364

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks.

PubMed

González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

2017-01-09

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

Automatic optimisation of gamma dose rate sensor networks: The DETECT Optimisation Tool

NASA Astrophysics Data System (ADS)

Helle, K. B.; Müller, T. O.; Astrup, P.; Dyve, J. E.

2014-05-01

Fast delivery of comprehensive information on the radiological situation is essential for decision-making in nuclear emergencies. Most national radiological agencies in Europe employ gamma dose rate sensor networks to monitor radioactive pollution of the atmosphere. Sensor locations were often chosen using regular grids or according to administrative constraints. Nowadays, however, the choice can be based on more realistic risk assessment, as it is possible to simulate potential radioactive plumes. To support sensor planning, we developed the DETECT Optimisation Tool (DOT) within the scope of the EU FP 7 project DETECT. It evaluates the gamma dose rates that a proposed set of sensors might measure in an emergency and uses this information to optimise the sensor locations. The gamma dose rates are taken from a comprehensive library of simulations of atmospheric radioactive plumes from 64 source locations. These simulations cover the whole European Union, so the DOT allows evaluation and optimisation of sensor networks for all EU countries, as well as evaluation of fencing sensors around possible sources. Users can choose from seven cost functions to evaluate the capability of a given monitoring network for early detection of radioactive plumes or for the creation of dose maps. The DOT is implemented as a stand-alone easy-to-use JAVA-based application with a graphical user interface and an R backend. Users can run evaluations and optimisations, and display, store and download the results. The DOT runs on a server and can be accessed via common web browsers; it can also be installed locally.

Physical limits to biomechanical sensing in disordered fibre networks

NASA Astrophysics Data System (ADS)

Beroz, Farzan; Jawerth, Louise M.; Münster, Stefan; Weitz, David A.; Broedersz, Chase P.; Wingreen, Ned S.

2017-07-01

Cells actively probe and respond to the stiffness of their surroundings. Since mechanosensory cells in connective tissue are surrounded by a disordered network of biopolymers, their in vivo mechanical environment can be extremely heterogeneous. Here we investigate how this heterogeneity impacts mechanosensing by modelling the cell as an idealized local stiffness sensor inside a disordered fibre network. For all types of networks we study, including experimentally-imaged collagen and fibrin architectures, we find that measurements applied at different points yield a strikingly broad range of local stiffnesses, spanning roughly two decades. We verify via simulations and scaling arguments that this broad range of local stiffnesses is a generic property of disordered fibre networks. Finally, we show that to obtain optimal, reliable estimates of global tissue stiffness, a cell must adjust its size, shape, and position to integrate multiple stiffness measurements over extended regions of space.

Characterizing the correlations between local phase fractions of gas-liquid two-phase flow with wire-mesh sensor.

PubMed

Tan, C; Liu, W L; Dong, F

2016-06-28

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas-liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas-liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

Characterizing the correlations between local phase fractions of gas–liquid two-phase flow with wire-mesh sensor

PubMed Central

Liu, W. L.; Dong, F.

2016-01-01

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas–liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas–liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue ‘Supersensing through industrial process tomography’. PMID:27185959

Energy Options for Wireless Sensor Nodes.

PubMed

Knight, Chris; Davidson, Joshua; Behrens, Sam

2008-12-08

Reduction in size and power consumption of consumer electronics has opened up many opportunities for low power wireless sensor networks. One of the major challenges is in supporting battery operated devices as the number of nodes in a network grows. The two main alternatives are to utilize higher energy density sources of stored energy, or to generate power at the node from local forms of energy. This paper reviews the state-of-the art technology in the field of both energy storage and energy harvesting for sensor nodes. The options discussed for energy storage include batteries, capacitors, fuel cells, heat engines and betavoltaic systems. The field of energy harvesting is discussed with reference to photovoltaics, temperature gradients, fluid flow, pressure variations and vibration harvesting.

Energy Options for Wireless Sensor Nodes

PubMed Central

Knight, Chris; Davidson, Joshua; Behrens, Sam

2008-01-01

Reduction in size and power consumption of consumer electronics has opened up many opportunities for low power wireless sensor networks. One of the major challenges is in supporting battery operated devices as the number of nodes in a network grows. The two main alternatives are to utilize higher energy density sources of stored energy, or to generate power at the node from local forms of energy. This paper reviews the state-of-the art technology in the field of both energy storage and energy harvesting for sensor nodes. The options discussed for energy storage include batteries, capacitors, fuel cells, heat engines and betavoltaic systems. The field of energy harvesting is discussed with reference to photovoltaics, temperature gradients, fluid flow, pressure variations and vibration harvesting. PMID:27873975

Wireless vibration monitoring for damage detection of highway bridges

NASA Astrophysics Data System (ADS)

Whelan, Matthew J.; Gangone, Michael V.; Janoyan, Kerop D.; Jha, Ratneshwar

2008-03-01

The development of low-cost wireless sensor networks has resulted in resurgence in the development of ambient vibration monitoring methods to assess the in-service condition of highway bridges. However, a reliable approach towards assessing the health of an in-service bridge and identifying and localizing damage without a priori knowledge of the vibration response history has yet to be formulated. A two-part study is in progress to evaluate and develop existing and proposed damage detection schemes. The first phase utilizes a laboratory bridge model to investigate the vibration response characteristics induced through introduction of changes to structural members, connections, and support conditions. A second phase of the study will validate the damage detection methods developed from the laboratory testing with progressive damage testing of an in-service highway bridge scheduled for replacement. The laboratory bridge features a four meter span, one meter wide, steel frame with a steel and cement board deck composed of sheet layers to regulate mass loading and simulate deck wear. Bolted connections and elastomeric bearings provide a means for prescribing variable local stiffness and damping effects to the laboratory model. A wireless sensor network consisting of fifty-six accelerometers accommodated by twenty-eight local nodes facilitates simultaneous, real-time and high-rate acquisition of the vibrations throughout the bridge structure. Measurement redundancy is provided by an array of wired linear displacement sensors as well as a scanning laser vibrometer. This paper presents the laboratory model and damage scenarios, a brief description of the developed wireless sensor network platform, an overview of available test and measurement instrumentation within the laboratory, and baseline measurements of dynamic response of the laboratory bridge model.

All-Direction Random Routing for Source-Location Privacy Protecting against Parasitic Sensor Networks

PubMed Central

Wang, Na; Zeng, Jiwen

2017-01-01

Wireless sensor networks are deployed to monitor the surrounding physical environments and they also act as the physical environments of parasitic sensor networks, whose purpose is analyzing the contextual privacy and obtaining valuable information from the original wireless sensor networks. Recently, contextual privacy issues associated with wireless communication in open spaces have not been thoroughly addressed and one of the most important challenges is protecting the source locations of the valuable packages. In this paper, we design an all-direction random routing algorithm (ARR) for source-location protecting against parasitic sensor networks. For each package, the routing process of ARR is divided into three stages, i.e., selecting a proper agent node, delivering the package to the agent node from the source node, and sending it to the final destination from the agent node. In ARR, the agent nodes are randomly chosen in all directions by the source nodes using only local decisions, rather than knowing the whole topology of the networks. ARR can control the distributions of the routing paths in a very flexible way and it can guarantee that the routing paths with the same source and destination are totally different from each other. Therefore, it is extremely difficult for the parasitic sensor nodes to trace the packages back to the source nodes. Simulation results illustrate that ARR perfectly confuses the parasitic nodes and obviously outperforms traditional routing-based schemes in protecting source-location privacy, with a marginal increase in the communication overhead and energy consumption. In addition, ARR also requires much less energy than the cloud-based source-location privacy protection schemes. PMID:28304367

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Far-field DOA estimation and source localization for different scenarios in a distributed sensor network

NASA Astrophysics Data System (ADS)

Asgari, Shadnaz

Recent developments in the integrated circuits and wireless communications not only open up many possibilities but also introduce challenging issues for the collaborative processing of signals for source localization and beamforming in an energy-constrained distributed sensor network. In signal processing, various sensor array processing algorithms and concepts have been adopted, but must be further tailored to match the communication and computational constraints. Sometimes the constraints are such that none of the existing algorithms would be an efficient option for the defined problem and as the result; the necessity of developing a new algorithm becomes undeniable. In this dissertation, we present the theoretical and the practical issues of Direction-Of-Arrival (DOA) estimation and source localization using the Approximate-Maximum-Likelihood (AML) algorithm for different scenarios. We first investigate a robust algorithm design for coherent source DOA estimation in a limited reverberant environment. Then, we provide a least-square (LS) solution for source localization based on our newly proposed virtual array model. In another scenario, we consider the determination of the location of a disturbance source which emits both wideband acoustic and seismic signals. We devise an enhanced AML algorithm to process the data collected at the acoustic sensors. For processing the seismic signals, two distinct algorithms are investigated to determine the DOAs. Then, we consider a basic algorithm for fusion of the results yielded by the acoustic and seismic arrays. We also investigate the theoretical and practical issues of DOA estimation in a three-dimensional (3D) scenario. We show that the performance of the proposed 3D AML algorithm converges to the Cramer-Rao Bound. We use the concept of an isotropic array to reduce the complexity of the proposed algorithm by advocating a decoupled 3D version. We also explore a modified version of the decoupled 3D AML algorithm which can be used for DOA estimation with non-isotropic arrays. In this dissertation, for each scenario, efficient numerical implementations of the corresponding AML algorithm are derived and applied into a real-time sensor network testbed. Extensive simulations as well as experimental results are presented to verify the effectiveness of the proposed algorithms.

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

NASA Astrophysics Data System (ADS)

Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

2011-06-01

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

Spatial sparsity based indoor localization in wireless sensor network for assistive healthcare.

PubMed

Pourhomayoun, Mohammad; Jin, Zhanpeng; Fowler, Mark

2012-01-01

Indoor localization is one of the key topics in the area of wireless networks with increasing applications in assistive healthcare, where tracking the position and actions of the patient or elderly are required for medical observation or accident prevention. Most of the common indoor localization methods are based on estimating one or more location-dependent signal parameters like TOA, AOA or RSS. However, some difficulties and challenges caused by the complex scenarios within a closed space significantly limit the applicability of those existing approaches in an indoor assistive environment, such as the well-known multipath effect. In this paper, we develop a new one-stage localization method based on spatial sparsity of the x-y plane. In this method, we directly estimate the location of the emitter without going through the intermediate stage of TOA or signal strength estimation. We evaluate the performance of the proposed method using Monte Carlo simulation. The results show that the proposed method is (i) very accurate even with a small number of sensors and (ii) very effective in addressing the multi-path issues.

Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

2015-01-01

Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

On Designing Thermal-Aware Localized QoS Routing Protocol for in-vivo Sensor Nodes in Wireless Body Area Networks.

PubMed

Monowar, Muhammad Mostafa; Bajaber, Fuad

2015-06-15

In this paper, we address the thermal rise and Quality-of-Service (QoS) provisioning issue for an intra-body Wireless Body Area Network (WBAN) having in-vivo sensor nodes. We propose a thermal-aware QoS routing protocol, called TLQoS, that facilitates the system in achieving desired QoS in terms of delay and reliability for diverse traffic types, as well as avoids the formation of highly heated nodes known as hotspot(s), and keeps the temperature rise along the network to an acceptable level. TLQoS exploits modular architecture wherein different modules perform integrated operations in providing multiple QoS service with lower temperature rise. To address the challenges of highly dynamic wireless environment inside the human body. TLQoS implements potential-based localized routing that requires only local neighborhood information. TLQoS avoids routing loop formation as well as reduces the number of hop traversal exploiting hybrid potential, and tuning a configurable parameter. We perform extensive simulations of TLQoS, and the results show that TLQoS has significant performance improvements over state-of-the-art approaches.

On Designing Thermal-Aware Localized QoS Routing Protocol for in-vivo Sensor Nodes in Wireless Body Area Networks

PubMed Central

Monowar, Muhammad Mostafa; Bajaber, Fuad

2015-01-01

In this paper, we address the thermal rise and Quality-of-Service (QoS) provisioning issue for an intra-body Wireless Body Area Network (WBAN) having in-vivo sensor nodes. We propose a thermal-aware QoS routing protocol, called TLQoS, that facilitates the system in achieving desired QoS in terms of delay and reliability for diverse traffic types, as well as avoids the formation of highly heated nodes known as hotspot(s), and keeps the temperature rise along the network to an acceptable level. TLQoS exploits modular architecture wherein different modules perform integrated operations in providing multiple QoS service with lower temperature rise. To address the challenges of highly dynamic wireless environment inside the human body. TLQoS implements potential-based localized routing that requires only local neighborhood information. TLQoS avoids routing loop formation as well as reduces the number of hop traversal exploiting hybrid potential, and tuning a configurable parameter. We perform extensive simulations of TLQoS, and the results show that TLQoS has significant performance improvements over state-of-the-art approaches. PMID:26083228

Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks

PubMed Central

Richter, Philipp; Toledano-Ayala, Manuel

2015-01-01

Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate. PMID:26370996

Lightweight filter architecture for energy efficient mobile vehicle localization based on a distributed acoustic sensor network.

PubMed

Kim, Keonwook

2013-08-23

The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably.

Efficient spatial privacy preserving scheme for sensor network

NASA Astrophysics Data System (ADS)

Debnath, Ashmita; Singaravelu, Pradheepkumar; Verma, Shekhar

2013-03-01

The privacy of sensitive events observed by a wireless sensor networks (WSN) needs to be protected. Adversaries with the knowledge of sensor deployment and network protocols can infer the location of a sensed event by monitoring the communication from the sensors even when the messages are encrypted. Encryption provides confidentiality; however, the context of the event can used to breach the privacy of sensed objects. An adversary can track the trajectory of a moving object or determine the location of the occurrence of a critical event to breach its privacy. In this paper, we propose ring signature to obfuscate the spatial information. Firstly, the extended region of location of an event of interest as estimated from a sensor communication is presented. Then, the increase in this region of spatial uncertainty due to the effect of ring signature is determined. We observe that ring signature can effectively enhance the region of location uncertainty of a sensed event. As the event of interest can be situated anywhere in the enhanced region of uncertainty, its privacy against local or global adversary is ensured. Both analytical and simulation results show that induced delay and throughput are insignificant with negligible impact on the performance of a WSN.

An improved genetic algorithm for increasing the addressing accuracy of encoding fiber Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Liu, Huanlin; Wang, Chujun; Chen, Yong

2018-01-01

Large-capacity encoding fiber Bragg grating (FBG) sensor network is widely used in modern long-term health monitoring system. Encoding FBG sensors have greatly improved the capacity of distributed FBG sensor network. However, the error of addressing increases correspondingly with the enlarging of capacity. To address the issue, an improved algorithm called genetic tracking algorithm (GTA) is proposed in the paper. In the GTA, for improving the success rate of matching and reducing the large number of redundant matching operations generated by sequential matching, the individuals are designed based on the feasible matching. Then, two kinds of self-crossover ways and a dynamic variation during mutation process are designed to increase the diversity of individuals and to avoid falling into local optimum. Meanwhile, an assistant decision is proposed to handle the issue that the GTA cannot solve when the variation of sensor information is highly overlapped. The simulation results indicate that the proposed GTA has higher accuracy compared with the traditional tracking algorithm and the enhanced tracking algorithm. In order to address the problems of spectrum fragmentation and low sharing degree of spectrum resources in survivable.

A Mobile Sensor Network to Map CO2 in Urban Environments

NASA Astrophysics Data System (ADS)

Lee, J.; Christen, A.; Nesic, Z.; Ketler, R.

2014-12-01

Globally, an estimated 80% of all fuel-based CO2 emissions into the atmosphere are attributable to cities, but there is still a lack of tools to map, visualize and monitor emissions to the scales at which emissions reduction strategies can be implemented - the local and urban scale. Mobile CO2 sensors, such as those attached to taxis and other existing mobile platforms, may be a promising way to observe and map CO2 mixing ratios across heterogenous urban environments with a limited number of sensors. Emerging modular open source technologies, and inexpensive compact sensor components not only enable rapid prototyping and replication, but also are allowing for the miniaturization and mobilization of traditionally fixed sensor networks. We aim to optimize the methods and technologies for monitoring CO2 in cities using a network of CO2 sensors deployable on vehicles and bikes. Our sensor technology is contained in a compact weather-proof case (35.8cm x 27.8cm x 11.8cm), powered independently by battery or by car, and includes the Li-Cor Li-820 infrared gas analyzer (Licor Inc, lincoln, NB, USA), Arduino Mega microcontroller (Arduino CC, Italy) and Adafruit GPS (Adafruit Technologies, NY, USA), and digital air temperature thermometer which measure CO2 mixing ratios (ppm), geolocation and speed, pressure and temperature, respectively at 1-second intervals. With the deployment of our sensor technology, we will determine if such a semi-autonomous mobile approach to monitoring CO2 in cities can determine excess urban CO2 mixing ratios (i.e. the 'urban CO2 dome') when compared to values measured at a fixed, remote background site. We present results from a pilot study in Vancouver, BC, where the a network of our new sensors was deployed both in fixed network and in a mobile campaign and examine the spatial biases of the two methods.

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

PubMed

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.

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

PubMed Central

Feng, Zuren; Ren, Zhigang

2018-01-01

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. PMID:29401649

Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks

PubMed Central

Liu, Zhihua; Gao, Han; Wang, Wuling; Chang, Shuai; Chen, Jiaxing

2015-01-01

Accurate localization of mobile nodes has been an important and fundamental problem in underwater acoustic sensor networks (UASNs). The detection information returned from a mobile node is meaningful only if its location is known. In this paper, we propose two localization algorithms based on color filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively accomplishing accurate localization of underwater mobile nodes with minimum energy expenditure. They both adopt the overlapping signal region of task anchors which can communicate with the mobile node directly as the current sampling area. PCFL employs the projected distances between each of the task projections and the mobile node, while ACFL adopts the direct distance between each of the task anchors and the mobile node. The proportion factor of distance is also proposed to weight the RGB values. By comparing the nearness degrees of the RGB sequences between the samples and the mobile node, samples can be filtered out. The normalized nearness degrees are considered as the weighted standards to calculate the coordinates of the mobile nodes. The simulation results show that the proposed methods have excellent localization performance and can localize the mobile node in a timely way. The average localization error of PCFL is decreased by about 30.4% compared to the AFLA method. PMID:25774706

Understanding the role of contrasting urban contexts in healthy aging: an international cohort study using wearable sensor devices (the CURHA study protocol).

PubMed

Kestens, Yan; Chaix, Basile; Gerber, Philippe; Desprès, Michel; Gauvin, Lise; Klein, Olivier; Klein, Sylvain; Köppen, Bernhard; Lord, Sébastien; Naud, Alexandre; Payette, Hélène; Richard, Lucie; Rondier, Pierre; Shareck, Martine; Sueur, Cédric; Thierry, Benoit; Vallée, Julie; Wasfi, Rania

2016-05-05

Given the challenges of aging populations, calls have been issued for more sustainable urban re-development and implementation of local solutions to address global environmental and healthy aging issues. However, few studies have considered older adults' daily mobility to better understand how local built and social environments may contribute to healthy aging. Meanwhile, wearable sensors and interactive map-based applications offer novel means for gathering information on people's mobility, levels of physical activity, or social network structure. Combining such data with classical questionnaires on well-being, physical activity, perceived environments and qualitative assessment of experience of places opens new opportunities to assess the complex interplay between individuals and environments. In line with current gaps and novel analytical capabilities, this research proposes an international research agenda to collect and analyse detailed data on daily mobility, social networks and health outcomes among older adults using interactive web-based questionnaires and wearable sensors. Our study resorts to a battery of innovative data collection methods including use of a novel multisensor device for collection of location and physical activity, interactive map-based questionnaires on regular destinations and social networks, and qualitative assessment of experience of places. This rich data will allow advanced quantitative and qualitative analyses in the aim to disentangle the complex people-environment interactions linking urban local contexts to healthy aging, with a focus on active living, social networks and participation, and well-being. This project will generate evidence about what characteristics of urban environments relate to active mobility, social participation, and well-being, three important dimensions of healthy aging. It also sets the basis for an international research agenda on built environment and healthy aging based on a shared and comprehensive data collection protocol.

Robust multiple frequency multiple power localization schemes in the presence of multiple jamming attacks

PubMed Central

2017-01-01

Localization of the wireless sensor network is a vital area acquiring an impressive research concern and called upon to expand more with the rising of its applications. As localization is gaining prominence in wireless sensor network, it is vulnerable to jamming attacks. Jamming attacks disrupt communication opportunity among the sender and receiver and deeply impact the localization process, leading to a huge error of the estimated sensor node position. Therefore, detection and elimination of jamming influence are absolutely indispensable. Range-based techniques especially Received Signal Strength (RSS) is facing severe impact of these attacks. This paper proposes algorithms based on Combination Multiple Frequency Multiple Power Localization (C-MFMPL) and Step Function Multiple Frequency Multiple Power Localization (SF-MFMPL). The algorithms have been tested in the presence of multiple types of jamming attacks including capture and replay, random and constant jammers over a log normal shadow fading propagation model. In order to overcome the impact of random and constant jammers, the proposed method uses two sets of frequencies shared by the implemented anchor nodes to obtain the averaged RSS readings all over the transmitted frequencies successfully. In addition, three stages of filters have been used to cope with the replayed beacons caused by the capture and replay jammers. In this paper the localization performance of the proposed algorithms for the ideal case which is defined by without the existence of the jamming attack are compared with the case of jamming attacks. The main contribution of this paper is to achieve robust localization performance in the presence of multiple jamming attacks under log normal shadow fading environment with a different simulation conditions and scenarios. PMID:28493977

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

PubMed Central

Wang, Jie-Sheng; Han, Shuang

2015-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:26583034

The “Wireless Sensor Networks for City-Wide Ambient Intelligence (WISE-WAI)” Project

PubMed Central

Casari, Paolo; Castellani, Angelo P.; Cenedese, Angelo; Lora, Claudio; Rossi, Michele; Schenato, Luca; Zorzi, Michele

2009-01-01

This paper gives a detailed technical overview of some of the activities carried out in the context of the “Wireless Sensor networks for city-Wide Ambient Intelligence (WISE-WAI)” project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide. These applications include long-term environmental monitoring, alarm event detection and propagation, single-sensor interrogation, localization and tracking of objects, assisted navigation, as well as fast data dissemination services to be used, e.g., to rapidly re-program all sensors over-the-air. The organization of such a large testbed requires notable efforts in terms of communication protocols and strategies, whose design must pursue scalability, energy efficiency (while sensors are connected through USB cables for logging and debugging purposes, most of them will be battery-operated), as well as the capability to support applications with diverse requirements. These efforts, the description of a subset of the results obtained so far, and of the final objectives to be met are the scope of the present paper. PMID:22408513

Model-Based Design of Tree WSNs for Decentralized Detection.

PubMed

Tantawy, Ashraf; Koutsoukos, Xenofon; Biswas, Gautam

2015-08-20

The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches.

Nearest neighbor imputation using spatial–temporal correlations in wireless sensor networks

PubMed Central

Li, YuanYuan; Parker, Lynne E.

2016-01-01

Missing data is common in Wireless Sensor Networks (WSNs), especially with multi-hop communications. There are many reasons for this phenomenon, such as unstable wireless communications, synchronization issues, and unreliable sensors. Unfortunately, missing data creates a number of problems for WSNs. First, since most sensor nodes in the network are battery-powered, it is too expensive to have the nodes retransmit missing data across the network. Data re-transmission may also cause time delays when detecting abnormal changes in an environment. Furthermore, localized reasoning techniques on sensor nodes (such as machine learning algorithms to classify states of the environment) are generally not robust enough to handle missing data. Since sensor data collected by a WSN is generally correlated in time and space, we illustrate how replacing missing sensor values with spatially and temporally correlated sensor values can significantly improve the network’s performance. However, our studies show that it is important to determine which nodes are spatially and temporally correlated with each other. Simple techniques based on Euclidean distance are not sufficient for complex environmental deployments. Thus, we have developed a novel Nearest Neighbor (NN) imputation method that estimates missing data in WSNs by learning spatial and temporal correlations between sensor nodes. To improve the search time, we utilize a kd-tree data structure, which is a non-parametric, data-driven binary search tree. Instead of using traditional mean and variance of each dimension for kd-tree construction, and Euclidean distance for kd-tree search, we use weighted variances and weighted Euclidean distances based on measured percentages of missing data. We have evaluated this approach through experiments on sensor data from a volcano dataset collected by a network of Crossbow motes, as well as experiments using sensor data from a highway traffic monitoring application. Our experimental results show that our proposed 𝒦-NN imputation method has a competitive accuracy with state-of-the-art Expectation–Maximization (EM) techniques, while using much simpler computational techniques, thus making it suitable for use in resource-constrained WSNs. PMID:28435414

Reliability based impact localization in composite panels using Bayesian updating and the Kalman filter

NASA Astrophysics Data System (ADS)

Morse, Llewellyn; Sharif Khodaei, Zahra; Aliabadi, M. H.

2018-01-01

In this work, a reliability based impact detection strategy for a sensorized composite structure is proposed. Impacts are localized using Artificial Neural Networks (ANNs) with recorded guided waves due to impacts used as inputs. To account for variability in the recorded data under operational conditions, Bayesian updating and Kalman filter techniques are applied to improve the reliability of the detection algorithm. The possibility of having one or more faulty sensors is considered, and a decision fusion algorithm based on sub-networks of sensors is proposed to improve the application of the methodology to real structures. A strategy for reliably categorizing impacts into high energy impacts, which are probable to cause damage in the structure (true impacts), and low energy non-damaging impacts (false impacts), has also been proposed to reduce the false alarm rate. The proposed strategy involves employing classification ANNs with different features extracted from captured signals used as inputs. The proposed methodologies are validated by experimental results on a quasi-isotropic composite coupon impacted with a range of impact energies.

New distributed fusion filtering algorithm based on covariances over sensor networks with random packet dropouts

NASA Astrophysics Data System (ADS)

Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

2017-07-01

This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example.

Structural health monitoring using a hybrid network of self-powered accelerometer and strain sensors

NASA Astrophysics Data System (ADS)

Alavi, Amir H.; Hasni, Hassene; Jiao, Pengcheng; Lajnef, Nizar

2017-04-01

This paper presents a structural damage identification approach based on the analysis of the data from a hybrid network of self-powered accelerometer and strain sensors. Numerical and experimental studies are conducted on a plate with bolted connections to verify the method. Piezoelectric ceramic Lead Zirconate Titanate (PZT)-5A ceramic discs and PZT-5H bimorph accelerometers are placed on the surface of the plate to measure the voltage changes due to damage progression. Damage is defined by loosening or removing one bolt at a time from the plate. The results show that the PZT accelerometers provide a fairly more consistent behavior than the PZT strain sensors. While some of the PZT strain sensors are not sensitive to the changes of the boundary condition, the bimorph accelerometers capture the mode changes from undamaged to missing bolt conditions. The results corresponding to the strain sensors are better indicator to the location of damage compared to the accelerometers. The characteristics of the overall structure can be monitored with even one accelerometer. On the other hand, several PZT strain sensors might be needed to localize the damage.

Node Scheduling Strategies for Achieving Full-View Area Coverage in Camera Sensor Networks.

PubMed

Wu, Peng-Fei; Xiao, Fu; Sha, Chao; Huang, Hai-Ping; Wang, Ru-Chuan; Xiong, Nai-Xue

2017-06-06

Unlike conventional scalar sensors, camera sensors at different positions can capture a variety of views of an object. Based on this intrinsic property, a novel model called full-view coverage was proposed. We study the problem that how to select the minimum number of sensors to guarantee the full-view coverage for the given region of interest (ROI). To tackle this issue, we derive the constraint condition of the sensor positions for full-view neighborhood coverage with the minimum number of nodes around the point. Next, we prove that the full-view area coverage can be approximately guaranteed, as long as the regular hexagons decided by the virtual grid are seamlessly stitched. Then we present two solutions for camera sensor networks in two different deployment strategies. By computing the theoretically optimal length of the virtual grids, we put forward the deployment pattern algorithm (DPA) in the deterministic implementation. To reduce the redundancy in random deployment, we come up with a local neighboring-optimal selection algorithm (LNSA) for achieving the full-view coverage. Finally, extensive simulation results show the feasibility of our proposed solutions.

Node Scheduling Strategies for Achieving Full-View Area Coverage in Camera Sensor Networks

PubMed Central

Wu, Peng-Fei; Xiao, Fu; Sha, Chao; Huang, Hai-Ping; Wang, Ru-Chuan; Xiong, Nai-Xue

2017-01-01

Unlike conventional scalar sensors, camera sensors at different positions can capture a variety of views of an object. Based on this intrinsic property, a novel model called full-view coverage was proposed. We study the problem that how to select the minimum number of sensors to guarantee the full-view coverage for the given region of interest (ROI). To tackle this issue, we derive the constraint condition of the sensor positions for full-view neighborhood coverage with the minimum number of nodes around the point. Next, we prove that the full-view area coverage can be approximately guaranteed, as long as the regular hexagons decided by the virtual grid are seamlessly stitched. Then we present two solutions for camera sensor networks in two different deployment strategies. By computing the theoretically optimal length of the virtual grids, we put forward the deployment pattern algorithm (DPA) in the deterministic implementation. To reduce the redundancy in random deployment, we come up with a local neighboring-optimal selection algorithm (LNSA) for achieving the full-view coverage. Finally, extensive simulation results show the feasibility of our proposed solutions. PMID:28587304

A novel optical fiber displacement sensor of wider measurement range based on neural network

NASA Astrophysics Data System (ADS)

Guo, Yuan; Dai, Xue Feng; Wang, Yu Tian

2006-02-01

By studying on the output characteristics of random type optical fiber sensor and semicircular type optical fiber sensor, the ratio of the two output signals was used as the output signal of the whole system. Then the measurement range was enlarged, the linearity was improved, and the errors of reflective and absorbent changing of target surface are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network(ANN) is set up. So the intrinsic errors such as effects of fluctuations in the light, circuit excursion, the intensity losses in the fiber lines and the additional losses in the receiving fiber caused by bends are eliminated. By discussing in theory and experiment, the error of nonlinear is 2.9%, the measuring range reaches to 5-6mm and the relative accuracy is 2%.And this sensor has such characteristics as no electromagnetic interference, simple construction, high sensitivity, good accuracy and stability. Also the multi-point sensor system can be used to on-line and non-touch monitor in working locales.

Development of Smart Grid for Community and Cyber based Landslide Hazard Monitoring and Early Warning System

NASA Astrophysics Data System (ADS)

Karnawati, D.; Wilopo, W.; Fathani, T. F.; Fukuoka, H.; Andayani, B.

2012-12-01

A Smart Grid is a cyber-based tool to facilitate a network of sensors for monitoring and communicating the landslide hazard and providing the early warning. The sensor is designed as an electronic sensor installed in the existing monitoring and early warning instruments, and also as the human sensors which comprise selected committed-people at the local community, such as the local surveyor, local observer, member of the local task force for disaster risk reduction, and any person at the local community who has been registered to dedicate their commitments for sending reports related to the landslide symptoms observed at their living environment. This tool is designed to be capable to receive up to thousands of reports/information at the same time through the electronic sensors, text message (mobile phone), the on-line participatory web as well as various social media such as Twitter and Face book. The information that should be recorded/ reported by the sensors is related to the parameters of landslide symptoms, for example the progress of cracks occurrence, ground subsidence or ground deformation. Within 10 minutes, this tool will be able to automatically elaborate and analyse the reported symptoms to predict the landslide hazard and risk levels. The predicted level of hazard/ risk can be sent back to the network of electronic and human sensors as the early warning information. The key parameters indicating the symptoms of landslide hazard were recorded/ monitored by the electrical and the human sensors. Those parameters were identified based on the investigation on geological and geotechnical conditions, supported with the laboratory analysis. The cause and triggering mechanism of landslide in the study area was also analysed in order to define the critical condition to launch the early warning. However, not only the technical but also social system were developed to raise community awareness and commitments to serve the mission as the human sensors, which will be responsible for reporting and informing the early warning. Therefore, a community empowerment and encouragement program through public education was conducted. Strategy and approach for this program was formulated based on the socio-engineering investigation. Finally, the results of technical and social engineering investigations, have been elaborated to further enhance the performance of expert system of the Smart Grid, in order to completely establish this system as an innovative and effective tool for the landslide monitoring and early warning in tropical-developing country.

Mobile device geo-localization and object visualization in sensor networks

NASA Astrophysics Data System (ADS)

Lemaire, Simon; Bodensteiner, Christoph; Arens, Michael

2014-10-01

In this paper we present a method to visualize geo-referenced objects on modern smartphones using a multi- functional application design. The application applies different localization and visualization methods including the smartphone camera image. The presented application copes well with different scenarios. A generic application work flow and augmented reality visualization techniques are described. The feasibility of the approach is experimentally validated using an online desktop selection application in a network with a modern of-the-shelf smartphone. Applications are widespread and include for instance crisis and disaster management or military applications.

Decentralized Dimensionality Reduction for Distributed Tensor Data Across Sensor Networks.

PubMed

Liang, Junli; Yu, Guoyang; Chen, Badong; Zhao, Minghua

2016-11-01

This paper develops a novel decentralized dimensionality reduction algorithm for the distributed tensor data across sensor networks. The main contributions of this paper are as follows. First, conventional centralized methods, which utilize entire data to simultaneously determine all the vectors of the projection matrix along each tensor mode, are not suitable for the network environment. Here, we relax the simultaneous processing manner into the one-vector-by-one-vector (OVBOV) manner, i.e., determining the projection vectors (PVs) related to each tensor mode one by one. Second, we prove that in the OVBOV manner each PV can be determined without modifying any tensor data, which simplifies corresponding computations. Third, we cast the decentralized PV determination problem as a set of subproblems with consensus constraints, so that it can be solved in the network environment only by local computations and information communications among neighboring nodes. Fourth, we introduce the null space and transform the PV determination problem with complex orthogonality constraints into an equivalent hidden convex one without any orthogonality constraint, which can be solved by the Lagrange multiplier method. Finally, experimental results are given to show that the proposed algorithm is an effective dimensionality reduction scheme for the distributed tensor data across the sensor networks.

Applying traditional signal processing techniques to social media exploitation for situational understanding

NASA Astrophysics Data System (ADS)

Abdelzaher, Tarek; Roy, Heather; Wang, Shiguang; Giridhar, Prasanna; Al Amin, Md. Tanvir; Bowman, Elizabeth K.; Kolodny, Michael A.

2016-05-01

Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social networks as noisy sensors that report events in the physical world. We then present a data processing stack for detection, localization, tracking, and veracity analysis of reported events using social network data. We show using a controlled experiment that the behavior of social sources as information relays varies dramatically depending on context. In benign contexts, there is general agreement on events, whereas in conflict scenarios, a significant amount of collective filtering is introduced by conflicted groups, creating a large data distortion. We describe signal processing techniques that mitigate such distortion, resulting in meaningful approximations of actual ground truth, given noisy reported observations. Finally, we briefly present an implementation of the aforementioned social network data processing stack in a sensor network analysis toolkit, called Apollo. Experiences with Apollo show that our techniques are successful at identifying and tracking credible events in the physical world.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S; Sen, Satyabrata; Berry, M. L..

Domestic Nuclear Detection Office s (DNDO) Intelligence Radiation Sensors Systems (IRSS) program supported the development of networks of commercial-off-the-shelf (COTS) radiation counters for detecting, localizing, and identifying low-level radiation sources. Under this program, a series of indoor and outdoor tests were conducted with multiple source strengths and types, different background profiles, and various types of source and detector movements. Following the tests, network algorithms were replayed in various re-constructed scenarios using sub-networks. These measurements and algorithm traces together provide a rich collection of highly valuable datasets for testing the current and next generation radiation network algorithms, including the ones (tomore » be) developed by broader R&D communities such as distributed detection, information fusion, and sensor networks. From this multiple TeraByte IRSS database, we distilled out and packaged the first batch of canonical datasets for public release. They include measurements from ten indoor and two outdoor tests which represent increasingly challenging baseline scenarios for robustly testing radiation network algorithms.« less

Challenges and Opportunities to Developing Synergies Among Diverse Environmental Observatories: FSML, NEON, and GLEON

NASA Astrophysics Data System (ADS)

Williamson, C. E.; Weathers, K. C.; Knoll, L. B.; Brentrup, J.

2012-12-01

Recent rapid advances in sensor technology and cyberinfrastructure have enabled the development of numerous environmental observatories ranging from local networks at field stations and marine laboratories (FSML) to continental scale observatories such as the National Ecological Observatory Network (NEON) to global scale observatories such as the Global Lake Ecological Observatory Network (GLEON). While divergent goals underlie the initial development of these observatories, and they are often designed to serve different communities, many opportunities for synergies exist. In addition, the use of existing infrastructure may enhance the cost-effectiveness of building and maintaining large scale observatories. For example, FSMLs are established facilities with the staff and infrastructure to host sensor nodes of larger networks. Many field stations have existing staff and long-term databases as well as smaller sensor networks that are the product of a single or small group of investigators with a unique data management system embedded in a local or regional community. These field station based facilities and data are a potentially untapped gold mine for larger continental and global scale observatories; common ecological and environmental challenges centered on understanding the impacts of changing climate, land use, and invasive species often underlie these efforts. The purpose of this talk is to stimulate a dialog on the challenges of merging efforts across these different spatial and temporal scales, as well as addressing how to develop synergies among observatory networks with divergent roots and philosophical approaches. For example, FSMLs have existing long-term databases and facilities, while NEON has sparse past data but a well-developed template and closely coordinated team working in a coherent format across a continental scale. GLEON on the other hand is a grass-roots network of experts in science, information technology, and engineering with a common goal of building a scalable network around the world to understand and predict how lakes respond to global change. Creating synergies among networks at these divergent scales requires open discussions ranging from data collection and management to data serving and sharing. Coordination of these efforts can provide an additional opportunity to educate both students and the public in innovative new ways about the broader continental to global scale of ecological and environmental challenges that they have observed in their more local ecosystems.

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms

PubMed Central

Zhang, Ying; Liang, Jixing; Jiang, Shengming; Chen, Wei

2016-01-01

Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO) is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object’s mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field. PMID:26861348

Survey of energy harvesting and energy scavenging approaches for on-site powering of wireless sensor- and microinstrument-networks

NASA Astrophysics Data System (ADS)

Lee, D.; Dulai, G.; Karanassios, Vassili

2013-05-01

Energy (or power) harvesting can be defined as the gathering and either storing or immediately using energy "freely" available in a local environment. Examples include harvesting energy from obvious sources such as photon-fluxes (e.g., solar), or wind or water waves, or from unusual sources such as naturally occurring pH differences. Energy scavenging can be defined as gathering and storing or immediately re-using energy that has been discarded, for instance, waste heat from air conditioning units, from in-door lights or from everyday actions such as walking or from body-heat. Although the power levels that can be harvested or scavenged are typically low (e.g., from nWatt/cm2 to mWatt/cm2), the key motivation is to harvest or to scavenge energy for a wide variety of applications. Example applications include powering devices in remote weather stations, or wireless Bluetooth headsets, or wearable computing devices or for sensor networks for health and bio-medical applications. Beyond sensors and sensor networks, there is a need to power compete systems, such as portable and energy-autonomous chemical analysis microinstruments for use on-site. A portable microinstrument is one that offers the same functionality as a large one but one that has at least one critical component in the micrometer regime. This paper surveys continuous or discontinuous energy harvesting and energy scavenging approaches (with particular emphasis on sensor and microinstrument networks) and it discusses current trends. It also briefly explores potential future directions, for example, for nature-inspired (e.g., photosynthesis), for human-power driven (e.g., for biomedical applications, or for wearable sensor networks) or for nanotechnology-enabled energy harvesting and energy scavenging approaches.

Calculating distance by wireless ethernet signal strength for global positioning method

NASA Astrophysics Data System (ADS)

Kim, Seung-Yong; Kim, Jeehong; Lee, Chang-goo

2005-12-01

This paper investigated mobile robot localization by using wireless Ethernet for global localization and INS for relative localization. For relative localization, the low-cost INS features self-contained was adopted. Low-cost MEMS-based INS has a short-period response and acceptable performance. Generally, variety sensor was used for mobile robot localization. In spite of precise modeling of the sensor, it leads inevitably to the accumulation of errors. The IEEE802.11b wireless Ethernet standard has been deployed in office building, museums, hospitals, shopping centers and other indoor environments. Many mobile robots already make use of wireless networking for communication. So location sensing with wireless Ethernet might be very useful for a low-cost robot. This research used wireless Ethernet card for compensation the accumulation of errors. So the mobile robot can use that for global localization through the installed many IEEE802.11b wireless Ethernets in indoor environments. The chief difficulty in localization with wireless Ethernet is predicting signal strength. As a sensor, RF signal strength measured indoors is non-linear with distance. So, there made the profiles of signal strength for points and used that. We wrote using function between signal strength profile and distance from the wireless Ethernet point.

SoilSCAPE in-Situ Observations of Soil Moisture for SMAP Validation: Pushing the Envelopes of Spatial Coverage and Energy Efficiency in Sparse Wireless Sensor Networks (Invited)

NASA Astrophysics Data System (ADS)

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

2013-12-01

Soil Moisture Sensing Controller and oPtimal Estimator (SoilSCAPE) is a wireless in-situ sensor network technology, developed under the support of NASA ESTO/AIST program, for multi-scale validation of soil moisture retrievals from the Soil Moisture Active and Passive (SMAP) mission. The SMAP sensor suite is expected to produce soil moisture retrievals at 3 km scale from the radar instrument, at 36 km from the radiometer, and at 10 km from the combination of the two sensors. To validate the retrieved soil moisture maps at any of these scales, it is necessary to perform in-situ observations at multiple scales (ten, hundreds, and thousands of meters), representative of the true spatial variability of soil moisture fields. The most recent SoilSCAPE network, deployed in the California central valley, has been designed, built, and deployed to accomplish this goal, and is expected to become a core validation site for SMAP. The network consists of up to 150 sensor nodes, each comprised of 3-4 soil moisture sensors at various depths, deployed over a spatial extent of 36 km by 36 km. The network contains multiple sub-networks, each having up to 30 nodes, whose location is selected in part based on maximizing the land cover diversity within the 36 km cell. The network has achieved unprecedented energy efficiency, longevity, and spatial coverage using custom-designed hardware and software protocols. The network architecture utilizes a nested strategy, where a number of end devices (EDs) communicate to a local coordinator (LC) using our recently developed hardware with ultra-efficient circuitry and best-effort-timeslot allocation communication protocol. The LCs in turn communicates with the base station (BS) via text messages and a new compression scheme. The hardware and software technologies required to implement this latest deployment of the SoilSCAPE network will be presented in this paper, and several data sets resulting from the measurements will be shown. The data are available publicly in near-real-time from the project web site, and are also available and searchable via an extensive set of metadata fields through the ORNL-DAAC.

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Spatial and temporal trends from an air quality sensor network near a heavily trafficked intersection

NASA Astrophysics Data System (ADS)

Orlando, P.; Vo, D.; Giossi, C.; George, L.

2017-12-01

With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.

Model-Free Stochastic Localization of CBRN Releases

DTIC Science & Technology

2013-01-01

Ioannis Ch. Paschalidis,‡ Senior Member, IEEE Abstract—We present a novel two-stage methodology for locating a Chemical, Biological, Radiological, or...Nuclear (CBRN) source in an urban area using a network of sensors. In contrast to earlier work, our approach does not solve an inverse dispersion problem...but relies on data obtained from a simulation of the CBRN dispersion to obtain probabilistic descriptors of sensor measurements under a variety of CBRN

Collaborative Catchment-Scale Water Quality Management using Integrated Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Zia, Huma; Harris, Nick; Merrett, Geoff

2013-04-01

Electronics and Computer Science, University of Southampton, United Kingdom Summary The challenge of improving water quality (WQ) is a growing global concern [1]. Poor WQ is mainly attributed to poor water management and outdated agricultural activities. We propose that collaborative sensor networks spread across an entire catchment can allow cooperation among individual activities for integrated WQ monitoring and management. We show that sharing information on critical parameters among networks of water bodies and farms can enable identification and quantification of the contaminant sources, enabling better decision making for agricultural practices and thereby reducing contaminants fluxes. Motivation and results Nutrient losses from land to water have accelerated due to agricultural and urban pursuits [2]. In many cases, the application of fertiliser can be reduced by 30-50% without any loss of yield [3]. Thus information about nutrient levels and trends around the farm can improve agricultural practices and thereby reduce water contamination. The use of sensor networks for monitoring WQ in a catchment is in its infancy, but more applications are being tested [4]. However, these are focussed on local requirements and are mostly limited to water bodies. They have yet to explore the use of this technology for catchment-scale monitoring and management decisions, in an autonomous and dynamic manner. For effective and integrated WQ management, we propose a system that utilises local monitoring networks across a catchment, with provision for collaborative information sharing. This system of networks shares information about critical events, such as rain or flooding. Higher-level applications make use of this information to inform decisions about nutrient management, improving the quality of monitoring through the provision of richer datasets of catchment information to local networks. In the full paper, we present example scenarios and analyse how the benefits of collaborative information sharing can have a direct influence on agricultural practice. We apply a nutrient management scheme to a model of an example catchment with several individual networks. The networks are able to correlate catchment events to events within their zone of influence, allowing them to adapt their monitoring and control strategy in light of wider changes across the catchment. Results indicate that this can lead to significant reductions in nutrient losses (up to 50%) and better reutilization of nutrients amongst farms, having a positive impact on catchment scale water quality and fertilizer costs. 1. EC, E.C., Directive 2000/60/EC establishing a framework for Community action in the field of water policy, 2000. 2. Rivers, M., K. Smettem, and P. Davies. Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling-Can on-farm BMPs really do the job at the watershed scale? in Proc.29th Int.Conf System Dynamics Society, 2011. 2010. Washington 3. Liu, C., et al., On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal, 2008. 100(6): p. 1527-1534. 4. Kotamäki, N., et al., Wireless in-situ sensor network for agriculture and water monitoring on a river basin scale in Southern Finland: Evaluation from a data user's perspective. Sensors, 2009. 9(4): p. 2862-2883.

Browsing the Real World using Organic Electronics, Si-Chips, and a Human Touch.

PubMed

Berggren, Magnus; Simon, Daniel T; Nilsson, David; Dyreklev, Peter; Norberg, Petronella; Nordlinder, Staffan; Ersman, Peter Andersson; Gustafsson, Göran; Wikner, J Jacob; Hederén, Jan; Hentzell, Hans

2016-03-09

Organic electronics have been developed according to an orthodox doctrine advocating "all-printed'', "all-organic'' and "ultra-low-cost'' primarily targeting various e-paper applications. In order to harvest from the great opportunities afforded with organic electronics potentially operating as communication and sensor outposts within existing and future complex communication infrastructures, high-quality computing and communication protocols must be integrated with the organic electronics. Here, we debate and scrutinize the twinning of the signal-processing capability of traditional integrated silicon chips with organic electronics and sensors, and to use our body as a natural local network with our bare hand as the browser of the physical world. The resulting platform provides a body network, i.e., a personalized web, composed of e-label sensors, bioelectronics, and mobile devices that together make it possible to monitor and record both our ambience and health-status parameters, supported by the ubiquitous mobile network and the resources of the "cloud". © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Test and Evaluation of a Prototyped Sensor-Camera Network for Persistent Intelligence, Surveillance, and Reconnaissance in Support of Tactical Coalition Networking Environments

DTIC Science & Technology

2006-06-01

scenarios. The demonstration planned for May 2006, in Chiang Mai , Thailand, will have a first-responder, law enforcement, and counter-terrorism and counter...to local ( Chiang Mai ), theater (Bangkok), and global (Alameda, California) command and control centers. This fusion of information validates using...network performance to be tested during moderate environmental conditions. The third and fourth scenarios were conducted in Chiang Mai , Thailand

Secure and lightweight network admission and transmission protocol for body sensor networks.

PubMed

He, Daojing; Chen, Chun; Chan, Sammy; Bu, Jiajun; Zhang, Pingxin

2013-05-01

A body sensor network (BSN) is a wireless network of biosensors and a local processing unit, which is commonly referred to as the personal wireless hub (PWH). Personal health information (PHI) is collected by biosensors and delivered to the PWH before it is forwarded to the remote healthcare center for further processing. In a BSN, it is critical to only admit eligible biosensors and PWH into the network. Also, securing the transmission from each biosensor to PWH is essential not only for ensuring safety of PHI delivery, but also for preserving the privacy of PHI. In this paper, we present the design, implementation, and evaluation of a secure network admission and transmission subsystem based on a polynomial-based authentication scheme. The procedures in this subsystem to establish keys for each biosensor are communication efficient and energy efficient. Moreover, based on the observation that an adversary eavesdropping in a BSN faces inevitable channel errors, we propose to exploit the adversary's uncertainty regarding the PHI transmission to update the individual key dynamically and improve key secrecy. In addition to the theoretical analysis that demonstrates the security properties of our system, this paper also reports the experimental results of the proposed protocol on resource-limited sensor platforms, which show the efficiency of our system in practice.

Intelligent route surveillance

NASA Astrophysics Data System (ADS)

Schoemaker, Robin; Sandbrink, Rody; van Voorthuijsen, Graeme

2009-05-01

Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent ground sensor networks use simple sensing nodes, e.g. seismic, magnetic, radar, or acoustic, or combinations of these in one housing. The nodes deliver rudimentary data at any time to be processed with software that filters out the required information. At TNO (Netherlands Organisation for Applied Scientific Research) research has started on how to equip a sensor network with data analysis software to determine whether behaviour is suspicious or not. Furthermore, the nodes should be expendable, if necessary, and be small in size such that they are hard to detect by adversaries. The network should be self-configuring and self-sustaining and should be reliable, efficient, and effective during operational tasks - especially route surveillance - as well as robust in time and space. If data from these networks are combined with data from other remote sensing devices (e.g. UAVs (Unmanned Aerial Vehicles)/aerostats), an even more accurate assessment of the tactical situation is possible. This paper shall focus on the concepts of operation towards a working intelligent route surveillance (IRS) research demonstrator network for monitoring suspicious behaviour in IED sensitive domains.

Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

NASA Astrophysics Data System (ADS)

Jiao, Wan; Hagler, Gayle; Williams, Ronald; Sharpe, Robert; Brown, Ryan; Garver, Daniel; Judge, Robert; Caudill, Motria; Rickard, Joshua; Davis, Michael; Weinstock, Lewis; Zimmer-Dauphinee, Susan; Buckley, Ken

2016-11-01

Advances in air pollution sensor technology have enabled the development of small and low-cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low-cost, continuous, and commercially available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ˜ 2 km area in the southeastern United States. Collocation of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as the degree to which multiple identical sensors produced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, and -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r < 0.5) with a reference monitor and erroneously high concentration values. A wide variety of particulate matter (PM) sensors were tested with variable results - some sensors had very high agreement (e.g., r = 0.99) between identical sensors but moderate agreement with a reference PM2.5 monitor (e.g., r = 0.65). For select sensors that had moderate to strong correlation with reference monitors (r > 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in number of sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference, incorporating all factors, was observed for an NO2 sensor (multiple correlation coefficient R2adj-orig = 0.57, R2adj-final = 0.81); however, other sensors showed no apparent improvement in agreement. A four-node sensor network was successfully able to capture ozone (two nodes) and PM (four nodes) data for an 8-month period of time and show expected diurnal concentration patterns, as well as potential ozone titration due to nearby traffic emissions. Overall, this study demonstrates the performance of emerging air quality sensor technologies in a real-world setting; the variable agreement between sensors and reference monitors indicates that in situ testing of sensors against benchmark monitors should be a critical aspect of all field studies.

Estimating Snow Water Equivalent over the American River in the Sierra Nevada Basin Using Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Welch, S. C.; Kerkez, B.; Glaser, S. D.; Bales, R. C.; Rice, R.

2011-12-01

We have designed a basin-scale (>2000 km2) instrument cluster, made up of 20 local-scale (1-km footprint) wireless sensor networks (WSNs), to measure patterns of snow depth and snow water equivalent (SWE) across the main snowmelt producing area within the American River basin. Each of the 20 WSNs has on the order of 25 wireless nodes, with over 10 nodes actively sensing snow depth, and thus snow accumulation and melt. When combined with existing snow density measurements and full-basin satellite snowcover data, these measurements are designed to provide dense ground-truth snow properties for research and real-time SWE for water management. The design of this large-scale network is based on rigorous testing of previous, smaller-scale studies, permitting for the development of methods to significantly, and efficiently scale up network operations. Recent advances in WSN technology have resulted in a modularized strategy that permits rapid future network deployment. To select network and sensor locations, various sensor placement approaches were compared, including random placement, placement of WSNs in locations that have captured the historical basin mean, as well as a placement algorithm leveraging the covariance structure of the SWE distribution. We show that that the optimal network locations do not exhibit a uniform grid, but rather follow strategic patterns based on physiographic terrain parameters. Uncertainty estimates are also provided to assess the confidence in the placement approach. To ensure near-optimal coverage of the full basin, we validated each placement approach with a multi-year record of SWE derived from reconstruction of historical satellite measurements.

Mobile Sensor Technologies Being Developed

NASA Technical Reports Server (NTRS)

Greer, Lawrence C.; Oberle, Lawrence G.

2003-01-01

The NASA Glenn Research Center is developing small mobile platforms for sensor placement, as well as methods for communicating between roving platforms and a central command location. The first part of this project is to use commercially available equipment to miniaturize an existing sensor platform. We developed a five-circuit-board suite, with an average board size of 1.5 by 3 cm. Shown in the preceding photograph, this suite provides all motor control, direction finding, and communications capabilities for a 27- by 21- by 40-mm prototype mobile platform. The second part of the project is to provide communications between mobile platforms, and also between multiple platforms and a central command location. This is accomplished with a low-power network labeled "SPAN," Sensor Platform Area Network, a local area network made up of proximity elements. In practice, these proximity elements are composed of fixed- and mobile-sensor-laden science packages that communicate to each other via radiofrequency links. Data in the network will be shared by a central command location that will pass information into and out of the network through its access to a backbone element. The result will be a protocol portable to general purpose microcontrollers satisfying a host of sensor networking tasks. This network will enter the gap somewhere between television remotes and Bluetooth but, unlike 802.15.4, will not specify a physical layer, thus allowing for many data rates over optical, acoustical, radiofrequency, hardwire, or other media. Since the protocol will exist as portable C-code, developers may be able to embed it in a host of microcontrollers from commercial to space grade and, of course, to design it into ASICs. Unlike in 802.15.4, the nodes will relate to each other as peers. A demonstration of this protocol using the two test bed platforms was recently held. Two NASA modified, commercially available, mobile platforms communicated and shared data with each other and a central command location. Web-based control and interrogation of similar mobile sensor platforms have also been demonstrated. Expected applications of this technology include robotic planetary exploration, astronaut-to-equipment communication, and remote aerospace engine inspections.

Cellular telephone-based wide-area radiation detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2009-06-09

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

The world's microbiology laboratories can be a global microbial sensor network.

PubMed

O'Brien, Thomas F; Stelling, John

2014-04-01

The microbes that infect us spread in global and local epidemics, and the resistance genes that block their treatment spread within and between them. All we can know about where they are to track and contain them comes from the only places that can see them, the world's microbiology laboratories, but most report each patient's microbe only to that patient's caregiver. Sensors, ranging from instruments to birdwatchers, are now being linked in electronic networks to monitor and interpret algorithmically in real-time ocean currents, atmospheric carbon, supply-chain inventory, bird migration, etc. To so link the world's microbiology laboratories as exquisite sensors in a truly lifesaving real-time network their data must be accessed and fully subtyped. Microbiology laboratories put individual reports into inaccessible paper or mutually incompatible electronic reporting systems, but those from more than 2,200 laboratories in more than 108 countries worldwide are now accessed and translated into compatible WHONET files. These increasingly web-based files could initiate a global microbial sensor network. Unused microbiology laboratory byproduct data, now from drug susceptibility and biochemical testing but increasingly from new technologies (genotyping, MALDI-TOF, etc.), can be reused to subtype microbes of each genus/species into sub-groupings that are discriminated and traced with greater sensitivity. Ongoing statistical delineation of subtypes from global sensor network data will improve detection of movement into any patient of a microbe or resistance gene from another patient, medical center or country. Growing data on clinical manifestations and global distributions of subtypes can automate comments for patient's reports, select microbes to genotype and alert responders.

Model-Based Design of Tree WSNs for Decentralized Detection †

PubMed Central

Tantawy, Ashraf; Koutsoukos, Xenofon; Biswas, Gautam

2015-01-01

The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches. PMID:26307989

[The Development of Information Centralization and Management Integration System for Monitors Based on Wireless Sensor Network].

PubMed

Xu, Xiu; Zhang, Honglei; Li, Yiming; Li, Bin

2015-07-01

Developed the information centralization and management integration system for monitors of different brands and models with wireless sensor network technologies such as wireless location and wireless communication, based on the existing wireless network. With adaptive implementation and low cost, the system which possesses the advantages of real-time, efficiency and elaboration is able to collect status and data of the monitors, locate the monitors, and provide services with web server, video server and locating server via local network. Using an intranet computer, the clinical and device management staffs can access the status and parameters of monitors. Applications of this system provide convenience and save human resource for clinical departments, as well as promote the efficiency, accuracy and elaboration for the device management. The successful achievement of this system provides solution for integrated and elaborated management of the mobile devices including ventilator and infusion pump.

A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks.

PubMed

Gu, Xiangping; Zhou, Xiaofeng; Sun, Yanjing

2018-02-28

Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings' spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node's residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets' sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods.

A Practical Application Combining Wireless Sensor Networks and Internet of Things: Safety Management System for Tower Crane Groups

PubMed Central

Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

2014-01-01

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things. PMID:25196106

A practical application combining wireless sensor networks and Internet of Things: Safety Management System for Tower Crane Groups.

PubMed

Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

2014-07-30

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things.

Physical activity discrimination improvement using accelerometers and wireless sensor network localization - biomed 2013.

PubMed

Bashford, Gregory R; Burnfield, Judith M; Perez, Lance C

2013-01-01

Automating documentation of physical activity data (e.g., duration and speed of walking or propelling a wheelchair) into the electronic medical record (EMR) offers promise for improving efficiency of documentation and understanding of best practices in the rehabilitation and home health settings. Commercially available devices which could be used to automate documentation of physical activities are either cumbersome to wear or lack the specificity required to differentiate activities. We have designed a novel system to differentiate and quantify physical activities, using inexpensive accelerometer-based biomechanical data technology and wireless sensor networks, a technology combination that has not been used in a rehabilitation setting to date. As a first step, a feasibility study was performed where 14 healthy young adults (mean age = 22.6 ± 2.5 years, mean height = 173 ± 10.0 cm, mean mass = 70.7 ± 11.3 kg) carried out eight different activities while wearing a biaxial accelerometer sensor. Activities were performed at each participant’s self-selected pace during a single testing session in a controlled environment. Linear discriminant analysis was performed by extracting spectral parameters from the subjects’ accelerometer patterns. It is shown that physical activity classification alone results in an average accuracy of 49.5%, but when combined with rule-based constraints using a wireless sensor network with localization capabilities in an in silico simulated room, accuracy improves to 99.3%. When fully implemented, our technology package is expected to improve goal setting, treatment interventions and patient outcomes by enhancing clinicians’ understanding of patients’ physical performance within a day and across the rehabilitation program.

ANZA Seismic Network- From Monitoring to Science

NASA Astrophysics Data System (ADS)

Vernon, F.; Eakin, J.; Martynov, V.; Newman, R.; Offield, G.; Hindley, A.; Astiz, L.

2007-05-01

The ANZA Seismic Network (http:eqinfo.ucsd.edu) utilizes broadband and strong motion sensors with 24-bit dataloggers combined with real-time telemetry to monitor local and regional seismicity in southernmost California. The ANZA network provides real-time data to the IRIS DMC, California Integrated Seismic Network (CISN), other regional networks, and the Advanced National Seismic System (ANSS), in addition to providing near real-time information and monitoring to the greater San Diego community. Twelve high dynamic range broadband and strong motion sensors adjacent to the San Jacinto Fault zone contribute data for earthquake source studies and continue the monitoring of the seismic activity of the San Jacinto fault initiated 24 years ago. Five additional stations are located in the San Diego region with one more station on San Clemente Island. The ANZA network uses the advance wireless networking capabilities of the NSF High Performance Wireless Research and Education Network (http:hpwren.ucsd.edu) to provide the communication infrastructure for the real-time telemetry of Anza seismic stations. The ANZA network uses the Antelope data acquisition software. The combination of high quality hardware, communications, and software allow for an annual network uptime in excess of 99.5% with a median annual station real-time data return rate of 99.3%. Approximately 90,000 events, dominantly local sources but including regional and teleseismic events, comprise the ANZA network waveform database. All waveform data and event data are managed using the Datascope relational database. The ANZA network data has been used in a variety of scientific research including detailed structure of the San Jacinto Fault Zone, earthquake source physics, spatial and temporal studies of aftershocks, array studies of teleseismic body waves, and array studies on the source of microseisms. To augment the location, detection, and high frequency observations of the seismic source spectrum from local earthquakes, the ANZA network is receiving real-time data from borehole arrays located at the UCSD Thornton Hospital, and from UCSB's Borrego Valley and Garner Valley Downhole Arrays. Finally the ANZA network is acquiring data from seven PBO sites each with 300 meter deep MEMs accelerometers, passive seismometers, and a borehole strainmeter.

Alternative Path Communication in Wide-Scale Cluster-Tree Wireless Sensor Networks Using Inactive Periods

PubMed Central

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-01-01

The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable technology to deploy wide-scale Wireless Sensor Networks (WSNs). These networks are usually designed to support convergecast traffic, where all communication paths go through the PAN (Personal Area Network) coordinator. Nevertheless, peer-to-peer communication relationships may be also required for different types of WSN applications. That is the typical case of sensor and actuator networks, where local control loops must be closed using a reduced number of communication hops. The use of communication schemes optimised just for the support of convergecast traffic may result in higher network congestion and in a potentially higher number of communication hops. Within this context, this paper proposes an Alternative-Route Definition (ARounD) communication scheme for WSNs. The underlying idea of ARounD is to setup alternative communication paths between specific source and destination nodes, avoiding congested cluster-tree paths. These alternative paths consider shorter inter-cluster paths, using a set of intermediate nodes to relay messages during their inactive periods in the cluster-tree network. Simulation results show that the ARounD communication scheme can significantly decrease the end-to-end communication delay, when compared to the use of standard cluster-tree communication schemes. Moreover, the ARounD communication scheme is able to reduce the network congestion around the PAN coordinator, enabling the reduction of the number of message drops due to queue overflows in the cluster-tree network. PMID:28481245

Alternative Path Communication in Wide-Scale Cluster-Tree Wireless Sensor Networks Using Inactive Periods.

PubMed

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-05-06

The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable technology to deploy wide-scale Wireless Sensor Networks (WSNs). These networks are usually designed to support convergecast traffic, where all communication paths go through the PAN (Personal Area Network) coordinator. Nevertheless, peer-to-peer communication relationships may be also required for different types of WSN applications. That is the typical case of sensor and actuator networks, where local control loops must be closed using a reduced number of communication hops. The use of communication schemes optimised just for the support of convergecast traffic may result in higher network congestion and in a potentially higher number of communication hops. Within this context, this paper proposes an Alternative-Route Definition (ARounD) communication scheme for WSNs. The underlying idea of ARounD is to setup alternative communication paths between specific source and destination nodes, avoiding congested cluster-tree paths. These alternative paths consider shorter inter-cluster paths, using a set of intermediate nodes to relay messages during their inactive periods in the cluster-tree network. Simulation results show that the ARounD communication scheme can significantly decrease the end-to-end communication delay, when compared to the use of standard cluster-tree communication schemes. Moreover, the ARounD communication scheme is able to reduce the network congestion around the PAN coordinator, enabling the reduction of the number of message drops due to queue overflows in the cluster-tree network.

An Improved Approach for RSSI-Based only Calibration-Free Real-Time Indoor Localization on IEEE 802.11 and 802.15.4 Wireless Networks.

PubMed

Passafiume, Marco; Maddio, Stefano; Cidronali, Alessandro

2017-03-29

Assuming a reliable and responsive spatial contextualization service is a must-have in IEEE 802.11 and 802.15.4 wireless networks, a suitable approach consists of the implementation of localization capabilities, as an additional application layer to the communication protocol stack. Considering the applicative scenario where satellite-based positioning applications are denied, such as indoor environments, and excluding data packet arrivals time measurements due to lack of time resolution, received signal strength indicator (RSSI) measurements, obtained according to IEEE 802.11 and 802.15.4 data access technologies, are the unique data sources suitable for indoor geo-referencing using COTS devices. In the existing literature, many RSSI based localization systems are introduced and experimentally validated, nevertheless they require periodic calibrations and significant information fusion from different sensors that dramatically decrease overall systems reliability and their effective availability. This motivates the work presented in this paper, which introduces an approach for an RSSI-based calibration-free and real-time indoor localization. While switched-beam array-based hardware (compliant with IEEE 802.15.4 router functionality) has already been presented by the author, the focus of this paper is the creation of an algorithmic layer for use with the pre-existing hardware capable to enable full localization and data contextualization over a standard 802.15.4 wireless sensor network using only RSSI information without the need of lengthy offline calibration phase. System validation reports the localization results in a typical indoor site, where the system has shown high accuracy, leading to a sub-metrical overall mean error and an almost 100% site coverage within 1 m localization error.

An Improved Approach for RSSI-Based only Calibration-Free Real-Time Indoor Localization on IEEE 802.11 and 802.15.4 Wireless Networks

PubMed Central

Passafiume, Marco; Maddio, Stefano; Cidronali, Alessandro

2017-01-01

Assuming a reliable and responsive spatial contextualization service is a must-have in IEEE 802.11 and 802.15.4 wireless networks, a suitable approach consists of the implementation of localization capabilities, as an additional application layer to the communication protocol stack. Considering the applicative scenario where satellite-based positioning applications are denied, such as indoor environments, and excluding data packet arrivals time measurements due to lack of time resolution, received signal strength indicator (RSSI) measurements, obtained according to IEEE 802.11 and 802.15.4 data access technologies, are the unique data sources suitable for indoor geo-referencing using COTS devices. In the existing literature, many RSSI based localization systems are introduced and experimentally validated, nevertheless they require periodic calibrations and significant information fusion from different sensors that dramatically decrease overall systems reliability and their effective availability. This motivates the work presented in this paper, which introduces an approach for an RSSI-based calibration-free and real-time indoor localization. While switched-beam array-based hardware (compliant with IEEE 802.15.4 router functionality) has already been presented by the author, the focus of this paper is the creation of an algorithmic layer for use with the pre-existing hardware capable to enable full localization and data contextualization over a standard 802.15.4 wireless sensor network using only RSSI information without the need of lengthy offline calibration phase. System validation reports the localization results in a typical indoor site, where the system has shown high accuracy, leading to a sub-metrical overall mean error and an almost 100% site coverage within 1 m localization error. PMID:28353676

Localization Algorithm with On-line Path Loss Estimation and Node Selection

PubMed Central

Bel, Albert; Vicario, José López; Seco-Granados, Gonzalo

2011-01-01

RSS-based localization is considered a low-complexity algorithm with respect to other range techniques such as TOA or AOA. The accuracy of RSS methods depends on the suitability of the propagation models used for the actual propagation conditions. In indoor environments, in particular, it is very difficult to obtain a good propagation model. For that reason, we present a cooperative localization algorithm that dynamically estimates the path loss exponent by using RSS measurements. Since the energy consumption is a key point in sensor networks, we propose a node selection mechanism to limit the number of neighbours of a given node that are used for positioning purposes. Moreover, the selection mechanism is also useful to discard bad links that could negatively affect the performance accuracy. As a result, we derive a practical solution tailored to the strict requirements of sensor networks in terms of complexity, size and cost. We present results based on both computer simulations and real experiments with the Crossbow MICA2 motes showing that the proposed scheme offers a good trade-off in terms of position accuracy and energy efficiency. PMID:22163992

Lightweight Filter Architecture for Energy Efficient Mobile Vehicle Localization Based on a Distributed Acoustic Sensor Network

PubMed Central

Kim, Keonwook

2013-01-01

The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably. PMID:23979482

Supersonic projectile models for asynchronous shooter localization

NASA Astrophysics Data System (ADS)

Kozick, Richard J.; Whipps, Gene T.; Ash, Joshua N.

2011-06-01

In this work we consider the localization of a gunshot using a distributed sensor network measuring time differences of arrival between a firearm's muzzle blast and the shockwave induced by a supersonic bullet. This so-called MB-SW approach is desirable because time synchronization is not required between the sensors, however it suffers from increased computational complexity and requires knowledge of the bullet's velocity at all points along its trajectory. While the actual velocity profile of a particular gunshot is unknown, one may use a parameterized model for the velocity profile and simultaneously fit the model and localize the shooter. In this paper we study efficient solutions for the localization problem and identify deceleration models that trade off localization accuracy and computational complexity. We also develop a statistical analysis that includes bias due to mismatch between the true and actual deceleration models and covariance due to additive noise.

Sensor Network Architectures for Monitoring Underwater Pipelines

PubMed Central

Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

2011-01-01

This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring. PMID:22346669

Sensor network architectures for monitoring underwater pipelines.

PubMed

Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

2011-01-01

This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (radio frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring.

RF Emitter Tracking and Intent Assessment

DTIC Science & Technology

2013-03-21

telecommunications sector. In 2010 there were 6,000 location-based applications for the iPhone, 900 for the Android and 300 for the Blackberry [2]. An example...Location-Aware Apps Keeps Growing Rapidly - But Very Few are Cross-Platform,” February 2010. [Online]. Available: http: //readwrite.com/2010/02/05...number of location-aware apps keeps growing - but. 3. L. Wang and Q. Xu, “Gps-Free Localization Algorithm for Wireless Sensor Networks,” Sensors, vol. 10

A versatile and interoperable network sensors for water resources monitoring

NASA Astrophysics Data System (ADS)

Ortolani, Alberto; Brandini, Carlo; Costantini, Roberto; Costanza, Letizia; Innocenti, Lucia; Sabatini, Francesco; Gozzini, Bernardo

2010-05-01

Monitoring systems to assess water resources quantity and quality require extensive use of in-situ measurements, that have great limitations like difficulties to access and share data, and to customise and easy reconfigure sensors network to fulfil end-users needs during monitoring or crisis phases. In order to address such limitations Sensor Web Enablement technologies for sensors management have been developed and applied to different environmental context under the EU-funded OSIRIS project (Open architecture for Smart and Interoperable networks in Risk management based on In-situ Sensors, www.osiris-fp6.eu). The main objective of OSIRIS was to create a monitoring system to manage different environmental crisis situations, through an efficient data processing chain where in-situ sensors are connected via an intelligent and versatile network infrastructure (based on web technologies) that enables end-users to remotely access multi-domain sensors information. Among the project application, one was focused on underground fresh-water monitoring and management. With this aim a monitoring system to continuously and automatically check water quality and quantity has been designed and built in a pilot test, identified as a portion of the Amiata aquifer feeding the Santa Fiora springs (Grosseto, Italy). This aquifer present some characteristics that make it greatly vulnerable under some conditions. It is a volcanic aquifer with a fractured structure. The volcanic nature in Santa Fiora causes levels of arsenic concentrations that normally are very close to the threshold stated by law, but that sometimes overpass such threshold for reasons still not fully understood. The presence of fractures makes the infiltration rate very inhomogeneous from place to place and very high in correspondence of big fractures. In case of liquid-pollutant spills (typically hydrocarbons spills from tanker accidents or leakage from house tanks containing fuel for heating), these fractures can act as shortcuts to the heart of the aquifer, causing water contamination much faster than what inferable from average infiltration rates. A new system has been set up, upgrading a legacy sensor network with new sensors to address the monitoring and emergency phase management. Where necessary sensors have been modified in order to manage the whole sensor network through SWE services. The network manage sensors for water parameters (physical and chemical) and for atmospheric ones (for supporting the management of accidental crises). A main property of the developed architecture is that it can be easily reconfigured to pass from the monitoring to the alert phase, by changing sampling frequencies of interesting parameters, or deploying specific additional sensors on identified optimal positions (as in case of the hydrocarbon spill). A hydrogeological model, coupled through a hydrological interface to the atmospheric forcing, has been implemented for the area. Model products (accessed through the same web interface than sensors) give a fundamental added value to the upgraded sensors network (e.g. for data merging procedures). Together with the available measurements, it is shown how the model improves the knowledge of the local hydrogeological system, gives a fundamental support to eventually reconfigure the system (e.g. support on transportable sensors position). The network, basically conceived for real-time monitoring, allow to accumulate an unprecedent amount of information for the aquifer. The availability of such a large set of data (in terms of continuously measured water levels, fluxes, precipitation, concentrations, etc.) from the system, gives a unique opportunity for studying the influences of hydrogeological and geopedological parameters on arsenic and concentrations of other chemicals that are naturally present in water.

An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

PubMed Central

Wang, Xue; Wang, Sheng; Ma, Jun-Jie

2007-01-01

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

The spectral positioning algorithm of new spectrum vehicle based on convex programming in wireless sensor network

NASA Astrophysics Data System (ADS)

Zhang, Yongjun; Lu, Zhixin

2017-10-01

Spectrum resources are very precious, so it is increasingly important to locate interference signals rapidly. Convex programming algorithms in wireless sensor networks are often used as localization algorithms. But in view of the traditional convex programming algorithm is too much overlap of wireless sensor nodes that bring low positioning accuracy, the paper proposed a new algorithm. Which is mainly based on the traditional convex programming algorithm, the spectrum car sends unmanned aerial vehicles (uses) that can be used to record data periodically along different trajectories. According to the probability density distribution, the positioning area is segmented to further reduce the location area. Because the algorithm only increases the communication process of the power value of the unknown node and the sensor node, the advantages of the convex programming algorithm are basically preserved to realize the simple and real-time performance. The experimental results show that the improved algorithm has a better positioning accuracy than the original convex programming algorithm.

A Study on the Performance of Low Cost MEMS Sensors in Strong Motion Studies

NASA Astrophysics Data System (ADS)

Tanırcan, Gulum; Alçık, Hakan; Kaya, Yavuz; Beyen, Kemal

2017-04-01

Recent advances in sensors have helped the growth of local networks. In recent years, many Micro Electro Mechanical System (MEMS)-based accelerometers have been successfully used in seismology and earthquake engineering projects. This is basically due to the increased precision obtained in these downsized instruments. Moreover, they are cheaper alternatives to force-balance type accelerometers. In Turkey, though MEMS-based accelerometers have been used in various individual applications such as magnitude and location determination of earthquakes, structural health monitoring, earthquake early warning systems, MEMS-based strong motion networks are not currently available in other populated areas of the country. Motivation of this study comes from the fact that, if MEMS sensors are qualified to record strong motion parameters of large earthquakes, a dense network can be formed in an affordable price at highly populated areas. The goals of this study are 1) to test the performance of MEMS sensors, which are available in the inventory of the Institute through shake table tests, and 2) to setup a small scale network for observing online data transfer speed to a trusted in-house routine. In order to evaluate the suitability of sensors in strong motion related studies, MEMS sensors and a reference sensor are tested under excitations of sweeping waves as well as scaled earthquake recordings. Amplitude response and correlation coefficients versus frequencies are compared. As for earthquake recordings, comparisons are carried out in terms of strong motion(SM) parameters (PGA, PGV, AI, CAV) and elastic response of structures (Sa). Furthermore, this paper also focuses on sensitivity and selectivity for sensor performances in time-frequency domain to compare different sensing characteristics and analyzes the basic strong motion parameters that influence the design majors. Results show that the cheapest MEMS sensors under investigation are able to record the mid-frequency dominant SM parameters PGV and CAV with high correlation. PGA and AI, the high frequency components of the ground motion, are underestimated. Such a difference, on the other hand, does not manifest itself on intensity estimations. PGV and CAV values from the reference and MEMS sensors converge to the same seismic intensity level. Hence a strong motion network with MEMS sensors could be a modest option to produce PGV-based damage impact of an urban area under large magnitude earthquake threats in the immediate vicinity.

Moving multiple sinks through wireless sensor networks for lifetime maximization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrioli, Chiara; Carosi, Alessio; Basagni, Stefano

2008-01-01

Unattended sensor networks typically watch for some phenomena such as volcanic events, forest fires, pollution, or movements in animal populations. Sensors report to a collection point periodically or when they observe reportable events. When sensors are too far from the collection point to communicate directly, other sensors relay messages for them. If the collection point location is static, sensor nodes that are closer to the collection point relay far more messages than those on the periphery. Assuming all sensor nodes have roughly the same capabilities, those with high relay burden experience battery failure much faster than the rest of themore » network. However, since their death disconnects the live nodes from the collection point, the whole network is then dead. We consider the problem of moving a set of collectors (sinks) through a wireless sensor network to balance the energy used for relaying messages, maximizing the lifetime of the network. We show how to compute an upper bound on the lifetime for any instance using linear and integer programming. We present a centralized heuristic that produces sink movement schedules that produce network lifetimes within 1.4% of the upper bound for realistic settings. We also present a distributed heuristic that produces lifetimes at most 25:3% below the upper bound. More specifically, we formulate a linear program (LP) that is a relaxation of the scheduling problem. The variables are naturally continuous, but the LP relaxes some constraints. The LP has an exponential number of constraints, but we can satisfy them all by enforcing only a polynomial number using a separation algorithm. This separation algorithm is a p-median facility location problem, which we can solve efficiently in practice for huge instances using integer programming technology. This LP selects a set of good sensor configurations. Given the solution to the LP, we can find a feasible schedule by selecting a subset of these configurations, ordering them via a traveling salesman heuristic, and computing feasible transitions using matching algorithms. This algorithm assumes sinks can get a schedule from a central server or a leader sink. If the network owner prefers the sinks make independent decisions, they can use our distributed heuristic. In this heuristic, sinks maintain estimates of the energy distribution in the network and move greedily (with some coordination) based on local search. This application uses the new SUCASA (Solver Utility for Customization with Automatic Symbol Access) facility within the PICO (Parallel Integer and Combinatorial Optimizer) integer programming solver system. SUCASA allows rapid development of customized math programming (search-based) solvers using a problem's natural multidimensional representation. In this case, SUCASA also significantly improves runtime compared to implementations in the ampl math programming language or in perl.« less

Engineering Amorphous Systems, Using Global-to-Local Compilation

NASA Astrophysics Data System (ADS)

Nagpal, Radhika

Emerging technologies are making it possible to assemble systems that incorporate myriad of information-processing units at almost no cost: smart materials, selfassembling structures, vast sensor networks, pervasive computing. How does one engineer robust and prespecified global behavior from the local interactions of immense numbers of unreliable parts? We discuss organizing principles and programming methodologies that have emerged from Amorphous Computing research, that allow us to compile a specification of global behavior into a robust program for local behavior.

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach.

PubMed

Ke, Mingxing; Li, Ding; Tian, Shiwei; Zhang, Yuli; Tong, Kaixiang; Xu, Yuhua

2018-05-08

The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ -equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.

Performance Evaluation of a Prototyped Wireless Ground Sensor Network

DTIC Science & Technology

2005-03-01

the network was capable of dynamic adaptation to failure and degradation. 14. SUBJECT TERMS: Wireless Sensor Network , Unmanned Sensor, Unattended...2 H. WIRELESS SENSOR NETWORKS .................................................................... 3...zation, and network traffic. The evaluated scenarios included outdoor, urban and indoor environments. The characteristics of wireless sensor networks , types

Sensor Authentication in Collaborating Sensor Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bielefeldt, Jake Uriah

2014-11-01

In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator O i of Sensor Network S imore » to correctly determine the number of active sensors in Network Si. Such a problem is challenging in collaborating sensor networks where other sensor networks, despite showing an intent to collaborate, may not be completely trustworthy and could compromise the authentication process. We propose two authentication protocols to address this problem. Our protocols rely on Physically Unclonable Functions, which are a hardware based authentication primitive exploiting inherent randomness in circuit fabrication. Our protocols are light-weight, energy efficient, and highly secure against a number of attacks. To the best of our knowledge, ours is the first to addresses a practical security problem in collaborating sensor networks.« less

Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements

DOE PAGES

Li, Xinya; Deng, Zhiqun Daniel; Rauchenstein, Lynn T.; ...

2016-04-01

Locating the position of fixed or mobile sources (i.e., transmitters) based on received measurements from sensors is an important research area that is attracting much research interest. In this paper, we present localization algorithms using time of arrivals (TOA) and time difference of arrivals (TDOA) to achieve high accuracy under line-of-sight conditions. The circular (TOA) and hyperbolic (TDOA) location systems both use nonlinear equations that relate the locations of the sensors and tracked objects. These nonlinear equations can develop accuracy challenges because of the existence of measurement errors and efficiency challenges that lead to high computational burdens. Least squares-based andmore » maximum likelihood-based algorithms have become the most popular categories of location estimators. We also summarize the advantages and disadvantages of various positioning algorithms. By improving measurement techniques and localization algorithms, localization applications can be extended into the signal-processing-related domains of radar, sonar, the Global Positioning System, wireless sensor networks, underwater animal tracking, mobile communications, and multimedia.« less

Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xinya; Deng, Zhiqun Daniel; Rauchenstein, Lynn T.

Locating the position of fixed or mobile sources (i.e., transmitters) based on received measurements from sensors is an important research area that is attracting much research interest. In this paper, we present localization algorithms using time of arrivals (TOA) and time difference of arrivals (TDOA) to achieve high accuracy under line-of-sight conditions. The circular (TOA) and hyperbolic (TDOA) location systems both use nonlinear equations that relate the locations of the sensors and tracked objects. These nonlinear equations can develop accuracy challenges because of the existence of measurement errors and efficiency challenges that lead to high computational burdens. Least squares-based andmore » maximum likelihood-based algorithms have become the most popular categories of location estimators. We also summarize the advantages and disadvantages of various positioning algorithms. By improving measurement techniques and localization algorithms, localization applications can be extended into the signal-processing-related domains of radar, sonar, the Global Positioning System, wireless sensor networks, underwater animal tracking, mobile communications, and multimedia.« less

Emergency navigation without an infrastructure.

PubMed

Gelenbe, Erol; Bi, Huibo

2014-08-18

Emergency navigation systems for buildings and other built environments, such as sport arenas or shopping centres, typically rely on simple sensor networks to detect emergencies and, then, provide automatic signs to direct the evacuees. The major drawbacks of such static wireless sensor network (WSN)-based emergency navigation systems are the very limited computing capacity, which makes adaptivity very difficult, and the restricted battery power, due to the low cost of sensor nodes for unattended operation. If static wireless sensor networks and cloud-computing can be integrated, then intensive computations that are needed to determine optimal evacuation routes in the presence of time-varying hazards can be offloaded to the cloud, but the disadvantages of limited battery life-time at the client side, as well as the high likelihood of system malfunction during an emergency still remain. By making use of the powerful sensing ability of smart phones, which are increasingly ubiquitous, this paper presents a cloud-enabled indoor emergency navigation framework to direct evacuees in a coordinated fashion and to improve the reliability and resilience for both communication and localization. By combining social potential fields (SPF) and a cognitive packet network (CPN)-based algorithm, evacuees are guided to exits in dynamic loose clusters. Rather than relying on a conventional telecommunications infrastructure, we suggest an ad hoc cognitive packet network (AHCPN)-based protocol to adaptively search optimal communication routes between portable devices and the network egress nodes that provide access to cloud servers, in a manner that spares the remaining battery power of smart phones and minimizes the time latency. Experimental results through detailed simulations indicate that smart human motion and smart network management can increase the survival rate of evacuees and reduce the number of drained smart phones in an evacuation process.

Emergency Navigation without an Infrastructure

PubMed Central

Gelenbe, Erol; Bi, Huibo

2014-01-01

Emergency navigation systems for buildings and other built environments, such as sport arenas or shopping centres, typically rely on simple sensor networks to detect emergencies and, then, provide automatic signs to direct the evacuees. The major drawbacks of such static wireless sensor network (WSN)-based emergency navigation systems are the very limited computing capacity, which makes adaptivity very difficult, and the restricted battery power, due to the low cost of sensor nodes for unattended operation. If static wireless sensor networks and cloud-computing can be integrated, then intensive computations that are needed to determine optimal evacuation routes in the presence of time-varying hazards can be offloaded to the cloud, but the disadvantages of limited battery life-time at the client side, as well as the high likelihood of system malfunction during an emergency still remain. By making use of the powerful sensing ability of smart phones, which are increasingly ubiquitous, this paper presents a cloud-enabled indoor emergency navigation framework to direct evacuees in a coordinated fashion and to improve the reliability and resilience for both communication and localization. By combining social potential fields (SPF) and a cognitive packet network (CPN)-based algorithm, evacuees are guided to exits in dynamic loose clusters. Rather than relying on a conventional telecommunications infrastructure, we suggest an ad hoc cognitive packet network (AHCPN)-based protocol to adaptively search optimal communication routes between portable devices and the network egress nodes that provide access to cloud servers, in a manner that spares the remaining battery power of smart phones and minimizes the time latency. Experimental results through detailed simulations indicate that smart human motion and smart network management can increase the survival rate of evacuees and reduce the number of drained smart phones in an evacuation process. PMID:25196014

Wireless Sensor Network Handles Image Data

NASA Technical Reports Server (NTRS)

2008-01-01

To relay data from remote locations for NASA s Earth sciences research, Goddard Space Flight Center contributed to the development of "microservers" (wireless sensor network nodes), which are now used commercially as a quick and affordable means to capture and distribute geographical information, including rich sets of aerial and street-level imagery. NASA began this work out of a necessity for real-time recovery of remote sensor data. These microservers work much like a wireless office network, relaying information between devices. The key difference, however, is that instead of linking workstations within one office, the interconnected microservers operate miles away from one another. This attribute traces back to the technology s original use: The microservers were originally designed for seismology on remote glaciers and ice streams in Alaska, Greenland, and Antarctica-acquiring, storing, and relaying data wirelessly between ground sensors. The microservers boast three key attributes. First, a researcher in the field can establish a "managed network" of microservers and rapidly see the data streams (recovered wirelessly) on a field computer. This rapid feedback permits the researcher to reconfigure the network for different purposes over the course of a field campaign. Second, through careful power management, the microservers can dwell unsupervised in the field for up to 2 years, collecting tremendous amounts of data at a research location. The third attribute is the exciting potential to deploy a microserver network that works in synchrony with robotic explorers (e.g., providing ground truth validation for satellites, supporting rovers as they traverse the local environment). Managed networks of remote microservers that relay data unsupervised for up to 2 years can drastically reduce the costs of field instrumentation and data rec

An efficient management system for wireless sensor networks.

PubMed

Ma, Yi-Wei; Chen, Jiann-Liang; Huang, Yueh-Min; Lee, Mei-Yu

2010-01-01

Wireless sensor networks have garnered considerable attention recently. Networks typically have many sensor nodes, and are used in commercial, medical, scientific, and military applications for sensing and monitoring the physical world. Many researchers have attempted to improve wireless sensor network management efficiency. A Simple Network Management Protocol (SNMP)-based sensor network management system was developed that is a convenient and effective way for managers to monitor and control sensor network operations. This paper proposes a novel WSNManagement system that can show the connections stated of relationships among sensor nodes and can be used for monitoring, collecting, and analyzing information obtained by wireless sensor networks. The proposed network management system uses collected information for system configuration. The function of performance analysis facilitates convenient management of sensors. Experimental results show that the proposed method enhances the alive rate of an overall sensor node system, reduces the packet lost rate by roughly 5%, and reduces delay time by roughly 0.2 seconds. Performance analysis demonstrates that the proposed system is effective for wireless sensor network management.

Synchronous wearable wireless body sensor network composed of autonomous textile nodes.

PubMed

Vanveerdeghem, Peter; Van Torre, Patrick; Stevens, Christiaan; Knockaert, Jos; Rogier, Hendrik

2014-10-09

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system.

Synchronous Wearable Wireless Body Sensor Network Composed of Autonomous Textile Nodes

PubMed Central

Vanveerdeghem, Peter; Van Torre, Patrick; Stevens, Christiaan; Knockaert, Jos; Rogier, Hendrik

2014-01-01

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system. PMID:25302808

Imagining CO2: development and assessment of interactive visualizations for high resolution greenhouse gas observations collected by BEACO2N

NASA Astrophysics Data System (ADS)

Raheja, G.; Shusterman, A.; Martin, S.; Shahar, E.; Laughner, J.; Turner, A. J.; Miller, M. K.; Cohen, R. C.

2016-12-01

The Berkeley Atmospheric CO2 Observation Network (BEACO2N) is a high-density network of 28 carbon dioxide sensors distributed around the San Francisco Bay Area that serve to enhance understanding of intra-city variations in CO2 concentrations that are not necessarily captured by sparser networks maintained by local and national air quality management agencies. We partner with designers at the San Francisco Exploratorium to create a suite of interactive exhibits and hands-on activities that creatively visualize data from BEACO2N for general audiences. Museum goers can manipulate a light-up "bar graph" of live CO2 concentrations by exhaling on an in-room sensor, query the current readings of rooftop sensors using a scale model of the Wired Pier observation system, scroll through the data from other BEACO2N sites projected on a 3-D "topographic table" of the Bay Area, and view interpolated CO2 fields driven by research-grade weather models on a nine-screen LCD display. We present lessons learned from these initial installations, from layperson audience feedback to details of the Stochastic Time-Inverted Lagrangian Transport (STILT) model coupled to Weather Research and Forecasting (WRF) weather fields used to generate intuitive concentration maps. We propose that compelling visual demonstrations of elevated CO2 concentrations due to routine small-scale high-emission anthropogenic activities (e.g. rush hour) and/or special events (such as fireworks or factory fires) generate deeper engagement in local environmental issues and interest in undertaking personal actions that can become part of the broader climate solution. While global means and other large-scale aggregate climate metrics can lead to feelings of disconnect and subsequent ambivalence, via such exhibitions, distributed network instruments like BEACO2N can provide the local sensitivity needed to "personalize" greenhouse gas concentrations to a given individual or community and incite the drive toward understanding, education, and action.

A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

NASA Technical Reports Server (NTRS)

Bhaduri, Kanishka; Srivastava, Ashok N.

2009-01-01

This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining tasks in a distributed environment such as clustering, anomaly detection, target tracking to name a few. This technology is crucial for many emerging peer-to-peer applications for bioinformatics, astronomy, social networking, sensor networks and web mining. Centralizing all or some of the data for building global models is impractical in such peer-to-peer environments because of the large number of data sources, the asynchronous nature of the peer-to-peer networks, and dynamic nature of the data/network. The distributed algorithm we have developed in this paper is provably-correct i.e. it converges to the same result compared to a similar centralized algorithm and can automatically adapt to changes to the data and the network. We show that the communication overhead of the algorithm is very low due to its local nature. This monitoring algorithm is then used as a feedback loop to sample data from the network and rebuild the model when it is outdated. We present thorough experimental results to verify our theoretical claims.

A Cost-Effective Vehicle Localization Solution Using an Interacting Multiple Model−Unscented Kalman Filters (IMM-UKF) Algorithm and Grey Neural Network

PubMed Central

Xu, Qimin; Li, Xu; Chan, Ching-Yao

2017-01-01

In this paper, we propose a cost-effective localization solution for land vehicles, which can simultaneously adapt to the uncertain noise of inertial sensors and bridge Global Positioning System (GPS) outages. First, three Unscented Kalman filters (UKFs) with different noise covariances are introduced into the framework of Interacting Multiple Model (IMM) algorithm to form the proposed IMM-based UKF, termed as IMM-UKF. The IMM algorithm can provide a soft switching among the three UKFs and therefore adapt to different noise characteristics. Further, two IMM-UKFs are executed in parallel when GPS is available. One fuses the information of low-cost GPS, in-vehicle sensors, and micro electromechanical system (MEMS)-based reduced inertial sensor systems (RISS), while the other fuses only in-vehicle sensors and MEMS-RISS. The differences between the state vectors of the two IMM-UKFs are considered as training data of a Grey Neural Network (GNN) module, which is known for its high prediction accuracy with a limited amount of samples. The GNN module can predict and compensate position errors when GPS signals are blocked. To verify the feasibility and effectiveness of the proposed solution, road-test experiments with various driving scenarios were performed. The experimental results indicate that the proposed solution outperforms all the compared methods. PMID:28629165

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

NASA Astrophysics Data System (ADS)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.

A wireless sensor network for monitoring volcanic tremors

NASA Astrophysics Data System (ADS)

Lopes Pereira, R.; Trindade, J.; Gonçalves, F.; Suresh, L.; Barbosa, D.; Vazão, T.

2013-08-01

Monitoring of volcanic activity is important to learn about the properties of each volcano and provide early warning systems to the population. Monitoring equipment can be expensive and thus, the degree of monitoring varies from volcano to volcano and from country to country, with many volcanoes not being monitored at all. This paper describes the development of a Wireless Sensor Network (WSN) capable of collecting geophysical measurements on remote active volcanoes. Our main goals were to create a flexible, easy to deploy and maintain, adaptable, low-cost WSN for temporary or permanent monitoring of seismic tremor. The WSN enables the easy installation of a sensor array on an area of tens of thousand of m2, allowing the location of the magma movements causing the seismic tremor to be calculated. This WSN can be used by recording data locally for latter analysis or by continuously transmitting it in real time to a remote laboratory for real-time analyses.

A Reinforcement Sensor Embedded Vertical Handoff Controller for Vehicular Heterogeneous Wireless Networks

PubMed Central

Li, Limin; Xu, Yubin; Soong, Boon-Hee; Ma, Lin

2013-01-01

Vehicular communication platforms that provide real-time access to wireless networks have drawn more and more attention in recent years. IEEE 802.11p is the main radio access technology that supports communication for high mobility terminals, however, due to its limited coverage, IEEE 802.11p is usually deployed by coupling with cellular networks to achieve seamless mobility. In a heterogeneous cellular/802.11p network, vehicular communication is characterized by its short time span in association with a wireless local area network (WLAN). Moreover, for the media access control (MAC) scheme used for WLAN, the network throughput dramatically decreases with increasing user quantity. In response to these compelling problems, we propose a reinforcement sensor (RFS) embedded vertical handoff control strategy to support mobility management. The RFS has online learning capability and can provide optimal handoff decisions in an adaptive fashion without prior knowledge. The algorithm integrates considerations including vehicular mobility, traffic load, handoff latency, and network status. Simulation results verify that the proposed algorithm can adaptively adjust the handoff strategy, allowing users to stay connected to the best network. Furthermore, the algorithm can ensure that RSUs are adequate, thereby guaranteeing a high quality user experience. PMID:24193101

Hybrid architecture for building secure sensor networks

NASA Astrophysics Data System (ADS)

Owens, Ken R., Jr.; Watkins, Steve E.

2012-04-01

Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

Cooperative UAV-Based Communications Backbone for Sensor Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Sensor and Video Monitoring of Water Quality at Bristol Floating Harbour

NASA Astrophysics Data System (ADS)

Chen, Yiheng; Han, Dawei

2017-04-01

Water system is an essential component in a smart city for its sustainability and resilience. The harbourside is a focal area of​ ​Bristol with new buildings and features redeveloped in the last ten years, attracting numerous visitors by the diversity of attractions and beautiful views. There is a strong​ ​relationship between the satisfactory of the visitors and local people with the water quality in the Harbour. The freshness and beauty of the water body would please people as well as benefit the aquatic ecosystems. As we are entering a data-rich era, this pilot project aims to explore the concept of using​ ​ video cameras and smart sensors to collect and monitor water quality condition at the Bristol harbourside. The video cameras and smart sensors are connected to the Bristol Is Open network, an open programmable city platform. This will be the​ first​ attempt to collect water quality data in real time in the​ ​Bristol urban area with the wireless network. The videos and images of the water body collected by the cameras will be correlated with the in-situ water quality parameters for research​ ​purposes. The successful implementation of the sensors can attract more academic researchers and industrial partners to expand the sensor network to multiple locations​ ​around the city covering the other parts of the Harbour and River Avon, leading to a new generation of urban system infrastructure model.

A Direct Position-Determination Approach for Multiple Sources Based on Neural Network Computation.

PubMed

Chen, Xin; Wang, Ding; Yin, Jiexin; Wu, Ying

2018-06-13

The most widely used localization technology is the two-step method that localizes transmitters by measuring one or more specified positioning parameters. Direct position determination (DPD) is a promising technique that directly localizes transmitters from sensor outputs and can offer superior localization performance. However, existing DPD algorithms such as maximum likelihood (ML)-based and multiple signal classification (MUSIC)-based estimations are computationally expensive, making it difficult to satisfy real-time demands. To solve this problem, we propose the use of a modular neural network for multiple-source DPD. In this method, the area of interest is divided into multiple sub-areas. Multilayer perceptron (MLP) neural networks are employed to detect the presence of a source in a sub-area and filter sources in other sub-areas, and radial basis function (RBF) neural networks are utilized for position estimation. Simulation results show that a number of appropriately trained neural networks can be successfully used for DPD. The performance of the proposed MLP-MLP-RBF method is comparable to the performance of the conventional MUSIC-based DPD algorithm for various signal-to-noise ratios and signal power ratios. Furthermore, the MLP-MLP-RBF network is less computationally intensive than the classical DPD algorithm and is therefore an attractive choice for real-time applications.

Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

PubMed

Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

2017-11-01

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

Cognitive radio wireless sensor networks: applications, challenges and research trends.

PubMed

Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won

2013-08-22

A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized.

A Risk Based Approach to Limit the Effects of Covert Channels for Internet Sensor Data Aggregators for Sensor Privacy

NASA Astrophysics Data System (ADS)

Viecco, Camilo H.; Camp, L. Jean

Effective defense against Internet threats requires data on global real time network status. Internet sensor networks provide such real time network data. However, an organization that participates in a sensor network risks providing a covert channel to attackers if that organization’s sensor can be identified. While there is benefit for every party when any individual participates in such sensor deployments, there are perverse incentives against individual participation. As a result, Internet sensor networks currently provide limited data. Ensuring anonymity of individual sensors can decrease the risk of participating in a sensor network without limiting data provision.

Instrumental measurement of odour nuisance in city agglomeration using electronic nose

NASA Astrophysics Data System (ADS)

Szulczyński, Bartosz; Dymerski, Tomasz; Gębicki, Jacek; Namieśnik, Jacek

2018-01-01

The paper describes an operation principle of odour nuisance monitoring network in a city agglomeration. Moreover, it presents the results of investigation on ambient air quality with respect to odour obtained during six-month period. The investigation was carried out using a network comprised of six prototypes of electronic nose and Nasal Ranger field olfactometers employed as a reference method. The monitoring network consisted of two measurement stations localized in a vicinity of crude oil processing plant and four stations localized near the main emitters of volatile odorous compounds such as sewage treatment plant, municipal landfill, phosphatic fertilizer production plant. The electronic nose prototype was equipped with a set of six semiconductor sensors by FIGARO Co. and one PID-type sensor. The field olfactometers were utilized for determination of mean concentration of odorants and for calibration of the electronic nose prototypes in order to provide their proper operation. Mean monthly values of odour concentration depended on the site of measurement and on meteorological parameters. They were within 0 - 6.0 ou/m3 range. Performed investigations revealed the possibility of electronic nose instrument application as a tool for monitoring of odour nuisance.

Scalable sensor management for automated fusion and tactical reconnaissance

NASA Astrophysics Data System (ADS)

Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

2013-05-01

The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a Sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system. The SMS architecture will be described and results from several flight tests and simulations will be shown.

Robust Multi-Agent Sensor Network Systems

DTIC Science & Technology

2012-05-08

Localization on the Sphere, International Journal of Intelligent Defence Support System, Vol. 4, no. 4, 2011, pp. 328-350. Quality of Network... Quality of Service (QoS). The following standards are included in the IEEE 1609 standard family: IEEE P1609.0, IEEE P1609.1, IEEE P1609.2, IEEE P1609.3...protocols to support safety services in ITS,” in IEEE International Conference on Emerging Technologies and Factory Au- tomation (ETFA), 2008, pp. 1189

The Video Collaborative Localization of a Miner's Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines.

PubMed

You, Kaiming; Yang, Wei; Han, Ruisong

2015-09-29

Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner's lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner's lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner's lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner's lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels.

Mining induced seismic event on an inactive fault in view of local surface and in mine underground networksS

NASA Astrophysics Data System (ADS)

Rudzinski, Lukasz; Lizurek, Grzegorz; Plesiewicz, Beata

2014-05-01

On 19th March 2013 tremor shook the surface of Polkowice town were "Rudna" mine is located. This event of ML=4.2 was third most powerful seismic event recorded in Legnica Głogów Copper District (LGCD). Citizens of the area reported that felt tremors were bigger and last longer than any other ones felt in last couple years. The event was studied with use of two different networks: underground network of "Rudna" mine and surface local network run by IGF PAS (LUMINEOS network). The first one is composed of 32 vertical seismometers at mining level, except 5 sensors placed in elevator shafts, seismometers location depth varies from 300 down to 1000 meters below surface. The seismometers used in this network are vertical short period Willmore MkII and MkIII sensors, with the frequency band from 1Hz to 100Hz. At the beginning of 2013th the local surface network of the Institute of Geophysics Polish Academy of Sciences (IGF PAS) with acronym LUMINEOS was installed under agreement with KGHM SA and "Rudna" mine officials. This network at the moment of the March 19th 2013 event was composed of 4 short-period one-second triaxial seismometers LE-3D/1s manufactured by Lenartz Electronics. Analysis of spectral parameters of the records from in mine seismic system and surface LUMINEOS network along with broadband station KSP record were carried out. Location of the event was close to the Rudna Główna fault zone, the nodal planes orientations determined with two different approaches were almost parallel to the strike of the fault. The mechanism solutions were also obtained in form of Full Moment Tensor inversion from P wave amplitude pulses of underground records and waveform inversion of surface network seismograms. Final results of the seismic analysis along with macroseismic survey and observed effects from the destroyed part of the mining panel indicate that the mechanism of the event was thrust faulting on inactive tectonic fault. The results confirm that the fault zones are the areas of higher risk, even in case of carefully taken mining operations.

LPTA: Location Predictive and Time Adaptive Data Gathering Scheme with Mobile Sink for Wireless Sensor Networks

PubMed Central

Rodrigues, Joel J. P. C.

2014-01-01

This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes. PMID:25302327

Optimal Estimation of Glider’s Underwater Trajectory with Depth-Dependent Correction Using the Navy Coastal Ocean Model with Application to Antisubmarine Warfare

DTIC Science & Technology

2014-09-01

deployed simultaneously. For example, a fleet of gliders would be able to act as an intelligence network by gathering underwater target information ...and to verify our novel method, a glider’s real underwater trajectory information must be obtained by using additional sensors like ADCP or DVL (see...lacks of inexpensive and efficient localization sensors during its subsurface mission. Therefore, knowing its precise underwater position is a

Achieving Congestion Mitigation Using Distributed Power Control for Spectrum Sensor Nodes in Sensor Network-Aided Cognitive Radio Ad Hoc Networks

PubMed Central

Zhuo, Fan; Duan, Hucai

2017-01-01

The data sequence of spectrum sensing results injected from dedicated spectrum sensor nodes (SSNs) and the data traffic from upstream secondary users (SUs) lead to unpredictable data loads in a sensor network-aided cognitive radio ad hoc network (SN-CRN). As a result, network congestion may occur at a SU acting as fusion center when the offered data load exceeds its available capacity, which degrades network performance. In this paper, we present an effective approach to mitigate congestion of bottlenecked SUs via a proposed distributed power control framework for SSNs over a rectangular grid based SN-CRN, aiming to balance resource load and avoid excessive congestion. To achieve this goal, a distributed power control framework for SSNs from interior tier (IT) and middle tier (MT) is proposed to achieve the tradeoff between channel capacity and energy consumption. In particular, we firstly devise two pricing factors by considering stability of local spectrum sensing and spectrum sensing quality for SSNs. By the aid of pricing factors, the utility function of this power control problem is formulated by jointly taking into account the revenue of power reduction and the cost of energy consumption for IT or MT SSN. By bearing in mind the utility function maximization and linear differential equation constraint of energy consumption, we further formulate the power control problem as a differential game model under a cooperation or noncooperation scenario, and rigorously obtain the optimal solutions to this game model by employing dynamic programming. Then the congestion mitigation for bottlenecked SUs is derived by alleviating the buffer load over their internal buffers. Simulation results are presented to show the effectiveness of the proposed approach under the rectangular grid based SN-CRN scenario. PMID:28914803

Time Synchronization in Wireless Sensor Networks

DTIC Science & Technology

2003-01-01

University of California Los Angeles Time Synchronization in Wireless Sensor Networks A dissertation submitted in partial satisfaction of the...4. TITLE AND SUBTITLE Time Synchronization in Wireless Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...1 1.1 Wireless Sensor Networks . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Time Synchronization in Sensor Networks

Secure Cooperation of Autonomous Mobile Sensors Using an Underwater Acoustic Network

PubMed Central

Caiti, Andrea; Calabrò, Vincenzo; Dini, Gianluca; Duca, Angelica Lo; Munafò, Andrea

2012-01-01

Methodologies and algorithms are presented for the secure cooperation of a team of autonomous mobile underwater sensors, connected through an acoustic communication network, within surveillance and patrolling applications. In particular, the work proposes a cooperative algorithm in which the mobile underwater sensors (installed on Autonomous Underwater Vehicles—AUVs) respond to simple local rules based on the available information to perform the mission and maintain the communication link with the network (behavioral approach). The algorithm is intrinsically robust: with loss of communication among the vehicles the coverage performance (i.e., the mission goal) is degraded but not lost. The ensuing form of graceful degradation provides also a reactive measure against Denial of Service. The cooperative algorithm relies on the fact that the available information from the other sensors, though not necessarily complete, is trustworthy. To ensure trustworthiness, a security suite has been designed, specifically oriented to the underwater scenario, and in particular with the goal of reducing the communication overhead introduced by security in terms of number and size of messages. The paper gives implementation details on the integration between the security suite and the cooperative algorithm and provides statistics on the performance of the system as collected during the UAN project sea trial held in Trondheim, Norway, in May 2011. PMID:22438748

Secure cooperation of autonomous mobile sensors using an underwater acoustic network.

PubMed

Caiti, Andrea; Calabrò, Vincenzo; Dini, Gianluca; Lo Duca, Angelica; Munafò, Andrea

2012-01-01

Methodologies and algorithms are presented for the secure cooperation of a team of autonomous mobile underwater sensors, connected through an acoustic communication network, within surveillance and patrolling applications. In particular, the work proposes a cooperative algorithm in which the mobile underwater sensors (installed on Autonomous Underwater Vehicles-AUVs) respond to simple local rules based on the available information to perform the mission and maintain the communication link with the network (behavioral approach). The algorithm is intrinsically robust: with loss of communication among the vehicles the coverage performance (i.e., the mission goal) is degraded but not lost. The ensuing form of graceful degradation provides also a reactive measure against Denial of Service. The cooperative algorithm relies on the fact that the available information from the other sensors, though not necessarily complete, is trustworthy. To ensure trustworthiness, a security suite has been designed, specifically oriented to the underwater scenario, and in particular with the goal of reducing the communication overhead introduced by security in terms of number and size of messages. The paper gives implementation details on the integration between the security suite and the cooperative algorithm and provides statistics on the performance of the system as collected during the UAN project sea trial held in Trondheim, Norway, in May 2011.

Strain field reconstruction on composite spars based on the identification of equivalent load conditions

NASA Astrophysics Data System (ADS)

Airoldi, A.; Marelli, L.; Bettini, P.; Sala, G.; Apicella, A.

2017-04-01

Technologies based on optical fibers provide the possibility of installing relatively dense networks of sensors that can perform effective strain sensing functions during the operational life of structures. A contemporary trend is the increasing adoption of composite materials in aerospace constructions, which leads to structural architectures made of large monolithic elements. The paper is aimed at showing the feasibility of a detailed reconstruction of the strain field in a composite spar, which is based on the development of reference finite element models and the identification of load modes, consisting of a parameterized set of forces. The procedure is described and assessed in ideal conditions. Thereafter, a surrogate model is used to obtain realistic representation of the data acquired by the strain sensing system, so that the developed procedure is evaluated considering local effects due to the introduction of loads, significant modelling discrepancy in the development of the reference model and the presence of measurement noise. Results show that the method can obtain a robust and quite detailed reconstruction of strain fields, even at the level of local distributions, of the internal forces in the spars and of the displacements, by identifying an equivalent set of load parameters. Finally, the trade-off between the number of sensor and the accuracy, and the optimal position of the sensors for a given maximum number of sensors is evaluated by performing a multi-objective optimization, thus showing that even a relative dense network of externally applied sensors can be used to achieve good quality results.

Cyberinfrastructure for remote environmental observatories: a model homogeneous sensor network in the Great Basin, USA

NASA Astrophysics Data System (ADS)

Strachan, Scotty; Slater, David; Fritzinger, Eric; Lyles, Bradley; Kent, Graham; Smith, Kenneth; Dascalu, Sergiu; Harris, Frederick

2017-04-01

Sensor-based data collection has changed the potential scale and resolution of in-situ environmental studies by orders of magnitude, increasing expertise and management requirements accordingly. Cost-effective management of these observing systems is possible by leveraging cyberinfrastructure resources. Presented is a case study environmental observation network in the Great Basin region, USA, the Nevada Climate-ecohydrological Assessment Network (NevCAN). NevCAN stretches hundreds of kilometers across several mountain ranges and monitors climate and ecohydrological conditions from low desert (900 m ASL) to high subalpine treeline (3360 m ASL) down to 1-minute timescales. The network has been operating continuously since 2010, collecting billions of sensor data points and millions of camera images that record hourly conditions at each site, despite requiring relatively low annual maintenance expenditure. These data have provided unique insight into fine-scale processes across mountain gradients, which is crucial scientific information for a water-scarce region. The key to maintaining data continuity for these remotely-located study sites has been use of uniform data transport and management systems, coupled with high-reliability power system designs. Enabling non-proprietary digital communication paths to all study sites and sensors allows the research team to acquire data in near-real-time, troubleshoot problems, and diversify sensor hardware. A wide-area network design based on common Internet Protocols (IP) has been extended into each study site, providing production bandwidth of between 2 Mbps and 60 Mbps, depending on local conditions. The network architecture and site-level support systems (such as power generation) have been implemented with the core objectives of capacity, redundancy, and modularity. NevCAN demonstrates that by following simple but uniform "best practices", the next generation of regionally-specific environmental observatories can evolve to provide dramatically improved levels of scientific and hazard monitoring that span complex topographies and remote geography.

Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks

NASA Astrophysics Data System (ADS)

Avci, Onur; Abdeljaber, Osama; Kiranyaz, Serkan; Hussein, Mohammed; Inman, Daniel J.

2018-06-01

Being an alternative to conventional wired sensors, wireless sensor networks (WSNs) are extensively used in Structural Health Monitoring (SHM) applications. Most of the Structural Damage Detection (SDD) approaches available in the SHM literature are centralized as they require transferring data from all sensors within the network to a single processing unit to evaluate the structural condition. These methods are found predominantly feasible for wired SHM systems; however, transmission and synchronization of huge data sets in WSNs has been found to be arduous. As such, the application of centralized methods with WSNs has been a challenge for engineers. In this paper, the authors are presenting a novel application of 1D Convolutional Neural Networks (1D CNNs) on WSNs for SDD purposes. The SDD is successfully performed completely wireless and real-time under ambient conditions. As a result of this, a decentralized damage detection method suitable for wireless SHM systems is proposed. The proposed method is based on 1D CNNs and it involves training an individual 1D CNN for each wireless sensor in the network in a format where each CNN is assigned to process the locally-available data only, eliminating the need for data transmission and synchronization. The proposed damage detection method operates directly on the raw ambient vibration condition signals without any filtering or preprocessing. Moreover, the proposed approach requires minimal computational time and power since 1D CNNs merge both feature extraction and classification tasks into a single learning block. This ability is prevailingly cost-effective and evidently practical in WSNs considering the hardware systems have been occasionally reported to suffer from limited power supply in these networks. To display the capability and verify the success of the proposed method, large-scale experiments conducted on a laboratory structure equipped with a state-of-the-art WSN are reported.

Data-centric multiobjective QoS-aware routing protocol for body sensor networks.

PubMed

Razzaque, Md Abdur; Hong, Choong Seon; Lee, Sungwon

2011-01-01

In this paper, we address Quality-of-Service (QoS)-aware routing issue for Body Sensor Networks (BSNs) in delay and reliability domains. We propose a data-centric multiobjective QoS-Aware routing protocol, called DMQoS, which facilitates the system to achieve customized QoS services for each traffic category differentiated according to the generated data types. It uses modular design architecture wherein different units operate in coordination to provide multiple QoS services. Their operation exploits geographic locations and QoS performance of the neighbor nodes and implements a localized hop-by-hop routing. Moreover, the protocol ensures (almost) a homogeneous energy dissipation rate for all routing nodes in the network through a multiobjective Lexicographic Optimization-based geographic forwarding. We have performed extensive simulations of the proposed protocol, and the results show that DMQoS has significant performance improvements over several state-of-the-art approaches.

A proportional integral estimator-based clock synchronization protocol for wireless sensor networks.

PubMed

Yang, Wenlun; Fu, Minyue

2017-11-01

Clock synchronization is an issue of vital importance in applications of WSNs. This paper proposes a proportional integral estimator-based protocol (EBP) to achieve clock synchronization for wireless sensor networks. As each local clock skew gradually drifts, synchronization accuracy will decline over time. Compared with existing consensus-based approaches, the proposed synchronization protocol improves synchronization accuracy under time-varying clock skews. Moreover, by restricting synchronization error of clock skew into a relative small quantity, it could reduce periodic re-synchronization frequencies. At last, a pseudo-synchronous implementation for skew compensation is introduced as synchronous protocol is unrealistic in practice. Numerical simulations are shown to illustrate the performance of the proposed protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Airport Remote Tower Sensor Systems

NASA Technical Reports Server (NTRS)

Maluf, David A.; Gawdiak, Yuri; Leidichj, Christopher; Papasin, Richard; Tran, Peter B.; Bass, Kevin

2006-01-01

Networks of video cameras, meteorological sensors, and ancillary electronic equipment are under development in collaboration among NASA Ames Research Center, the Federal Aviation Administration (FAA), and the National Oceanic Atmospheric Administration (NOAA). These networks are to be established at and near airports to provide real-time information on local weather conditions that affect aircraft approaches and landings. The prototype network is an airport-approach-zone camera system (AAZCS), which has been deployed at San Francisco International Airport (SFO) and San Carlos Airport (SQL). The AAZCS includes remotely controlled color video cameras located on top of SFO and SQL air-traffic control towers. The cameras are controlled by the NOAA Center Weather Service Unit located at the Oakland Air Route Traffic Control Center and are accessible via a secure Web site. The AAZCS cameras can be zoomed and can be panned and tilted to cover a field of view 220 wide. The NOAA observer can see the sky condition as it is changing, thereby making possible a real-time evaluation of the conditions along the approach zones of SFO and SQL. The next-generation network, denoted a remote tower sensor system (RTSS), will soon be deployed at the Half Moon Bay Airport and a version of it will eventually be deployed at Los Angeles International Airport. In addition to remote control of video cameras via secure Web links, the RTSS offers realtime weather observations, remote sensing, portability, and a capability for deployment at remote and uninhabited sites. The RTSS can be used at airports that lack control towers, as well as at major airport hubs, to provide synthetic augmentation of vision for both local and remote operations under what would otherwise be conditions of low or even zero visibility.

Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System.

PubMed

Wu, Fan; Rüdiger, Christoph; Yuce, Mehmet Rasit

2017-02-01

Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting.

Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System

PubMed Central

Wu, Fan; Rüdiger, Christoph; Yuce, Mehmet Rasit

2017-01-01

Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more low-power sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting. PMID:28157148

Sensor Network Localization by Eigenvector Synchronization Over the Euclidean Group

PubMed Central

CUCURINGU, MIHAI; LIPMAN, YARON; SINGER, AMIT

2013-01-01

We present a new approach to localization of sensors from noisy measurements of a subset of their Euclidean distances. Our algorithm starts by finding, embedding, and aligning uniquely realizable subsets of neighboring sensors called patches. In the noise-free case, each patch agrees with its global positioning up to an unknown rigid motion of translation, rotation, and possibly reflection. The reflections and rotations are estimated using the recently developed eigenvector synchronization algorithm, while the translations are estimated by solving an overdetermined linear system. The algorithm is scalable as the number of nodes increases and can be implemented in a distributed fashion. Extensive numerical experiments show that it compares favorably to other existing algorithms in terms of robustness to noise, sparse connectivity, and running time. While our approach is applicable to higher dimensions, in the current article, we focus on the two-dimensional case. PMID:23946700

Citizen Science to Support Community-based Flood Early Warning and Resilience Building

NASA Astrophysics Data System (ADS)

Paul, J. D.; Buytaert, W.; Allen, S.; Ballesteros-Cánovas, J. A.; Bhusal, J.; Cieslik, K.; Clark, J.; Dewulf, A.; Dhital, M. R.; Hannah, D. M.; Liu, W.; Nayaval, J. L.; Schiller, A.; Smith, P. J.; Stoffel, M.; Supper, R.

2017-12-01

In Disaster Risk Management, an emerging shift has been noted from broad-scale, top-down assessments towards more participatory, community-based, bottom-up approaches. Combined with technologies for robust and low-cost sensor networks, a citizen science approach has recently emerged as a promising direction in the provision of extensive, real-time information for flood early warning systems. Here we present the framework and initial results of a major new international project, Landslide EVO, aimed at increasing local resilience against hydrologically induced disasters in western Nepal by exploiting participatory approaches to knowledge generation and risk governance. We identify three major technological developments that strongly support our approach to flood early warning and resilience building in Nepal. First, distributed sensor networks, participatory monitoring, and citizen science hold great promise in complementing official monitoring networks and remote sensing by generating site-specific information with local buy-in, especially in data-scarce regions. Secondly, the emergence of open source, cloud-based risk analysis platforms supports the construction of a modular, distributed, and potentially decentralised data processing workflow. Finally, linking data analysis platforms to social computer networks and ICT (e.g. mobile phones, tablets) allows tailored interfaces and people-centred decision- and policy-support systems to be built. Our proposition is that maximum impact is created if end-users are involved not only in data collection, but also over the entire project life-cycle, including the analysis and provision of results. In this context, citizen science complements more traditional knowledge generation practices, and also enhances multi-directional information provision, risk management, early-warning systems and local resilience building.

Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends

PubMed Central

Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won

2013-01-01

A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized. PMID:23974152

Pairwise graphical models for structural health monitoring with dense sensor arrays

NASA Astrophysics Data System (ADS)

Mohammadi Ghazi, Reza; Chen, Justin G.; Büyüköztürk, Oral

2017-09-01

Through advances in sensor technology and development of camera-based measurement techniques, it has become affordable to obtain high spatial resolution data from structures. Although measured datasets become more informative by increasing the number of sensors, the spatial dependencies between sensor data are increased at the same time. Therefore, appropriate data analysis techniques are needed to handle the inference problem in presence of these dependencies. In this paper, we propose a novel approach that uses graphical models (GM) for considering the spatial dependencies between sensor measurements in dense sensor networks or arrays to improve damage localization accuracy in structural health monitoring (SHM) application. Because there are always unobserved damaged states in this application, the available information is insufficient for learning the GMs. To overcome this challenge, we propose an approximated model that uses the mutual information between sensor measurements to learn the GMs. The study is backed by experimental validation of the method on two test structures. The first is a three-story two-bay steel model structure that is instrumented by MEMS accelerometers. The second experimental setup consists of a plate structure and a video camera to measure the displacement field of the plate. Our results show that considering the spatial dependencies by the proposed algorithm can significantly improve damage localization accuracy.

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Abas, Faizulsalihin bin; Takayama, Shigeru

2015-02-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence.

PubMed

Zhang, Ran; Peng, Zhen; Wu, Lifeng; Yao, Beibei; Guan, Yong

2017-03-09

Intelligent condition monitoring and fault diagnosis by analyzing the sensor data can assure the safety of machinery. Conventional fault diagnosis and classification methods usually implement pretreatments to decrease noise and extract some time domain or frequency domain features from raw time series sensor data. Then, some classifiers are utilized to make diagnosis. However, these conventional fault diagnosis approaches suffer from the expertise of feature selection and they do not consider the temporal coherence of time series data. This paper proposes a fault diagnosis model based on Deep Neural Networks (DNN). The model can directly recognize raw time series sensor data without feature selection and signal processing. It also takes advantage of the temporal coherence of the data. Firstly, raw time series training data collected by sensors are used to train the DNN until the cost function of DNN gets the minimal value; Secondly, test data are used to test the classification accuracy of the DNN on local time series data. Finally, fault diagnosis considering temporal coherence with former time series data is implemented. Experimental results show that the classification accuracy of bearing faults can get 100%. The proposed fault diagnosis approach is effective in recognizing the type of bearing faults.

Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence

PubMed Central

Zhang, Ran; Peng, Zhen; Wu, Lifeng; Yao, Beibei; Guan, Yong

2017-01-01

Intelligent condition monitoring and fault diagnosis by analyzing the sensor data can assure the safety of machinery. Conventional fault diagnosis and classification methods usually implement pretreatments to decrease noise and extract some time domain or frequency domain features from raw time series sensor data. Then, some classifiers are utilized to make diagnosis. However, these conventional fault diagnosis approaches suffer from the expertise of feature selection and they do not consider the temporal coherence of time series data. This paper proposes a fault diagnosis model based on Deep Neural Networks (DNN). The model can directly recognize raw time series sensor data without feature selection and signal processing. It also takes advantage of the temporal coherence of the data. Firstly, raw time series training data collected by sensors are used to train the DNN until the cost function of DNN gets the minimal value; Secondly, test data are used to test the classification accuracy of the DNN on local time series data. Finally, fault diagnosis considering temporal coherence with former time series data is implemented. Experimental results show that the classification accuracy of bearing faults can get 100%. The proposed fault diagnosis approach is effective in recognizing the type of bearing faults. PMID:28282936

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

An open-source wireless sensor stack: from Arduino to SDI-12 to Water One Flow

NASA Astrophysics Data System (ADS)

Hicks, S.; Damiano, S. G.; Smith, K. M.; Olexy, J.; Horsburgh, J. S.; Mayorga, E.; Aufdenkampe, A. K.

2013-12-01

Implementing a large-scale streaming environmental sensor network has previously been limited by the high cost of the datalogging and data communication infrastructure. The Christina River Basin Critical Zone Observatory (CRB-CZO) is overcoming the obstacles to large near-real-time data collection networks by using Arduino, an open source electronics platform, in combination with XBee ZigBee wireless radio modules. These extremely low-cost and easy-to-use open source electronics are at the heart of the new DIY movement and have provided solutions to countless projects by over half a million users worldwide. However, their use in environmental sensing is in its infancy. At present a primary limitation to widespread deployment of open-source electronics for environmental sensing is the lack of a simple, open-source software stack to manage streaming data from heterogeneous sensor networks. Here we present a functioning prototype software stack that receives sensor data over a self-meshing ZigBee wireless network from over a hundred sensors, stores the data locally and serves it on demand as a CUAHSI Water One Flow (WOF) web service. We highlight a few new, innovative components, including: (1) a versatile open data logger design based the Arduino electronics platform and ZigBee radios; (2) a software library implementing SDI-12 communication protocol between any Arduino platform and SDI12-enabled sensors without the need for additional hardware (https://github.com/StroudCenter/Arduino-SDI-12); and (3) 'midStream', a light-weight set of Python code that receives streaming sensor data, appends it with metadata on the fly by querying a relational database structured on an early version of the Observations Data Model version 2.0 (ODM2), and uses the WOFpy library to serve the data as WaterML via SOAP and REST web services.

Adaptive Environmental Source Localization and Tracking with Unknown Permittivity and Path Loss Coefficients †

PubMed Central

Fidan, Barış; Umay, Ilknur

2015-01-01

Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for the electromagnetic signal case. Thus, accurate estimation of these coefficients has significant importance for the accuracy of location estimates. In this paper, we propose a geometric cooperative technique to instantaneously estimate such coefficients, with details provided for received signal strength (RSS) and time-of-flight (TOF)-based range sensors. The proposed technique is integrated to a recursive least squares (RLS)-based adaptive localization scheme and an adaptive motion control law, to construct adaptive target localization and adaptive target tracking algorithms, respectively, that are robust to uncertainties in aforementioned environmental signal propagation coefficients. The efficiency of the proposed adaptive localization and tracking techniques are both mathematically analysed and verified via simulation experiments. PMID:26690441

Smart Rocks for Bridge Scour Monitoring: Design and Localization Using Electromagnetic Techniques and Embedded Orientation Sensors

NASA Astrophysics Data System (ADS)

Radchenko, Andro

River bridge scour is an erosion process in which flowing water removes sediment materials (such as sand, rocks) from a bridge foundation, river beds and banks. As a result, the level of the river bed near a bridge pier is lowering such that the bridge foundation stability can be compromised, and the bridge can collapse. The scour is a dynamic process, which can accelerate rapidly during a flood event. Thus, regular monitoring of the scour progress is necessary to be performed at most river bridges. Present techniques are usually expensive, require large man/hour efforts, and often lack the real-time monitoring capabilities. In this dissertation a new method--'Smart Rocks Network for bridge scour monitoring' is introduced. The method is based on distributed wireless sensors embedded in ground underwater nearby the bridge pillars. The sensor nodes are unconstrained in movement, are equipped with years-lasting batteries and intelligent custom designed electronics, which minimizes power consumption during operation and communication. The electronic part consists of a microcontroller, communication interfaces, orientation and environment sensors (such as are accelerometer, magnetometer, temperature and pressure sensors), supporting power supplies and circuitries. Embedded in the soil nearby a bridge pillar the Smart Rocks can move/drift together with the sediments, and act as the free agent probes transmitting the unique signature signals to the base-station monitors. Individual movement of a Smart Rock can be remotely detected processing the orientation sensors reading. This can give an indication of the on-going scour progress, and set a flag for the on-site inspection. The map of the deployed Smart Rocks Network can be obtained utilizing the custom developed in-network communication protocol with signals intensity (RSSI) analysis. Particle Swarm Optimization (PSO) is applied for map reconstruction. Analysis of the map can provide detailed insight into the scour progress and topology. Smart Rocks Network wireless communication is based on the magnetoinductive (MI) link, at low (125 KHz) frequency, allowing for signal to penetrate through the water, rocks, and the bridge structure. The dissertation describes the Smart Rocks Network implementation, its electronic design and the electromagnetic/computational intelligence techniques used for the network mapping.

An Integrative Structural Health Monitoring System for the Local/Global Responses of a Large-Scale Irregular Building under Construction

PubMed Central

Park, Hyo Seon; Shin, Yunah; Choi, Se Woon; Kim, Yousok

2013-01-01

In this study, a practical and integrative SHM system was developed and applied to a large-scale irregular building under construction, where many challenging issues exist. In the proposed sensor network, customized energy-efficient wireless sensing units (sensor nodes, repeater nodes, and master nodes) were employed and comprehensive communications from the sensor node to the remote monitoring server were conducted through wireless communications. The long-term (13-month) monitoring results recorded from a large number of sensors (75 vibrating wire strain gauges, 10 inclinometers, and three laser displacement sensors) indicated that the construction event exhibiting the largest influence on structural behavior was the removal of bents that were temporarily installed to support the free end of the cantilevered members during their construction. The safety of each member could be confirmed based on the quantitative evaluation of each response. Furthermore, it was also confirmed that the relation between these responses (i.e., deflection, strain, and inclination) can provide information about the global behavior of structures induced from specific events. Analysis of the measurement results demonstrates the proposed sensor network system is capable of automatic and real-time monitoring and can be applied and utilized for both the safety evaluation and precise implementation of buildings under construction. PMID:23860317

Understanding dynamic pattern and process across spatial scales in river systems using simultaneous deployments of in situ sensors

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Mulukutla, G.; Cook, C.; Carey, R. O.

2014-12-01

Biogeochemical conditions throughout aquatic landscapes are spatially varied and temporally dynamic due to interactions of upstream land use, climate, hydrologic responses, and internal aquatic processes. One of the key goals in aquatic ecosystem ecology is to parse the upstream influences of terrestrial and aquatic processes on local conditions, which becomes progressively more difficult as watershed size increases and as processes are altered by diverse human activities. Simultaneous deployments of high frequency, in situ aquatic sensors for multiple constituents (e.g. NO3-N, CDOM, turbidity, conductivity, D.O., water temperature, along with flow) offer a new approach for understanding patterns along the aquatic continuum. For this talk, we explore strategies for deployments within single watersheds to improve understanding of terrestrial and aquatic processes. We address applications regarding mobilization of non-point nutrient sources across temporal scales, interactions with land use and watershed size, and the importance of aquatic processes. We also explore ways in which simultaneous sensor deployments can be designed to improve parameterization and testing of river network biogeochemical models. We will provide several specific examples using conductivity, nitrate and carbon from ongoing sensor deployments in New England, USA. We expect that improved deployments of sensors and sensor networks will benefit the management of critical freshwater resources.

Measurement and visualization of face-to-face interaction among community-dwelling older adults using wearable sensors.

PubMed

Masumoto, Kouhei; Yaguchi, Takaharu; Matsuda, Hiroshi; Tani, Hideaki; Tozuka, Keisuke; Kondo, Narihiko; Okada, Shuichi

2017-10-01

A number of interventions have been undertaken to develop and promote social networks among community-dwelling older adults. However, it has been difficult to examine the effects of these interventions, because of problems in assessing interactions. The present study was designed to quantitatively measure and visualize face-to-face interactions among elderly participants in an exercise program. We also examined relationships among interactional variables, personality and interest in community involvement, including interactions with the local community. Older adults living in the same community were recruited to participate in an exercise program that consisted of four sessions. We collected data on face-to-face interactions of the participants by using a wearable sensor technology device. Network analysis identified the communication networks of participants in the exercise program, as well as changes in these networks. Additionally, there were significant correlations between the number of people involved in face-to-face interactions and changes in both interest in community involvement and interactions with local community residents, as well as personality traits, including agreeableness. Social networks in the community are essential for solving problems caused by the aging society. We showed the possible applications of face-to-face interactional data for identifying core participants having many interactions, and isolated participants having only a few interactions within the community. Such data would be useful for carrying out efficient interventions for increasing participants' involvement with their community. Geriatr Gerontol Int 2017; 17: 1752-1758. © 2017 Japan Geriatrics Society.

iSANLA: intelligent sensor and actuator network for life science applications.

PubMed

Schloesser, Mario; Schnitzer, Andreas; Ying, Hong; Silex, Carmen; Schiek, Michael

2008-01-01

In the fields of neurological rehabilitation and neurophysiological research there is a strong need for miniaturized, multi channel, battery driven, wireless networking DAQ systems enabling real-time digital signal processing and feedback experiments. For the scientific investigation on the passive auditory based 3D-orientation of Barn Owls and the scientific research on vegetative locomotor coordination of Parkinson's disease patients during rehabilitation we developed our 'intelligent Sensor and Actuator Network for Life science Application' (iSANLA) system. Implemented on the ultra low power microcontroller MSP430 sample rates up to 96 kHz have been realised for single channel DAQ. The system includes lossless local data storage up to 4 GB. With its outer dimensions of 20mm per rim and less than 15 g of weight including the Lithium-Ion battery our modular designed sensor node is thoroughly capable of up to eight channel recordings with 8 kHz sample rate each and provides sufficient computational power for digital signal processing ready to start our first mobile experiments. For wireless mobility a compact communication protocol based on the IEEE 802.15.4 wireless standard with net data rates up to 141 kbit/s has been implemented. To merge the lossless acquired data of the distributed iNODEs a time synchronization protocol has been developed preserving causality. Hence the necessary time synchronous start of the data acquisition inside a network of multiple sensors with a precision better than the highest sample rate has been realized.

Breaking wire detection and strain distribution of seven-wire steel cables with acoustic emission and optical fiber sensors.

DOT National Transportation Integrated Search

2013-09-01

Cable-stayed bridges have been increasingly used as river-crossing links in highway and railway transportation networks. In the event : of an abnormal situation, they can not only impact the local and national economy but also threaten the safety of ...

Acoustic Sensor Network for Relative Positioning of Nodes

PubMed Central

De Marziani, Carlos; Ureña, Jesus; Hernandez, Álvaro; Mazo, Manuel; García, Juan Jesús; Jimenez, Ana; Rubio, María del Carmen Pérez; Álvarez, Fernando; Villadangos, José Manuel

2009-01-01

In this work, an acoustic sensor network for a relative localization system is analyzed by reporting the accuracy achieved in the position estimation. The proposed system has been designed for those applications where objects are not restricted to a particular environment and thus one cannot depend on any external infrastructure to compute their positions. The objects are capable of computing spatial relations among themselves using only acoustic emissions as a ranging mechanism. The object positions are computed by a multidimensional scaling (MDS) technique and, afterwards, a least-square algorithm, based on the Levenberg-Marquardt algorithm (LMA), is applied to refine results. Regarding the position estimation, all the parameters involved in the computation of the temporary relations with the proposed ranging mechanism have been considered. The obtained results show that a fine-grained localization can be achieved considering a Gaussian distribution error in the proposed ranging mechanism. Furthermore, since acoustic sensors require a line-of-sight to properly work, the system has been tested by modeling the lost of this line-of-sight as a non-Gaussian error. A suitable position estimation has been achieved even if it is considered a bias of up to 25 of the line-of-sight measurements among a set of nodes. PMID:22291520

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray

2011-01-01

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Dependable Wireless Sensor Networks for Prognostics and Health Management: A Survey

DTIC Science & Technology

2014-10-02

sensor network has many advantages. First of all, the absence of wires gives sensor networks the ability to cover a large scale surveillance area...system/component health state. Usually, this information is gathered through independent sensors or a wired network of sensors. The use of a wireless

Data Summarization in the Node by Parameters (DSNP): Local Data Fusion in an IoT Environment.

PubMed

Maschi, Luis F C; Pinto, Alex S R; Meneguette, Rodolfo I; Baldassin, Alexandro

2018-03-07

With the advent of the Internet of Things, billions of objects or devices are inserted into the global computer network, generating and processing data at a volume never imagined before. This paper proposes a way to collect and process local data through a data fusion technology called summarization. The main feature of the proposal is the local data fusion, through parameters provided by the application, ensuring the quality of data collected by the sensor node. In the evaluation, the sensor node was compared when performing the data summary with another that performed a continuous recording of the collected data. Two sets of nodes were created, one with a sensor node that analyzed the luminosity of the room, which in this case obtained a reduction of 97% in the volume of data generated, and another set that analyzed the temperature of the room, obtaining a reduction of 80% in the data volume. Through these tests, it has been proven that the local data fusion at the node can be used to reduce the volume of data generated, consequently decreasing the volume of messages generated by IoT environments.

Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Bakar, Kamalrulnizam Abu; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks. PMID:22368490

Multipath routing in wireless sensor networks: survey and research challenges.

PubMed

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks.

A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

USGS Publications Warehouse

David, Hamilton P; Carey, Cayelan C.; Arvola, Lauri; Arzberger, Peter; Brewer, Carol A.; Cole, Jon J; Gaiser, Evelyn; Hanson, Paul C.; Ibelings, Bas W; Jennings, Eleanor; Kratz, Tim K; Lin, Fang-Pang; McBride, Christopher G.; de Motta Marques, David; Muraoka, Kohji; Nishri, Ami; Qin, Boqiang; Read, Jordan S.; Rose, Kevin C.; Ryder, Elizabeth; Weathers, Kathleen C.; Zhu, Guangwei; Trolle, Dennis; Brookes, Justin D

2014-01-01

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process- based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process

PubMed Central

Parra, Lorena; García, Laura

2018-01-01

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €. PMID:29494560

Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process.

PubMed

Parra, Lorena; Sendra, Sandra; García, Laura; Lloret, Jaime

2018-03-01

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €.

Design and first tests of a Macroseismic Sensor System

NASA Astrophysics Data System (ADS)

Brueckl, Ewald; Polydor, Stefan; Ableitinger, Klaus; Rafeiner-Magor, Walter; Kristufek, Werner; Mertl, Stefan; Lenhardt, Wolfgang

2017-04-01

Seismic observatories are located in remote, low-noise areas for good reason and do not probe areas of dense and sensitive infrastructure. Complementary macroseismic data provide dense, qualitative information on ground motion in populated areas. Motivated by the QCN (Quake Catcher Network), a new low-cost sensor system (Macroseismic Sensor System = MSS) has been developed to support the evaluation of macroseismic data with quantitative information on ground movement in populated and industrial areas. Scholars, alumni and teachers from a technical high school contributed substantially to this development within the Sparkling Science project Schools & Quakes and the Citizen Science project QuakeWatch Austria. The MSS uses horizontal 4.5 Hz geophones and 16Bit AD conversion, and 100 Hz sampling, formatting to MiniSeed, and continuous data transmission via LAN or WLAN to a server are controlled by an integrated microcomputer (Raspberry Pi). Real-time generation of shake and source maps (based on proxies of the PGV in successive time windows) allows for differentiation between local seismic events (e.g., traffic noise, shock close to the sensor) and signals from earthquakes or quarry blasts. The inherent noise of the MSS is about 1% of the PGV corresponding to the lower boundary of intensity I = 2, which is below the ambient noise level at stations in highly populated or industrial areas. The MSS is already being tested at locations around a quarry with regular production blasts. An expansion to a local network in the Vienna Basin will be the next step.

A multidisciplinary monitoring network at Mayon volcano, Philippines: A collaborative effort between PHIVOLCS and EOS

NASA Astrophysics Data System (ADS)

Schwandner, F. M.; Hidayat, D.; Laguerta, E. P.; Baloloy, A. V.; Valerio, R.; Vaquilar, R.; Arpa, M. C.; Marcial, S. S.; Novianti, M. L.

2012-04-01

Mount Mayon in Albay province (Philippines) is an openly-degassing basaltic-andesitic stratovolcano, located on the northern edge of the northwest-trending OAS graben. Its latest eruptions were in Aug-Sept 2006 and Dec 2009. Mayon's current status is PHIVOLCS' level 1 with low seismicity dominated mostly local and regional tectonic earthquakes and continuous emission of SO2 from its summit crater. A research collaboration between the Earth Observatory of Singapore-NTU and the Philippine Institute of Volcanology and Seismology (PHIVOLCS) was initiated in 2009, aimed at developing a multi-disciplinary monitoring network around Mayon. The network design comprises a network of co-located geophysical, geochemical, hydrological and meteorological sensors, in both radial and circular arrangements. Radially arranged stations are intended to capture and distinguish vertical conduit processes, while the circular station design (including existing PHIVOLCS stations in cooperation with JICA, Japan) is meant to distinguish locations and sector activity of subsurface events. Geophysical instrumentation from EOS currently includes 4 broadband seismographs (in addition to 3 existing broadbands and 3 short period instruments from PHIVOLCS & JICA), and 5 tiltmeters. Four continuous cGPS stations will be installed in 2012, complementing 5 existing PHIVOLCS stations. Stations are also designed to house a multi-sensor package of static subsurface soil CO2 monitoring stations, the first of which was installed in early 2012, and which include subsoil sensors for heat flux, temperature, and moisture, as well as meteorological stations (with sonic anemometers and contact rain gages). These latter sensors are all controlled from one control box per station. Meteorological stations will help us to validate tilt, gas permeability, and also know lahar initiation potential. Since early 2011, separate stations downwind of the two prevailing wind directions from the summit continuously monitor the SO2 plume during daylight (the first Asian NOVAC dual-channel mini-DOAS). One unused agricultural well and one boxed spring were equipped with multi-sensor probes, installed in spring and summer 2011, to detect bulk volumetric strain and changes in chemical composition in high-gain and low-gain mode. All stations are autonomous in terms of their power source (solar), and are designed to withstand typhoons, break-in attempts and direct/indirect lightning strikes. To telemeter the data from these instruments to the local PHIVOLCS observatory at Lignon Hill (Legazpi), we use spread-spectrum radios with our own repeater stations, GSM/GPRS radio modems, and 3G broadband Internet. High rate data including seismic and NOVAC SO2 data are transmitted via spread-spectrum radio, whereas tilt, ground CO2, meteorology, hydrology and soil parameters are transmitted via 3G and SMS. We designed a low-cost datalogger system, which has been operating since Jan 2011, performing continuous data acquisition with sampling rate of 20 minute/sample and transmitted through GSM network, for tilt data. The receiving station is the PHIVOLCS Lignon Hill Observatory (LHO), where an off-grid power system has been installed to ensure continuous operation of the monitoring computers and radios. Local pre-processing by observatory staff and local archiving ensures close to immediate availability of data products in times of crisis. The data are also forwarded via TCP/IP to servers at PHIVOLCS headquarters and at EOS. Network infrastructure and data flows will be completed in 2012.

Wireless Sensor Networks for Detection of IED Emplacement

DTIC Science & Technology

2009-06-01

unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Abstract We are investigating the use of wireless nonimaging -sensor...networks for the difficult problem of detection of suspicious behavior related to IED emplacement. Hardware for surveillance by nonimaging -sensor networks...with people crossing a live sensor network. We conclude that nonimaging -sensor networks can detect a variety of suspicious behavior, but

Design architecture for multi-zone HVAC control systems from existing single-zone systems using wireless sensor networks

NASA Astrophysics Data System (ADS)

Redfern, Andrew; Koplow, Michael; Wright, Paul

2007-01-01

Most residential heating, ventilating, and air-conditioning (HVAC) systems utilize a single zone for conditioning air throughout the entire house. While inexpensive, these systems lead to wide temperature distributions and inefficient cooling due to the difference in thermal loads in different rooms. The end result is additional cost to the end user because the house is over conditioned. To reduce the total amount of energy used in a home and to increase occupant comfort there is a need for a better control system using multiple temperature zones. Typical multi-zone systems are costly and require extensive infrastructure to function. Recent advances in wireless sensor networks (WSNs) have enabled a low cost drop-in wireless vent register control system. The register control system is controlled by a master controller unit, which collects sensor data from a distributed wireless sensor network. Each sensor node samples local settings (occupancy, light, humidity and temperature) and reports the data back to the master control unit. The master control unit compiles the incoming data and then actuates the vent resisters to control the airflow throughout the house. The control system also utilizes a smart thermostat with a movable set point to enable the user to define their given comfort levels. The new system can reduce the run time of the HVAC system and thus decreasing the amount of energy used and increasing the comfort of the home occupations.

An agronomic field-scale sensor network for monitoring soil water and temperature variation

NASA Astrophysics Data System (ADS)

Brown, D. J.; Gasch, C.; Brooks, E. S.; Huggins, D. R.; Campbell, C. S.; Cobos, D. R.

2014-12-01

Environmental sensor networks have been deployed in a variety of contexts to monitor plant, air, water and soil properties. To date, there have been relatively few such networks deployed to monitor dynamic soil properties in cropped fields. Here we report on experience with a distributed soil sensor network that has been deployed for seven years in a research farm with ongoing agronomic field operations. The Washington State University R. J. Cook Agronomy Farm (CAF), Pullman, WA, USA has recently been designated a United States Department of Agriculture (USDA) Long-Term Agro-Ecosystem Research (LTAR) site. In 2007, 12 geo-referenced locations at CAF were instrumented, then in 2009 this network was expended to 42 locations distributed across the 37-ha farm. At each of this locations, Decagon 5TE probes (Decagon Devices Inc., Pullman, WA, USA) were installed at five depths (30, 60, 90, 120, and 150 cm), with temperature and volumetric soil moisture content recorded hourly. Initially, data loggers were wirelessly connected to a data station that could be accessed through a cell connection, but due to the logistics of agronomic field operations, we later buried the dataloggers at each site and now periodically download data via local radio transmission. In this presentation, we share our experience with the installation, maintenance, calibration and data processing associated with an agronomic soil monitoring network. We also present highlights of data derived from this network, including seasonal fluctuations of soil temperature and volumetric water content at each depth, and how these measurements are influenced by crop type, soil properties, landscape position, and precipitation events.

A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks.

PubMed

Zhang, Qingguo; Fok, Mable P

2017-01-09

Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate's target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate's target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage-distance rate and the number of moved mobile sensors, when compare with other approaches.

A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks

PubMed Central

Zhang, Qingguo; Fok, Mable P.

2017-01-01

Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate’s target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate’s target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage–distance rate and the number of moved mobile sensors, when compare with other approaches. PMID:28075365

Key Exchange Trust Evaluation in Peer-to-Peer Sensor Networks With Unconditionally Secure Key Exchange

NASA Astrophysics Data System (ADS)

Gonzalez, Elias; Kish, Laszlo B.

2016-03-01

As the utilization of sensor networks continue to increase, the importance of security becomes more profound. Many industries depend on sensor networks for critical tasks, and a malicious entity can potentially cause catastrophic damage. We propose a new key exchange trust evaluation for peer-to-peer sensor networks, where part of the network has unconditionally secure key exchange. For a given sensor, the higher the portion of channels with unconditionally secure key exchange the higher the trust value. We give a brief introduction to unconditionally secured key exchange concepts and mention current trust measures in sensor networks. We demonstrate the new key exchange trust measure on a hypothetical sensor network using both wired and wireless communication channels.

Memetic Algorithm-Based Multi-Objective Coverage Optimization for Wireless Sensor Networks

PubMed Central

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-01-01

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms. PMID:25360579

Memetic algorithm-based multi-objective coverage optimization for wireless sensor networks.

PubMed

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-10-30

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms.

A wireless sensor network based personnel positioning scheme in coal mines with blind areas.

PubMed

Liu, Zhigao; Li, Chunwen; Wu, Danchen; Dai, Wenhan; Geng, Shaobo; Ding, Qingqing

2010-01-01

This paper proposes a novel personnel positioning scheme for a tunnel network with blind areas, which compared with most existing schemes offers both low-cost and high-precision. Based on the data models of tunnel networks, measurement networks and mobile miners, the global positioning method is divided into four steps: (1) calculate the real time personnel location in local areas using a location engine, and send it to the upper computer through the gateway; (2) correct any localization errors resulting from the underground tunnel environmental interference; (3) determine the global three-dimensional position by coordinate transformation; (4) estimate the personnel locations in the blind areas. A prototype system constructed to verify the positioning performance shows that the proposed positioning system has good reliability, scalability, and positioning performance. In particular, the static localization error of the positioning system is less than 2.4 m in the underground tunnel environment and the moving estimation error is below 4.5 m in the corridor environment. The system was operated continuously over three months without any failures.

A Wireless Sensor Network Based Personnel Positioning Scheme in Coal Mines with Blind Areas

PubMed Central

Liu, Zhigao; Li, Chunwen; Wu, Danchen; Dai, Wenhan; Geng, Shaobo; Ding, Qingqing

2010-01-01

This paper proposes a novel personnel positioning scheme for a tunnel network with blind areas, which compared with most existing schemes offers both low-cost and high-precision. Based on the data models of tunnel networks, measurement networks and mobile miners, the global positioning method is divided into four steps: (1) calculate the real time personnel location in local areas using a location engine, and send it to the upper computer through the gateway; (2) correct any localization errors resulting from the underground tunnel environmental interference; (3) determine the global three-dimensional position by coordinate transformation; (4) estimate the personnel locations in the blind areas. A prototype system constructed to verify the positioning performance shows that the proposed positioning system has good reliability, scalability, and positioning performance. In particular, the static localization error of the positioning system is less than 2.4 m in the underground tunnel environment and the moving estimation error is below 4.5 m in the corridor environment. The system was operated continuously over three months without any failures. PMID:22163446

Availability Issues in Wireless Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Silva, Ivanovitch; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

2014-01-01

Wireless visual sensor networks have been considered for a large set of monitoring applications related with surveillance, tracking and multipurpose visual monitoring. When sensors are deployed over a monitored field, permanent faults may happen during the network lifetime, reducing the monitoring quality or rendering parts or the entire network unavailable. In a different way from scalar sensor networks, camera-enabled sensors collect information following a directional sensing model, which changes the notions of vicinity and redundancy. Moreover, visual source nodes may have different relevancies for the applications, according to the monitoring requirements and cameras' poses. In this paper we discuss the most relevant availability issues related to wireless visual sensor networks, addressing availability evaluation and enhancement. Such discussions are valuable when designing, deploying and managing wireless visual sensor networks, bringing significant contributions to these networks. PMID:24526301

A comparative study of wireless sensor networks and their routing protocols.

PubMed

Bhattacharyya, Debnath; Kim, Tai-hoon; Pal, Subhajit

2010-01-01

Recent developments in the area of micro-sensor devices have accelerated advances in the sensor networks field leading to many new protocols specifically designed for wireless sensor networks (WSNs). Wireless sensor networks with hundreds to thousands of sensor nodes can gather information from an unattended location and transmit the gathered data to a particular user, depending on the application. These sensor nodes have some constraints due to their limited energy, storage capacity and computing power. Data are routed from one node to other using different routing protocols. There are a number of routing protocols for wireless sensor networks. In this review article, we discuss the architecture of wireless sensor networks. Further, we categorize the routing protocols according to some key factors and summarize their mode of operation. Finally, we provide a comparative study on these various protocols.

A Sensor Driven Probabilistic Method for Enabling Hyper Resolution Flood Simulations

NASA Astrophysics Data System (ADS)

Fries, K. J.; Salas, F.; Kerkez, B.

2016-12-01

A reduction in the cost of sensors and wireless communications is now enabling researchers and local governments to make flow, stage and rain measurements at locations that are not covered by existing USGS or state networks. We ask the question: how should these new sources of densified, street-level sensor measurements be used to make improved forecasts using the National Water Model (NWM)? Assimilating these data "into" the NWM can be challenging due to computational complexity, as well as heterogeneity of sensor and other input data. Instead, we introduce a machine learning and statistical framework that layers these data "on top" of the NWM outputs to improve high-resolution hydrologic and hydraulic forecasting. By generalizing our approach into a post-processing framework, a rapidly repeatable blueprint is generated for for decision makers who want to improve local forecasts by coupling sensor data with the NWM. We present preliminary results based on case studies in highly instrumented watersheds in the US. Through the use of statistical learning tools and hydrologic routing schemes, we demonstrate the ability of our approach to improve forecasts while simultaneously characterizing bias and uncertainty in the NWM.

Development and Implementation of Low-Cost Mobile Sensor Platforms Within a Wireless Sensor Network

DTIC Science & Technology

2010-09-01

WIRELESS SENSOR NETWORK by Michael Jay Tozzi September 2010 Thesis Advisor: Rachel Goshorn Second Reader: Duane Davis Approved for...Platforms Within a Wireless Sensor Network 6. AUTHOR(S) Tozzi, Michael Jay 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...IMPLEMENTATION OF LOW-COST MOBILE SENSOR PLATFORMS WITHIN A WIRELESS SENSOR NETWORK Michael Jay Tozzi Lieutenant, United States Navy B.S., United

Joint Prior Learning for Visual Sensor Network Noisy Image Super-Resolution

PubMed Central

Yue, Bo; Wang, Shuang; Liang, Xuefeng; Jiao, Licheng; Xu, Caijin

2016-01-01

The visual sensor network (VSN), a new type of wireless sensor network composed of low-cost wireless camera nodes, is being applied for numerous complex visual analyses in wild environments, such as visual surveillance, object recognition, etc. However, the captured images/videos are often low resolution with noise. Such visual data cannot be directly delivered to the advanced visual analysis. In this paper, we propose a joint-prior image super-resolution (JPISR) method using expectation maximization (EM) algorithm to improve VSN image quality. Unlike conventional methods that only focus on upscaling images, JPISR alternatively solves upscaling mapping and denoising in the E-step and M-step. To meet the requirement of the M-step, we introduce a novel non-local group-sparsity image filtering method to learn the explicit prior and induce the geometric duality between images to learn the implicit prior. The EM algorithm inherently combines the explicit prior and implicit prior by joint learning. Moreover, JPISR does not rely on large external datasets for training, which is much more practical in a VSN. Extensive experiments show that JPISR outperforms five state-of-the-art methods in terms of both PSNR, SSIM and visual perception. PMID:26927114

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

PubMed

Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

Cellular telephone-based radiation detection instrument

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2011-06-14

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Calibration of an electronic nose for poultry farm

NASA Astrophysics Data System (ADS)

Abdullah, A. H.; Shukor, S. A.; Kamis, M. S.; Shakaff, A. Y. M.; Zakaria, A.; Rahim, N. A.; Mamduh, S. M.; Kamarudin, K.; Saad, F. S. A.; Masnan, M. J.; Mustafa, H.

2017-03-01

Malodour from the poultry farms could cause air pollution and therefore potentially dangerous to humans' and animals' health. This issue also poses sustainability risk to the poultry industries due to objections from local community. The aim of this paper is to develop and calibrate a cost effective and efficient electronic nose for poultry farm air monitoring. The instrument main components include sensor chamber, array of specific sensors, microcontroller, signal conditioning circuits and wireless sensor networks. The instrument was calibrated to allow classification of different concentrations of main volatile compounds in the poultry farm malodour. The outcome of the process will also confirm the device's reliability prior to being used for poultry farm malodour assessment. The Multivariate Analysis (HCA and KNN) and Artificial Neural Network (ANN) pattern recognition technique was used to process the acquired data. The results show that the instrument is able to calibrate the samples using ANN classification model with high accuracy. The finding verifies the instrument's performance to be used as an effective poultry farm malodour monitoring.

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors.

PubMed

Jenkins, R Brian; Joyce, Peter; Mechtel, Deborah

2017-01-27

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay.

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors

PubMed Central

Jenkins, R. Brian; Joyce, Peter; Mechtel, Deborah

2017-01-01

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay. PMID:28134815

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

Distributed sensor coordination for advanced energy systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tumer, Kagan

Motivation: The ability to collect key system level information is critical to the safe, efficient and reliable operation of advanced power systems. Recent advances in sensor technology have enabled some level of decision making directly at the sensor level. However, coordinating large numbers of sensors, particularly heterogeneous sensors, to achieve system level objectives such as predicting plant efficiency, reducing downtime or predicting outages requires sophisticated coordination algorithms. Indeed, a critical issue in such systems is how to ensure the interaction of a large number of heterogenous system components do not interfere with one another and lead to undesirable behavior. Objectivesmore » and Contributions: The long-term objective of this work is to provide sensor deployment, coordination and networking algorithms for large numbers of sensors to ensure the safe, reliable, and robust operation of advanced energy systems. Our two specific objectives are to: 1. Derive sensor performance metrics for heterogeneous sensor networks. 2. Demonstrate effectiveness, scalability and reconfigurability of heterogeneous sensor network in advanced power systems. The key technical contribution of this work is to push the coordination step to the design of the objective functions of the sensors, allowing networks of heterogeneous sensors to be controlled. By ensuring that the control and coordination is not specific to particular sensor hardware, this approach enables the design and operation of large heterogeneous sensor networks. In addition to the coordination coordination mechanism, this approach allows the system to be reconfigured in response to changing needs (e.g., sudden external events requiring new responses) or changing sensor network characteristics (e.g., sudden changes to plant condition). Impact: The impact of this work extends to a large class of problems relevant to the National Energy Technology Laboratory including sensor placement, heterogeneous sensor coordination, and sensor network control in advanced power systems. Each application has specific needs, but they all share the one crucial underlying problem: how to ensure that the interactions of a large number of heterogenous agents lead to coordinated system behavior. This proposal describes a new paradigm that addresses that very issue in a systematic way. Key Results and Findings: All milestones have been completed. Our results demonstrate that by properly shaping agent objective functions, we can develop large (up to 10,000 devices) heterogeneous sensor networks with key desirable properties. The first milestone shows that properly choosing agent-specific objective functions increases system performance by up to 99.9% compared to global evaluations. The second milestone shows evolutionary algorithms learn excellent sensor network coordination policies prior to network deployment, and these policies can be refined online once the network is deployed. The third milestone shows the resulting sensor networks networks are extremely robust to sensor noise, where networks with up to 25% sensor noise are capable of providing measurements with errors on the order of 10⁻³. The fourth milestone shows the resulting sensor networks are extremely robust to sensor failure, with 25% of the sensors in the system failing resulting in no significant performance losses after system reconfiguration.« less

A survey on routing protocols for large-scale wireless sensor networks.

PubMed

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. "Large-scale" means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.

A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks

PubMed Central

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed. PMID:22163808

A feedback-based secure path approach for wireless sensor network data collection.

PubMed

Mao, Yuxin; Wei, Guiyi

2010-01-01

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

Olfaction and Hearing Based Mobile Robot Navigation for Odor/Sound Source Search

PubMed Central

Song, Kai; Liu, Qi; Wang, Qi

2011-01-01

Bionic technology provides a new elicitation for mobile robot navigation since it explores the way to imitate biological senses. In the present study, the challenging problem was how to fuse different biological senses and guide distributed robots to cooperate with each other for target searching. This paper integrates smell, hearing and touch to design an odor/sound tracking multi-robot system. The olfactory robot tracks the chemical odor plume step by step through information fusion from gas sensors and airflow sensors, while two hearing robots localize the sound source by time delay estimation (TDE) and the geometrical position of microphone array. Furthermore, this paper presents a heading direction based mobile robot navigation algorithm, by which the robot can automatically and stably adjust its velocity and direction according to the deviation between the current heading direction measured by magnetoresistive sensor and the expected heading direction acquired through the odor/sound localization strategies. Simultaneously, one robot can communicate with the other robots via a wireless sensor network (WSN). Experimental results show that the olfactory robot can pinpoint the odor source within the distance of 2 m, while two hearing robots can quickly localize and track the olfactory robot in 2 min. The devised multi-robot system can achieve target search with a considerable success ratio and high stability. PMID:22319401

Localization with Sparse Acoustic Sensor Network Using UAVs as Information-Seeking Data Mules

DTIC Science & Technology

2013-05-01

technique to differentiate among several sources. 2.2. AoA Estimation AoA Models. The kth of NAOA AoA sensors produces an angular measurement modeled...squares sense. θ̂ = arg min φ 3∑ i=1 ( ̂τi0 − eTφ ri )2 (9) The minimization was done by gridding the one-dimensional angular space and finding the optimum...Latitude E5500 laptop running FreeBSD and custom Java applications to process and store the raw audio signals. Power Source: The laptop was powered for an

The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

PubMed Central

You, Kaiming; Yang, Wei; Han, Ruisong

2015-01-01

Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner’s lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner’s lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner’s lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner’s lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels. PMID:26426023

Experiences with a Decade of Wireless Sensor Networks in Mountain Cryosphere Research

NASA Astrophysics Data System (ADS)

Beutel, Jan

2017-04-01

Research in geoscience depends on high-quality measurements over long periods of time in order to understand processes and to create and validate models. The promise of wireless sensor networks to monitor autonomously at unprecedented spatial and temporal scale motivated the use of this novel technology for studying mountain permafrost in the mid 2000s. Starting from a first experimental deployment to investigate the thermal properties of steep bedrock permafrost in 2006 on the Jungfraujoch, Switzerland at 3500 m asl using prototype wireless sensors the PermaSense project has evolved into a multi-site and multi-discipline initiative. We develop, deploy and operate wireless sensing systems customized for long-term autonomous operation in high-mountain environments. Around this central element, we develop concepts, methods and tools to investigate and to quantify the connection between climate, cryosphere (permafrost, glaciers, snow) and geomorphodynamics. In this presentation, we describe the concepts and system architecture used both for the wireless sensor network as well as for data management and processing. Furthermore, we will discuss the experience gained in over a decade of planning, installing and operating large deployments on field sites spread across a large part of the Swiss and French Alps and applications ranging from academic, experimental research campaigns, long-term monitoring and natural hazard warning in collaboration with government authorities and local industry partners. Reference http://www.permasense.ch Online Open Data Access http://data.permasense.ch

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System

PubMed Central

Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco

2017-01-01

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.

PubMed

Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco

2017-08-31

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.

Study of Composite Plate Damages Using Embedded PZT Sensors with Various Center Frequency

NASA Astrophysics Data System (ADS)

Kang, Kyoung-Tak; Chun, Heoung-Jae; Son, Ju-Hyun; Byun, Joon-Hyung; Um, Moon-Kwang; Lee, Sang-Kwan

This study presents part of an experimental and analytical survey of candidate methods for damage detection of composite structural. Embedded piezoceramic (PZT) sensors were excited with the high power ultrasonic wave generator generating a propagation of stress wave along the composite plate. The same embedded piezoceramic (PZT) sensors are used as receivers for acquiring stress signals. The effects of center frequency of embedded sensor were evaluated for the damage identification capability with known localized defects. The study was carried out to assess damage in composite plate by fusing information from multiple sensing paths of the embedded network. It was based on the Hilbert transform, signal correlation and probabilistic searching. The obtained results show that satisfactory detection of defects could be achieved by proposed method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, Perry J.; Kottenstette, Richard Joseph; Crouch, Shannon M.

The National Ecological Observatory Network (NEON) is an ambitious National Science Foundation sponsored project intended to accumulate and disseminate ecologically informative sensor data from sites among 20 distinct biomes found within the United States and Puerto Rico over a period of at least 30 years. These data are expected to provide valuable insights into the ecological impacts of climate change, land-use change, and invasive species in these various biomes, and thereby provide a scientific foundation for the decisions of future national, regional, and local policy makers. NEON's objectives are of substantial national and international importance, yet they must be achievedmore » with limited resources. Sandia National Laboratories was therefore contracted to examine four areas of significant systems engineering concern; specifically, alternatives to commercial electrical utility power for remote operations, approaches to data acquisition and local data handling, protocols for secure long-distance data transmission, and processes and procedures for the introduction of new instruments and continuous improvement of the sensor network. The results of these preliminary systems engineering evaluations are presented, with a series of recommendations intended to optimize the efficiency and probability of long-term success for the NEON enterprise.« less

Cellular nonlinear networks for strike-point localization at JET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arena, P.; Fortuna, L.; Bruno, M.

2005-11-15

At JET, the potential of fast image processing for real-time purposes is thoroughly investigated. Particular attention is devoted to smart sensors based on system on chip technology. The data of the infrared cameras were processed with a chip implementing a cellular nonlinear network (CNN) structure so as to support and complement the magnetic diagnostics in the real-time localization of the strike-point position in the divertor. The circuit consists of two layers of complementary metal-oxide semiconductor components, the first being the sensor and the second implementing the actual CNN. This innovative hardware has made it possible to determine the position ofmore » the maximum thermal load with a time resolution of the order of 30 ms. Good congruency has been found with the measurement from the thermocouples in the divertor, proving the potential of the infrared data in locating the region of the maximum thermal load. The results are also confirmed by JET magnetic codes, both those used for the equilibrium reconstructions and those devoted to the identification of the plasma boundary.« less

A novel cooperative localization algorithm using enhanced particle filter technique in maritime search and rescue wireless sensor network.

PubMed

Wu, Huafeng; Mei, Xiaojun; Chen, Xinqiang; Li, Junjun; Wang, Jun; Mohapatra, Prasant

2018-07-01

Maritime search and rescue (MSR) play a significant role in Safety of Life at Sea (SOLAS). However, it suffers from scenarios that the measurement information is inaccurate due to wave shadow effect when utilizing wireless Sensor Network (WSN) technology in MSR. In this paper, we develop a Novel Cooperative Localization Algorithm (NCLA) in MSR by using an enhanced particle filter method to reduce measurement errors on observation model caused by wave shadow effect. First, we take into account the mobility of nodes at sea to develop a motion model-Lagrangian model. Furthermore, we introduce both state model and observation model to constitute a system model for particle filter (PF). To address the impact of the wave shadow effect on the observation model, we develop an optimal parameter derived by Kullback-Leibler divergence (KLD) to mitigate the error. After the optimal parameter is acquired, an improved likelihood function is presented. Finally, the estimated position is acquired. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Linking Simulation with Formal Verification and Modeling of Wireless Sensor Network in TLA+

NASA Astrophysics Data System (ADS)

Martyna, Jerzy

In this paper, we present the results of the simulation of a wireless sensor network based on the flooding technique and SPIN protocols. The wireless sensor network was specified and verified by means of the TLA+ specification language [1]. For a model of wireless sensor network built this way simulation was carried with the help of specially constructed software tools. The obtained results allow us to predict the behaviour of the wireless sensor network in various topologies and spatial densities. Visualization of the output data enable precise examination of some phenomenas in wireless sensor networks, such as a hidden terminal, etc.

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

PubMed

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.

An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks.

PubMed

Hosen, A S M Sanwar; Cho, Gi Hwan

2018-05-11

Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head's role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks' information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime.

An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks

PubMed Central

Hosen, A. S. M. Sanwar; Cho, Gi Hwan

2018-01-01

Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head’s role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks’ information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime. PMID:29751663

Low-cost, high-density sensor network for urban emission monitoring: BEACO2N

NASA Astrophysics Data System (ADS)

Kim, J.; Shusterman, A.; Lieschke, K.; Newman, C.; Cohen, R. C.

2017-12-01

In urban environments, air quality is spatially and temporally heterogeneous as diverse emission sources create a high degree of variability even at the neighborhood scale. Conventional air quality monitoring relies on continuous measurements with limited spatial resolution or passive sampling with high-density and low temporal resolution. Either approach averages the air quality information over space or time and hinders our attempts to understand emissions, chemistry, and human exposure in the near-field of emission sources. To better capture the true spatio-temporal heterogeneity of urban conditions, we have deployed a low-cost, high-density air quality monitoring network in San Francisco Bay Area distributed at 2km horizontal spacing. The BErkeley Atmospheric CO2 Observation Network (BEACO2N) consists of approximately 50 sensor nodes, measuring CO2, CO, NO, NO2, O­3, and aerosol. Here we describe field-based calibration approaches that are consistent with the low-cost strategy of the monitoring network. Observations that allow inference of emission factors and identification of specific local emission sources will also be presented.

Network Computing for Distributed Underwater Acoustic Sensors

DTIC Science & Technology

2014-03-31

underwater sensor network with mobility. In preparation. [3] EvoLogics (2013), Underwater Acoustic Modems, (Product Information Guide... Wireless Communications, 9(9), 2934–2944. [21] Pompili, D. and Akyildiz, I. (2010), A multimedia cross-layer protocol for underwater acoustic sensor networks ... Network Computing for Distributed Underwater Acoustic Sensors M. Barbeau E. Kranakis

Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors

PubMed Central

Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis

2010-01-01

In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment. PMID:22399930

Estimation of visual maps with a robot network equipped with vision sensors.

PubMed

Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis

2010-01-01

In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.

Capacity Building for Research and Education in GIS/GPS Technology and Systems

DTIC Science & Technology

2015-05-20

In multi- sensor area Wireless Sensor Networking (WSN) fields will be explored. As a step forward the research to be conducted in WSN field is to...Agriculture Using Technology for Crops Scouting in Agriculture Application of Technology in Precision Agriculture Wireless Sensor Network (WSN) in...Cooperative Engagement Capability Range based algorithms for Wireless Sensor Network Self-configurable Wireless Sensor Network Energy Efficient Wireless

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

PubMed

Huang, Shuqiang; Tao, Ming

2017-01-22

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K -center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

A Hybrid Memetic Framework for Coverage Optimization in Wireless Sensor Networks.

PubMed

Chen, Chia-Pang; Mukhopadhyay, Subhas Chandra; Chuang, Cheng-Long; Lin, Tzu-Shiang; Liao, Min-Sheng; Wang, Yung-Chung; Jiang, Joe-Air

2015-10-01

One of the critical concerns in wireless sensor networks (WSNs) is the continuous maintenance of sensing coverage. Many particular applications, such as battlefield intrusion detection and object tracking, require a full-coverage at any time, which is typically resolved by adding redundant sensor nodes. With abundant energy, previous studies suggested that the network lifetime can be maximized while maintaining full coverage through organizing sensor nodes into a maximum number of disjoint sets and alternately turning them on. Since the power of sensor nodes is unevenly consumed over time, and early failure of sensor nodes leads to coverage loss, WSNs require dynamic coverage maintenance. Thus, the task of permanently sustaining full coverage is particularly formulated as a hybrid of disjoint set covers and dynamic-coverage-maintenance problems, and both have been proven to be nondeterministic polynomial-complete. In this paper, a hybrid memetic framework for coverage optimization (Hy-MFCO) is presented to cope with the hybrid problem using two major components: 1) a memetic algorithm (MA)-based scheduling strategy and 2) a heuristic recursive algorithm (HRA). First, the MA-based scheduling strategy adopts a dynamic chromosome structure to create disjoint sets, and then the HRA is utilized to compensate the loss of coverage by awaking some of the hibernated nodes in local regions when a disjoint set fails to maintain full coverage. The results obtained from real-world experiments using a WSN test-bed and computer simulations indicate that the proposed Hy-MFCO is able to maximize sensing coverage while achieving energy efficiency at the same time. Moreover, the results also show that the Hy-MFCO significantly outperforms the existing methods with respect to coverage preservation and energy efficiency.

Gust prediction via artificial hair sensor array and neural network

NASA Astrophysics Data System (ADS)

Pankonien, Alexander M.; Thapa Magar, Kaman S.; Beblo, Richard V.; Reich, Gregory W.

2017-04-01

Gust Load Alleviation (GLA) is an important aspect of flight dynamics and control that reduces structural loadings and enhances ride quality. In conventional GLA systems, the structural response to aerodynamic excitation informs the control scheme. A phase lag, imposed by inertia, between the excitation and the measurement inherently limits the effectiveness of these systems. Hence, direct measurement of the aerodynamic loading can eliminate this lag, providing valuable information for effective GLA system design. Distributed arrays of Artificial Hair Sensors (AHS) are ideal for surface flow measurements that can be used to predict other necessary parameters such as aerodynamic forces, moments, and turbulence. In previous work, the spatially distributed surface flow velocities obtained from an array of artificial hair sensors using a Single-State (or feedforward) Neural Network were found to be effective in estimating the steady aerodynamic parameters such as air speed, angle of attack, lift and moment coefficient. This paper extends the investigation of the same configuration to unsteady force and moment estimation, which is important for active GLA control design. Implementing a Recurrent Neural Network that includes previous-timestep sensor information, the hair sensor array is shown to be capable of capturing gust disturbances with a wide range of periods, reducing predictive error in lift and moment by 68% and 52% respectively. The L2 norms of the first layer of the weight matrices were compared showing a 23% emphasis on prior versus current information. The Recurrent architecture also improves robustness, exhibiting only a 30% increase in predictive error when undertrained as compared to a 170% increase by the Single-State NN. This diverse, localized information can thus be directly implemented into a control scheme that alleviates the gusts without waiting for a structural response or requiring user-intensive sensor calibration.

Small Imaging Depth LIDAR and DCNN-Based Localization for Automated Guided Vehicle †

PubMed Central

Ito, Seigo; Hiratsuka, Shigeyoshi; Ohta, Mitsuhiko; Matsubara, Hiroyuki; Ogawa, Masaru

2018-01-01

We present our third prototype sensor and a localization method for Automated Guided Vehicles (AGVs), for which small imaging LIght Detection and Ranging (LIDAR) and fusion-based localization are fundamentally important. Our small imaging LIDAR, named the Single-Photon Avalanche Diode (SPAD) LIDAR, uses a time-of-flight method and SPAD arrays. A SPAD is a highly sensitive photodetector capable of detecting at the single-photon level, and the SPAD LIDAR has two SPAD arrays on the same chip for detection of laser light and environmental light. Therefore, the SPAD LIDAR simultaneously outputs range image data and monocular image data with the same coordinate system and does not require external calibration among outputs. As AGVs travel both indoors and outdoors with vibration, this calibration-less structure is particularly useful for AGV applications. We also introduce a fusion-based localization method, named SPAD DCNN, which uses the SPAD LIDAR and employs a Deep Convolutional Neural Network (DCNN). SPAD DCNN can fuse the outputs of the SPAD LIDAR: range image data, monocular image data and peak intensity image data. The SPAD DCNN has two outputs: the regression result of the position of the SPAD LIDAR and the classification result of the existence of a target to be approached. Our third prototype sensor and the localization method are evaluated in an indoor environment by assuming various AGV trajectories. The results show that the sensor and localization method improve the localization accuracy. PMID:29320434

Small Imaging Depth LIDAR and DCNN-Based Localization for Automated Guided Vehicle.

PubMed

Ito, Seigo; Hiratsuka, Shigeyoshi; Ohta, Mitsuhiko; Matsubara, Hiroyuki; Ogawa, Masaru

2018-01-10

We present our third prototype sensor and a localization method for Automated Guided Vehicles (AGVs), for which small imaging LIght Detection and Ranging (LIDAR) and fusion-based localization are fundamentally important. Our small imaging LIDAR, named the Single-Photon Avalanche Diode (SPAD) LIDAR, uses a time-of-flight method and SPAD arrays. A SPAD is a highly sensitive photodetector capable of detecting at the single-photon level, and the SPAD LIDAR has two SPAD arrays on the same chip for detection of laser light and environmental light. Therefore, the SPAD LIDAR simultaneously outputs range image data and monocular image data with the same coordinate system and does not require external calibration among outputs. As AGVs travel both indoors and outdoors with vibration, this calibration-less structure is particularly useful for AGV applications. We also introduce a fusion-based localization method, named SPAD DCNN, which uses the SPAD LIDAR and employs a Deep Convolutional Neural Network (DCNN). SPAD DCNN can fuse the outputs of the SPAD LIDAR: range image data, monocular image data and peak intensity image data. The SPAD DCNN has two outputs: the regression result of the position of the SPAD LIDAR and the classification result of the existence of a target to be approached. Our third prototype sensor and the localization method are evaluated in an indoor environment by assuming various AGV trajectories. The results show that the sensor and localization method improve the localization accuracy.

Design and implementation of smart sensor nodes for wireless disaster monitoring systems

NASA Astrophysics Data System (ADS)

Chen, Yih-Fan; Wu, Wen-Jong; Chen, Chun-Kuang; Wen, Chih-Min; Jin, Ming-Hui; Gau, Chung-Yun; Chang, Chih-Chie; Lee, Chih-Kung

2004-07-01

A newly developed smart sensor node that can monitor the safety of temporary structures such as scaffolds at construction sites is detailed in this paper. The design methodology and its trade-offs, as well as its influence on the optimization of sensor networks, is examined. The potential impact on civil engineering construction sites, environmental and natural disaster pre-warning issues, etc., all of which are foundations of smart sensor nodes and corresponding smart sensor networks, is also presented. To minimize the power requirements in order to achieve a true wireless system both in terms of signal and power, a sensor node was designed by adopting an 8051-based micro-controller, an ISM band RF transceiver, and an auto-balanced strain gage signal conditioner. With the built-in RF transceiver, all measurement data can be transmitted to a local control center for data integrity, security, central monitoring, and full-scale analysis. As a battery is the only well-established power source and there is a strong desire to eliminate the need to install bulky power lines, this system designed includes a battery-powered core with optimal power efficiency. To further extend the service life of the built-in power source, a power control algorithm has been embedded in the microcontroller of each sensor node. The entire system has been verified by experimental tests on full-scale scaffold monitoring. The results show that this system provides a practical method to monitor the structure safety in real time and possesses the potential of reducing maintenance costs significantly. The design of the sensor node, central control station, and the integration of several kinds of wireless communication protocol, all of which are successfully integrated to demonstrate the capabilities of this newly developed system, are detailed. Potential impact to the network topology is briefly examined as well.

Demonstration of a roving-host wireless sensor network for rapid assessment monitoring of structural health

NASA Astrophysics Data System (ADS)

Mascarenas, David D. L.; Flynn, Eric; Lin, Kaisen; Farinholt, Kevin; Park, Gyuhae; Gupta, Rajesh; Todd, Michael; Farrar, Charles

2008-03-01

A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is developing means to supply power to the sensor nodes in a cost-effective manner. In this work an initial test of a roving-host wireless sensor network was performed on a bridge near Truth or Consequences, NM in August of 2007. The roving-host wireless sensor network features a radio controlled helicopter responsible for wirelessly delivering energy to sensor nodes on an "as-needed" basis. In addition, the helicopter also serves as a central data repository and processing center for the information collected by the sensor network. The sensor nodes used on the bridge were developed for measuring the peak displacement of the bridge, as well as measuring the preload of some of the bolted joints in the bridge. These sensors and sensor nodes were specifically designed to be able to operate from energy supplied wirelessly from the helicopter. The ultimate goal of this research is to ease the requirement for battery power supplies in wireless sensor networks.

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

PubMed Central

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

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

PubMed

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.

Bio-Inspired Stretchable Absolute Pressure Sensor Network

PubMed Central

Guo, Yue; Li, Yu-Hung; Guo, Zhiqiang; Kim, Kyunglok; Chang, Fu-Kuo; Wang, Shan X.

2016-01-01

A bio-inspired absolute pressure sensor network has been developed. Absolute pressure sensors, distributed on multiple silicon islands, are connected as a network by stretchable polyimide wires. This sensor network, made on a 4’’ wafer, has 77 nodes and can be mounted on various curved surfaces to cover an area up to 0.64 m × 0.64 m, which is 100 times larger than its original size. Due to Micro Electro-Mechanical system (MEMS) surface micromachining technology, ultrathin sensing nodes can be realized with thicknesses of less than 100 µm. Additionally, good linearity and high sensitivity (~14 mV/V/bar) have been achieved. Since the MEMS sensor process has also been well integrated with a flexible polymer substrate process, the entire sensor network can be fabricated in a time-efficient and cost-effective manner. Moreover, an accurate pressure contour can be obtained from the sensor network. Therefore, this absolute pressure sensor network holds significant promise for smart vehicle applications, especially for unmanned aerial vehicles. PMID:26729134

The Coverage Problem in Video-Based Wireless Sensor Networks: A Survey

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2010-01-01

Wireless sensor networks typically consist of a great number of tiny low-cost electronic devices with limited sensing and computing capabilities which cooperatively communicate to collect some kind of information from an area of interest. When wireless nodes of such networks are equipped with a low-power camera, visual data can be retrieved, facilitating a new set of novel applications. The nature of video-based wireless sensor networks demands new algorithms and solutions, since traditional wireless sensor networks approaches are not feasible or even efficient for that specialized communication scenario. The coverage problem is a crucial issue of wireless sensor networks, requiring specific solutions when video-based sensors are employed. In this paper, it is surveyed the state of the art of this particular issue, regarding strategies, algorithms and general computational solutions. Open research areas are also discussed, envisaging promising investigation considering coverage in video-based wireless sensor networks. PMID:22163651

Interference-Robust Transmission in Wireless Sensor Networks

PubMed Central

Han, Jin-Seok; Lee, Yong-Hwan

2016-01-01

Low-power wireless sensor networks (WSNs) operating in unlicensed spectrum bands may seriously suffer from interference from other coexisting radio systems, such as IEEE 802.11 wireless local area networks. In this paper, we consider the improvement of the transmission performance of low-power WSNs by adjusting the transmission rate and the payload size in response to the change of co-channel interference. We estimate the probability of transmission failure and the data throughput and then determine the payload size to maximize the throughput performance. We investigate that the transmission time maximizing the normalized throughput is not much affected by the transmission rate, but rather by the interference condition. We adjust the transmission rate and the transmission time in response to the change of the channel and interference condition, respectively. Finally, we verify the performance of the proposed scheme by computer simulation. The simulation results show that the proposed scheme significantly improves data throughput compared with conventional schemes while preserving energy efficiency even in the presence of interference. PMID:27854249

Interference-Robust Transmission in Wireless Sensor Networks.

PubMed

Han, Jin-Seok; Lee, Yong-Hwan

2016-11-14

Low-power wireless sensor networks (WSNs) operating in unlicensed spectrum bands may seriously suffer from interference from other coexisting radio systems, such as IEEE 802.11 wireless local area networks. In this paper, we consider the improvement of the transmission performance of low-power WSNs by adjusting the transmission rate and the payload size in response to the change of co-channel interference. We estimate the probability of transmission failure and the data throughput and then determine the payload size to maximize the throughput performance. We investigate that the transmission time maximizing the normalized throughput is not much affected by the transmission rate, but rather by the interference condition. We adjust the transmission rate and the transmission time in response to the change of the channel and interference condition, respectively. Finally, we verify the performance of the proposed scheme by computer simulation. The simulation results show that the proposed scheme significantly improves data throughput compared with conventional schemes while preserving energy efficiency even in the presence of interference.

Energy harvesting: small scale energy production from ambient sources

NASA Astrophysics Data System (ADS)

Yeatman, Eric M.

2009-03-01

Energy harvesting - the collection of otherwise unexploited energy in the local environment - is attracting increasing attention for the powering of electronic devices. While the power levels that can be reached are typically modest (microwatts to milliwatts), the key motivation is to avoid the need for battery replacement or recharging in portable or inaccessible devices. Wireless sensor networks are a particularly important application: the availability of essentially maintenance free sensor nodes, as enabled by energy harvesting, will greatly increase the feasibility of large scale networks, in the paradigm often known as pervasive sensing. Such pervasive sensing networks, used to monitor buildings, structures, outdoor environments or the human body, offer significant benefits for large scale energy efficiency, health and safety, and many other areas. Sources of energy for harvesting include light, temperature differences, and ambient motion, and a wide range of miniature energy harvesters based on these sources have been proposed or demonstrated. This paper reviews the principles and practice in miniature energy harvesters, and discusses trends, suitable applications, and possible future developments.

Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

ERIC Educational Resources Information Center

Yu, Chao

2013-01-01

In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Wireless Sensor Network Applications for the Combat Air Forces

DTIC Science & Technology

2006-06-13

WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT...Government. AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT Presented to the...Major, USAF June 2006 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS

A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection

PubMed Central

Mao, Yuxin; Wei, Guiyi

2010-01-01

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose. PMID:22163424

Smart border: ad-hoc wireless sensor networks for border surveillance

NASA Astrophysics Data System (ADS)

He, Jun; Fallahi, Mahmoud; Norwood, Robert A.; Peyghambarian, Nasser

2011-06-01

Wireless sensor networks have been proposed as promising candidates to provide automated monitoring, target tracking, and intrusion detection for border surveillance. In this paper, we demonstrate an ad-hoc wireless sensor network system for border surveillance. The network consists of heterogeneously autonomous sensor nodes that distributively cooperate with each other to enable a smart border in remote areas. This paper also presents energy-aware and sleeping algorithms designed to maximize the operating lifetime of the deployed sensor network. Lessons learned in building the network and important findings from field experiments are shared in the paper.

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

PubMed Central

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment. PMID:22163678

Automated construction of node software using attributes in a ubiquitous sensor network environment.

PubMed

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric-the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization

PubMed Central

Sánchez-Rodríguez, David; Hernández-Morera, Pablo; Quinteiro, José Ma.; Alonso-González, Itziar

2015-01-01

Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have. PMID:26110413

A sensor network based virtual beam-like structure method for fault diagnosis and monitoring of complex structures with Improved Bacterial Optimization

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-02-01

This paper proposes a novel method for the fault diagnosis of complex structures based on an optimized virtual beam-like structure approach. A complex structure can be regarded as a combination of numerous virtual beam-like structures considering the vibration transmission path from vibration sources to each sensor. The structural 'virtual beam' consists of a sensor chain automatically obtained by an Improved Bacterial Optimization Algorithm (IBOA). The biologically inspired optimization method (i.e. IBOA) is proposed for solving the discrete optimization problem associated with the selection of the optimal virtual beam for fault diagnosis. This novel virtual beam-like-structure approach needs less or little prior knowledge. Neither does it require stationary response data, nor is it confined to a specific structure design. It is easy to implement within a sensor network attached to the monitored structure. The proposed fault diagnosis method has been tested on the detection of loosening screws located at varying positions in a real satellite-like model. Compared with empirical methods, the proposed virtual beam-like structure method has proved to be very effective and more reliable for fault localization.

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network.

PubMed

Magar, Kaman Thapa; Reich, Gregory W; Kondash, Corey; Slinker, Keith; Pankonien, Alexander M; Baur, Jeffery W; Smyers, Brian

2016-11-10

Distributed arrays of artificial hair sensors have bio-like sensing capabilities to obtain spatial and temporal surface flow information which is an important aspect of an effective fly-by-feel system. The spatiotemporal surface flow measurement enables further exploration of additional flow features such as flow stagnation, separation, and reattachment points. Due to their inherent robustness and fault tolerant capability, distributed arrays of hair sensors are well equipped to assess the aerodynamic and flow states in adverse conditions. In this paper, a local flow measurement from an array of artificial hair sensors in a wind tunnel experiment is used with a feedforward artificial neural network to predict aerodynamic parameters such as lift coefficient, moment coefficient, free-stream velocity, and angle of attack on an airfoil. We find the prediction error within 6% and 10% for lift and moment coefficients. The error for free-stream velocity and angle of attack were within 0.12 mph and 0.37 degrees. Knowledge of these parameters are key to finding the real time forces and moments which paves the way for effective control design to increase flight agility, stability, and maneuverability.

Towards efficient mobile M2M communications: survey and open challenges.

PubMed

Pereira, Carlos; Aguiar, Ana

2014-10-20

Machine-to-Machine (M2M) communications enable networked devices and services to exchange information and perform actions seamlessly without the need for human intervention. They are viewed as a key enabler of the Internet of Things (IoT) and ubiquitous applications, like mobile healthcare, telemetry, or intelligent transport systems. We survey existing work on mobile M2M communications, we identify open challenges that have a direct impact on performance and resource usage efficiency, especially the impact on energy efficiency, and we review techniques to improve communications. We review the ETSI standard and application protocols, and draw considerations on the impact of their use in constrained mobile devices. Nowadays, smartphones are equipped with a wide range of embedded sensors, with varied local and wide area connectivity capabilities, and thus they offer a unique opportunity to serve as mobile gateways for other more constrained devices with local connectivity. At the same time, they can gather context data about users and environment from the embedded sensors. These capabilities may be crucial for mobile M2M applications. Finally, in this paper, we consider a scenario where smartphones are used as gateways that collect and aggregate data from sensors in a cellular network. We conclude that, in order for their use to the feasible in terms of a normal depletion time of a smartphone's battery, it is a good advice to maximize the collection of data necessary to be transmitted from nearby sensors, and maximize the intervals between transmissions. More research is required to devise energy efficient transmission methods that enable the use of smartphones as mobile gateways.

Towards Efficient Mobile M2M Communications: Survey and Open Challenges

PubMed Central

Pereira, Carlos; Aguiar, Ana

2014-01-01

Machine-to-Machine (M2M) communications enable networked devices and services to exchange information and perform actions seamlessly without the need for human intervention. They are viewed as a key enabler of the Internet of Things (IoT) and ubiquitous applications, like mobile healthcare, telemetry, or intelligent transport systems. We survey existing work on mobile M2M communications, we identify open challenges that have a direct impact on performance and resource usage efficiency, especially the impact on energy efficiency, and we review techniques to improve communications. We review the ETSI standard and application protocols, and draw considerations on the impact of their use in constrained mobile devices. Nowadays, smartphones are equipped with a wide range of embedded sensors, with varied local and wide area connectivity capabilities, and thus they offer a unique opportunity to serve as mobile gateways for other more constrained devices with local connectivity. At the same time, they can gather context data about users and environment from the embedded sensors. These capabilities may be crucial for mobile M2M applications. Finally, in this paper, we consider a scenario where smartphones are used as gateways that collect and aggregate data from sensors in a cellular network. We conclude that, in order for their use to the feasible in terms of a normal depletion time of a smartphone's battery, it is a good advice to maximize the collection of data necessary to be transmitted from nearby sensors, and maximize the intervals between transmissions. More research is required to devise energy efficient transmission methods that enable the use of smartphones as mobile gateways. PMID:25333291