scholarly journals Efficient and Adaptive Node Selection for Target Tracking in Wireless Sensor Network

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Juan Feng ◽  
Hongwei Zhao ◽  
Baowang Lian
Keyword(s):  
Wireless Sensor Network ◽  
Target Tracking ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Selection Strategy ◽  
Tracking Accuracy ◽  
Node Selection ◽  
Information Utility ◽  
Distance Weighted

In target tracking wireless sensor network, choosing the proper working nodes can not only minimize the number of active nodes, but also satisfy the tracking reliability requirement. However, most existing works focus on selecting sensor nodes which are the nearest to the target for tracking missions and they did not consider the correlation of the location of the sensor nodes so that these approaches can not meet all the goals of the network. This work proposes an efficient and adaptive node selection approach for tracking a target in a distributed wireless sensor network. The proposed approach combines the distance-based node selection strategy and particle filter prediction considering the spatial correlation of the different sensing nodes. Moreover, a joint distance weighted measurement is proposed to estimate the information utility of sensing nodes. Experimental results show that EANS outperformed the state-of-the-art approaches by reducing the energy cost and computational complexity as well as guaranteeing the tracking accuracy.

scholarly journals Efficient Node and Sensed Module Management for Multisensory Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2328 ◽  
Author(s):  
Juan Feng ◽  
Xiaozhu Shi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Management Strategies ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Tracking Accuracy ◽  
Node Selection ◽  
Information Utility ◽  
Save Energy ◽  
Selection Of

In target tracking wireless sensor networks, choosing a part of sensor nodes to execute tracking tasks and letting the other nodes sleep to save energy are efficient node management strategies. However, at present more and more sensor nodes carry many different types of sensed modules, and the existing researches on node selection are mainly focused on sensor nodes with a single sensed module. Few works involved the management and selection of the sensed modules for sensor nodes which have several multi-mode sensed modules. This work proposes an efficient node and sensed module management strategy, called ENSMM, for multisensory WSNs (wireless sensor networks). ENSMM considers not only node selection, but also the selection of the sensed modules for each node, and then the power management of sensor nodes is performed according to the selection results. Moreover, a joint weighted information utility measurement is proposed to estimate the information utility of the multiple sensed modules in the different nodes. Through extensive and realistic experiments, the results show that, ENSMM outperforms the state-of-the-art approaches by decreasing the energy consumption and prolonging the network lifetime. Meanwhile, it reduces the computational complexity with guaranteeing the tracking accuracy.

Target Tracking in Wireless Sensor Network

2020 ◽  
pp. 857-880
Author(s):  
Madhuri Rao ◽  
Narendra Kumar Kamila
Keyword(s):  
Wireless Sensor Network ◽  
Target Tracking ◽  
Sensor Network ◽  
Traffic Control ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Matlab Simulation ◽  
Wireless Sensor Nodes ◽  
Habitat Monitoring ◽  
Emergency Rescue

Wireless Sensor nodes are being employed in various applications like in traffic control, battlefield, and habitat monitoring, emergency rescue, aerospace systems, healthcare systems and in intruder tracking recently. Tracking techniques differ in almost every application of Wireless Sensor Network (WSN), as WSN is itself application specific. The chapter aims to present the current state of art of the tracking techniques. It throws light on how mathematically target tracking is perceived and then explains tracking schemes and routing techniques based on tracking techniques. An insight of how to code localization techniques in matlab simulation tool is provided and analyzed. It further draws the attention of the readers to types of tracking scenarios. Some of the well established tracking techniques are also surveyed for the reader's benefit. The chapter presents with open research challenges that need to be addressed along with target tracking in wireless sensor networks.

scholarly journals IMM Filter Based Human Tracking Using a Distributed Wireless Sensor Network

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Sen Zhang ◽  
Wendong Xiao ◽  
Jun Gong
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Node ◽  
Computing System ◽  
Human Motion ◽  
Wireless Sensor ◽  
Human Tracking ◽  
Multiple Model ◽  
Tracking Accuracy ◽  
Node Selection

This paper proposes a human tracking approach in a distributed wireless sensor network. Most of the efforts on human tracking focus on vision techniques. However, most vision-based approaches to moving object detection involve intensive real-time computations. In this paper, we present an algorithm for human tracking using low-cost range wireless sensor nodes which can contribute lower computational burden based on a distributed computing system, while the centralized computing system often makes some information from sensors delay. Because the human target often moves with high maneuvering, the proposed algorithm applies the interacting multiple model (IMM) filter techniques and a novel sensor node selection scheme developed considering both the tracking accuracy and the energy cost which is based on the tacking results of IMM filter at each time step. This paper also proposed a novel sensor management scheme which can manage the sensor node effectively during the sensor node selection and the tracking process. Simulations results show that the proposed approach can achieve superior tracking accuracy compared to the most recent human motion tracking scheme.

Target Tracking in Wireless Sensor Network

2017 ◽  
pp. 413-437
Author(s):  
Madhuri Rao ◽  
Narendra Kumar Kamila
Keyword(s):  
Wireless Sensor Network ◽  
Target Tracking ◽  
Sensor Network ◽  
Traffic Control ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Matlab Simulation ◽  
Wireless Sensor Nodes ◽  
Habitat Monitoring ◽  
Emergency Rescue

Wireless Sensor nodes are being employed in various applications like in traffic control, battlefield, and habitat monitoring, emergency rescue, aerospace systems, healthcare systems and in intruder tracking recently. Tracking techniques differ in almost every application of Wireless Sensor Network (WSN), as WSN is itself application specific. The chapter aims to present the current state of art of the tracking techniques. It throws light on how mathematically target tracking is perceived and then explains tracking schemes and routing techniques based on tracking techniques. An insight of how to code localization techniques in matlab simulation tool is provided and analyzed. It further draws the attention of the readers to types of tracking scenarios. Some of the well established tracking techniques are also surveyed for the reader's benefit. The chapter presents with open research challenges that need to be addressed along with target tracking in wireless sensor networks.

scholarly journals Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking

2019 ◽  
Vol 8 (12) ◽  
pp. 4517-4524
Keyword(s):  
Wireless Sensor Network ◽  
Target Tracking ◽  
Sensor Network ◽  
Sensor Node ◽  
Average Energy ◽  
Extended Period ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Simulator ◽  
Average Scheme

In wireless sensor network application, the localization of nodes are carried out for extended life time of the node. Many applications in wireless sensor network perform localization of nodes over an extended period of time with energy variance. However, optimal selection algorithm poses new challenges to the overall transmission power levels for target detection, and thus localized energy optimized sensor management strategies are necessary for improving the accuracy of target tracking. In this work, it is proposed to develop a Bayesian Localized Energy Optimized Sensor Distribution (BLEOSD) scheme for efficient target tracking in Wireless Sensor Network. The sensor node localized with Bayesian average scheme thatestimates the sensor node’s energy are optimized as per data transfer capacity verification. The Bayesian average energy level of the sensor network is compared with the energy of each sensor node. The sensor nodes are localized and energy distribution based on the Bayesian energy estimate for efficient target tracking. The sensor node distribution strategy improves the accuracyto identify the targets effectively. Experiments are conducted using simulation of WSN by varying number of nodes, energy levels of the node and target object density using the Network Simulator Tool (NS2) The proposed BLEOSD technique is compared with various recent methods by evaluating accuracy of target tracking, energy consumption rate, localized node density and time for target tracking. The experimental results shows that the performance of BLESOD is more encouraging compared to contemporary methods.

scholarly journals Performance enhancement of wireless sensor network by using non-orthogonal multiple access and sensor node selection schemes

2021 ◽  
Vol 21 (2) ◽  
pp. 886
Author(s):  
Duy-Hung Ha ◽  
Duy-Binh Ha ◽  
Van-Truong Truong ◽  
Van-Duc Phan ◽  
Q. S. Vu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Multiple Access ◽  
Sensor Node ◽  
Rayleigh Fading ◽  
Performance Enhancement ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Amplify And Forward ◽  
Node Selection

In this paper, we investigate a relaying wireless sensor network (WSN) with the non-orthogonal multiple access (NOMA) and sensor node selection schemes over Rayleigh fading. Precisely, the system consists of two sensor clusters, a sink node, and an amplify-and-forward (AF) relay. These sensors applying the NOMA and sensor node selection schemes transmit the sensing data from the sensor clusters via the relay to the sink. We derived the expressions of outage probability and throughput for two sensor nodes. We also provide numerical results to examine the behavior of the system. Finally, we verify the validity of our analysis by using the Monte-Carlo simulation.

scholarly journals Energy-Efficient Constant Gain Kalman Filter Based Tracking in Wireless Sensor Network

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Kirti Hirpara ◽  
Keyur Rana
Keyword(s):  
Energy Efficiency ◽  
Kalman Filter ◽  
Wireless Sensor Network ◽  
Target Tracking ◽  
Sensor Network ◽  
Energy Efficient ◽  
Base Station ◽  
Wireless Sensor ◽  
Tracking Accuracy ◽  
Prediction Techniques

Target tracking is one of the most widely used applications of wireless sensor network (WSN). Efficient usage of energy is a key issue in WSN application such as target tracking. Another important criterion is a tracking accuracy that can be achieved by using appropriate tracking mechanism. Because of the special characteristic of WSN, there is a trade-off between tracking accuracy and power consumption. Our aim is to improve tracking accuracy as well as provide energy-efficient solution by integrating the concept of clustering and prediction techniques. This paper presents Energy-Efficient Constant Gain Kalman Filter based Tracking (EECGKFT) algorithm to optimize the energy usage and to increase the tracking accuracy. There is also a need to collect data from network having a mobile Base Station (BS). Hence, performance of proposed algorithm is analyzed for a static BS and also for mobile BS. The results depict that proposed algorithm performs better compared to the existing algorithms in energy efficiency and prediction accuracy. Analysis of results validates that EECGKFT increases energy efficiency by reducing transmission of unnecessary data in the sensor network environment and also provides good tracking results.

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