scholarly journals Geometric Midpoint Algorithm for Device-Free Localization in Low-Density Wireless Sensor Networks

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2924
Author(s):  
Chao Sun ◽  
Biao Zhou ◽  
Shangyi Yang ◽  
Youngok Kim
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Electronic Devices ◽  
Wireless Sensor ◽  
Low Density ◽  
Tracking Accuracy ◽  
Resource Limited ◽  
Geometric Objects ◽  
Device Free ◽  
Mean Square Errors

Device-free localization (DFL) is a technique used to track a target transporting no electronic devices. Radiofrequency (RF) tomography based DFL technology in wireless sensor networks has been a popular research topic in recent years. Typically, high-tracking accuracy requires a high-density wireless network which limits its application in some resource-limited scenarios. To solve this problem, a geometric midpoint (GM) algorithm based on the computations of simple geometric objects is proposed to realize effective tracking of moving targets in low-density wireless networks. First, we proposed a signal processing method for raw RSS signals collected from wireless links that can detect the fluctuations caused by a moving target effectively. Second, a geometric midpoint algorithm is proposed to estimate the location of the target. Finally, simulations and experiments were performed to validate the proposed scheme. The experimental results show that the proposed GM algorithm outperforms the geometric filter algorithm, which is a state-of-the-art DFL method that yields tracking root-mean-square errors up to 0.86 m and improvements in tracking accuracy up to 67.66%.

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.

iLight: Device-Free Passive Tracking Using Wireless Sensor Networks

2013 ◽  
Vol 13 (10) ◽  
pp. 3785-3792 ◽  
Author(s):  
Xufei Mao ◽  
ShaoJie Tang ◽  
Jiliang Wang ◽  
Xiang Yang Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Passive Tracking ◽  
Device Free

Localisation algorithm for large-scale and low-density wireless sensor networks

2011 ◽  
Vol 47 (15) ◽  
pp. 881 ◽  
Author(s):  
H. Dai ◽  
A.G. Chen ◽  
X.F. Gu ◽  
L. He
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Wireless Sensor ◽  
Low Density

Wireless Sensor Networks to Predict the Range Covered by the Priority Scheduling Algorithm for Multi-Target Tracking

2014 ◽  
Vol 687-691 ◽  
pp. 1071-1075
Author(s):  
Yong Long Zhuang ◽  
Xiao Lan Weng ◽  
Xiang He Wei
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Scheduling Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Tracking Accuracy ◽  
Detection Range ◽  
Multi Target Tracking ◽  
The Relationship

Research on multi-target tracking wireless sensor networks, the main problem is how to improve tracking accuracy and reduce energy consumption. Proposed use of forecasting methods to predict the target state, the selection of target detection range forecast based on the relationship between states and between sensor nodes deployed. And in accordance with the selected detection range, to wake up and form a cluster to track the target. In multi-target tracking will use to adjust the detection range, time to time to separate the conflict node of conflict, in order to achieve a successful track multiple targets. Simulation results show that the proposed method can indeed improve the chances of success of the track.

Particle filter based device free localisation and tracking for large scale wireless sensor networks

2015 ◽  
Vol 19 (3/4) ◽  
pp. 194 ◽  
Author(s):  
Jie Wang ◽  
Qinghua Gao ◽  
Xiaoyun Zhang ◽  
Hongyu Wang ◽  
Minglu Jin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Particle Filter ◽  
Large Scale ◽  
Wireless Sensor ◽  
Device Free
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