Poster abstract: Exploiting human mobility trajectory information in indoor device-free passive tracking

Author(s):  
Chenren Xu ◽  
Bernhard Firner ◽  
Yanyong Zhang ◽  
Richard Howard ◽  
Jun Li
2013 ◽  
Vol 13 (10) ◽  
pp. 3785-3792 ◽  
Author(s):  
Xufei Mao ◽  
ShaoJie Tang ◽  
Jiliang Wang ◽  
Xiang Yang Li

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3276 ◽  
Author(s):  
Biao Zhou ◽  
Deockhyeon Ahn ◽  
Jungpyo Lee ◽  
Chao Sun ◽  
Sabbir Ahmed ◽  
...  

Target tracking technologies in wireless sensor network (WSNs) environments fall into two categories: active and passive schemes. Unlike with the active positioning schemes, in which the targets are required to hold cooperative devices, the research on passive tracking, i.e., tracking device-free targets, has recently showed promise. In the WSN, device-free targets can be tracked by sensing radio frequency tomography (RFT) on the line-of-sight links (LOSLs). In this paper, we propose a passive tracking scheme exploiting both adaptive-networking LOSL webs and geometric constraint methodology for tracking single targets, as well as multiple targets. Regarding fundamental knowledge, we firstly explore the spatial diversity technique for RFT detection in realistic situations. Then, we analyze the power consumption of the WSN and propose an adaptive networking scheme for the purpose of energy conservation. Instead of maintaining a fixed LOSL density, the proposed scheme can adaptively adjust the networking level to save energy while guaranteeing tracking accuracy. The effectiveness of the proposed scheme is evaluated with computer simulations. According to the results, it is observed that the proposed scheme can sufficiently reduce power consumption, while providing qualified tracking performance.


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