Energy-based target numeration in wireless sensor networks

被引:0
|
作者
Guo, Yan [1 ]
Hua, Bei [1 ]
Yue, Lihua [1 ]
机构
[1] Univ Sci & Technol China, Dept Comp Sci & Technol, Hefei 230027, Anhui, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Target numeration is of great importance for activity monitoring applications in wireless sensor networks (WSNs); however it is also a challenging problem in a WSN only equipped with simple amplitude sensors. Only a few algorithms have been proposed to solve the problem of target counting, and their accuracy and computational complexity is not satisfactory. This paper provides a two-step energy-based target numeration (EBTN) algorithm that firstly groups the sensor nodes that detect a target into separate clusters, and then calculates the number of targets covered by each cluster based on the total signal energy collected over the cluster A polynomial regression function is used to approximate the signal strength over a cluster and the total energy is estimated by taking the integral of the function over the area. By combining with preliminary clustering step, energy-based target counting greatly improves the counting accuracy. Experiments also show that EBTN requires lower node density and computational complexity compared with other algorithms.
引用
收藏
页码:383 / 388
页数:6
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