Accurate Detection of Important Events in WSNs
Vishal Krishna Singh, Manish Kumar, Shekhar Verma · IEEE Systems Journal · 2017
Security applications of wireless sensor networks (such as surveillance systems) require highly accurate detection systems for distinguishing the events of vital importance from simultaneously occurring random events. In order to improve the accuracy of the detection of such events of critical importance, a distributed in-network inference scheme is proposed in this paper. The problem of detection of such events is formulated as a sparse event detection problem and the awake cycle of every node is partitioned into smaller time blocks. Such a division allows the distributed inference algorithm to precisely identify the events of importance and their exact location in the physical sensor field. In order to further minimize the false alarm rate (FAR), spatially correlated data, from targeted regions, are obtained via a compressed sensing based data gathering scheme. The proposed scheme is able to achieve a significantly high accuracy rate of 0.9875 and exceptionally low FAR of 0.01. The prodigious performance of the proposed scheme continues in the experiments performed in outdoor environment and simulations.