Event Boundary Detection Method Based on Wireless Sensor Network and Linear Neural Network
WU Peng-Fei1,2, LI Guang-Hui1, ZHU Hong1, ZENG Song-Wei1, LU Wen-Wei1
1.School of Information Engineering, Zhejiang A&F University, Hangzhou 311300 2.School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003
Abstract Environmental monitoring is a typical application in wireless sensor network (WSN), and event boundary detection is important for environmental monitoring. In this paper, a temporal-spatial data model of WSN is established, and then an event boundary detection method based on the linear neural network is presented. Firstly, the temporal correlation of data stream is analyzed, and the abnormal data set is determined based on linear neural network technique. Then, the event boundary is detected by using the spatial correlation of data stream between the neighbor nodes, and both the fault nodes and the event boundary nodes can be found. Thus, the location and the size of the event region can be estimated. Theoretical analysis and experimental results show that the proposed method has a high accuracy of fault node and event boundary detection and a low false positive rate.
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2015, Vol. 28 
