An Outlier detection approach with data mining in wireless sensor network

Abstract

Wireless sensor networks had been deployed in the real world to collect large amounts of raw sensed data. However, the
key challenge is to extract high level knowledge from such raw data. Sensor networks applications; outlier/anomaly
detection has been paid more and more attention. The propose of a classification approach that provides outlier
detection and data classification simultaneously. Experiments on Intel Berkley lab sensor dataset show that the proposed
approach outperforms other techniques in both effectiveness & efficiency.