In this paper we present an application of techniques from statistical signal processing to the problem of event detection in wireless sensor networks used for environmental monitoring. The proposed approach uses the well-established Principal Component Analysis (PCA) technique to build a compact model of the observed phenomena that is able to capture daily and seasonal trends in the collected measurements. We then use the divergence between actual measurements and model predictions to detect the existence of discrete events within the collected data streams. Our preliminary results show that this event detection mechanism is sensitive enough to detect the onset of rain events using the temperature modality of a wireless sensor network.
- Pub Date:
- January 2009
- Computer Science - Networking and Internet Architecture;
- Computer Science - Computer Vision and Pattern Recognition
- Workshop for Data Sharing and Interoperability on the World Wide Web (DSI 2007). April 2007, In Proceedings