Dempster-Shafer Information Filtering Framework: Temporal and Spatio-Temporal Evidence Filtering

Abstract

This paper presents an information processing framework for Distributed Sensor Networks (DSNs). The framework is capable of directly processing temporally and spatially distributed multi-modality sensor data to extract information buried in the noise clutter. Moreover, we introduce distributed algorithms to implement Spatio-Temporal filtering applications in grid sensor networks within the context of the framework. The proposed framework is based on the belief notions in Dempster- Shafer (DS) evidence theory and Evidence Filtering method. Further analysis is done by exploiting a fire propagation scenario when high noise is present in the sensed data. We compare intuitively appealing results against Dempster-Shafer fusion method to grant further credence to the proposed framework.