A Novel way of BPA calculation for context inference using sensor signals

Abstract

Basic probability assignment (BPA) has the key role in multi-sensor data fusion. This paper proposed a way to determine BPA using the various signals acquired from the sensors. It described the analysis of signals detected by the sensors. The determined BPA were used for multi-sensor data fusion to infer and recognize the context targeted by a wireless sensor networks. To determine BPA, the change rate was calculated and assessed to be reflected. The method enabled context inference using the sensor signals even when there was no advanced information of the situation. ©2014 SERSC.