Fire detection system based on improved multi-sensor information fusion

Abstract

In the fire detection system, the evidences of multiple sensors often conflict with each other. If the classical DS(Dempster-Shafer) evidence theory is used for information fusion, it will lead to a high rate of misjudgment. In this paper, an improved DS evidence theory algorithm based on standard deviation is proposed and applied to the fire detection system to judge the fire state.This paper first describes the working principle of the system in detail, and then uses the overall standard deviation of sensor evidence to measure each sensor, judge the conflicting evidence items, then redefine the weight of each sensor according to the degree of conflict, modify the probability distribution of the conflict evidence. Finally, the DS combination rule calculation is performed to corrected basic probability assignment( BPA) to obtain the fusion result. The experimental results show that the method proposed in this paper can effectively improve the evidence problems in the classical evidence theory, improves the fire identification ability and the speed of fire prediction, and greatly enhances the reliability of the system.