Efficient Forest Fire Detection System Based on Data Fusion Applied in Wireless Sensor Networks
Mohammed Anas El Abbassi, Abdelilah Jilbab, Abdennaser Bourouhou
Abstract
In this paper we propose an intelligent hybrid model for reliable and fast fire detection applied in Wireless Sensor Network platform. This model discusses a data fusion strategy hybridized with an intelligent information routing system based on a clustering method of sensor nodes located in the vicinity of the event. The transfer of the alert message to the base station is performed through the elected sensor nodes CH and IN. The alert message is transferred to notify BS in two successive levels of danger; first, the detection of the appearance of fire; second, the danger spread. The data fusion side is proposed in a hierarchical manner; the first step makes it possible to affirm the first appearance of fire detected by a first sensor node through a reasoning performed by the KNN classifier. The second is conditioned by the previous step, it allows in the positive case to perform an overall heterogeneous data fusion for a defined area where, in its first-level processing, data sorting operation are carried out using the K-means clustering. This processing allows ignoring unnecessary and incorrect data that influences the reliability of the detection. The magnitude of the event propagation is estimated in the second level using the Fuzzy Inference System in the final fusion center. This model shows, through its simulation experiments, a robustness of performance in terms of reliability of detection, rapidity of triggering of the alert, elimination of useless and redundant information, and will also guarantee an efficient energy consumption of the network which will lead to a remarkable extension of its lifetime.