In this study, an early fire detection system is proposed in order to minimize the losses caused by fires in the potentially chaotic environment that may occur after earthquakes in cities. This system consists of a structure that detects fire with convolutional neural network (CNN) based You Only Look Once (YOLO) model, determines the geolocation of the fire with stereo vision/epipolar geometry and provides information to the disaster management center via wireless sensor network (WSN). Experimental test findings conducted in İstanbul verify that the proposed system would be useful for post-earthquake fire detection with low cost, high reliability and high accuracy.

The Authors: Tacettin Kustu, Alev Taskin