Intelligent fire monitoring system based on the information fusion algorithm

Fire disaster is the most common disaster that threatens public safety and social development. Therefore, the prevention and rescue of fire disasters becomes the focus among the scientists. In order to prevent serious consequences of fire disasters, the performance, effectiveness and accuracy of fire monitoring systems should be improved. Current fire monitoring systems are mostly equipped with a single smoke sensor, thus their false alarm and missing report rates are high and the intelligence degree is low. To solve these problems, we applied the information fusion technique to the fire monitoring system and designed a multi-sensor intelligent fire monitoring system that was mainly composed of a detector and a master controller. The applied sensors included a smoke sensor, a temperature sensor and a carbonic oxide (CO) sensor. In addition, fuzzy system and radial basis function (RBF) neural network fusion algorithm were studied and sample data were pre-processed to obtain a rule base. Fire experiments were simulated and results showed that the designed fire monitoring system had high accuracy, as expected. Copyright © 2016 American Scientific Publishers All rights reserved.