Title :
Fire Monitoring System Based on Multi-Sensor Information Fusion
Author :
Yao, Yaochuan ; Yang, Jing ; Huang, Changquan ; Zhu, Wenyu
Author_Institution :
Sch. of Autom. & Electron. Inf., Sichuan Univ. of Sci. & Eng., Zigong, China
Abstract :
The reliability and versatility of the traditional fire monitoring system based on single-sensor information is relatively poor. In this paper, a fire monitoring system based on multi-sensor information fusion is discussed, and which adopts the ART2 (adaptive resonance theory model) and the three-layer BP neural network for two-layer fusion processing for temperature, smoke and CO sensors information, and it comprehensively uses a variety of fire parameters, and the real-time monitoring of fire conditions of the measured environment is realized, and its reliability and versatility are higher.
Keywords :
ART neural nets; backpropagation; computerised monitoring; fires; reliability; sensor fusion; smoke detectors; temperature sensors; ART2; adaptive resonance theory model; fire monitoring system; multisensor information fusion; real-time monitoring; single-sensor information; three-layer BP neural network; two-layer fusion processing; Condition monitoring; Fires; Gas detectors; Neural networks; Real time systems; Reliability theory; Resonance; Sensor fusion; Sensor systems; Temperature sensors;
Conference_Titel :
Information Engineering and Electronic Commerce (IEEC), 2010 2nd International Symposium on
Conference_Location :
Ternopil
Print_ISBN :
978-1-4244-6972-7
Electronic_ISBN :
978-1-4244-6974-1
DOI :
10.1109/IEEC.2010.5533209
