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

fYear

2010

fDate

23-25 July 2010

Firstpage

1

Lastpage

3

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IEEC.2010.5533209

Filename

5533209