Application Of Data Fusion Technology In Fire Detection System Based On The Internet Of Things

At present, fire is the major one of the most often and common threat to publicsafety and social development in various disasters, so fire detection technology is theeffective means to prevent fire and reduce the fire losses. The traditional function ofthe fire protection system is relatively simple. And the characteristic parameters forfire judgment is single. The traditional system often miss some faults and producefalse positives. It will obtain a greater degree of information of the measured targetand the environment to apply the data fusion technology in fire detection.And it canfurther improve intelligence and accuracy of fire protection system.As early as1973, the United States has already begun the research on data fusiontechnology. In1988, it grow to be the focus of its research and development oftechnology. The technology has been applied to the military war in1991. Currently,multi-sensor data fusion technology has changed from sporadic dispersed researchinto an independent field of study. It even has an important effect in the field ofelectronics, computer and information science.Bias method, D-S evidential reasoning, neural network and fuzzy theoryalgorithm is relatively common data fusion algorithm. Data fusion has three layers ofstructure, according to this characteristic, this article use the appropriate algorithms atdifferent levels. So it can play the advantages of different algorithm and can make upfor each other’s deficiencies. It can further to improve the reliability and accuracy offusion results, so as to reduce the false alarm rate of fire judgment.This article first built a small fire characteristic data acquisition system based onZigBee technology. Respectively from hardware and software to realize the twoaspects in detail and analysis of the concept and the application method of Z-stackprotocol stack. The acquisition system has been tested and performance-relatedfunctions. Experimental results show the system can effectively collect temperature,smoke concentration and CO concentration parameters of fire.Then this article proposed a fire detection algorithm applied in intelligent firesystems. It combines neural network and fuzzy reasoning algorithm. The writertheoretically analyzed the advantages and disadvantages of these two algorithms, additionally using neural network toolbox and fuzzy reasoning tools boxes ofMATLAB software to simulate and analyze these two algorithms. The conclusionstells us that the combination of these two algorithms is suitable for fire detection.Finally, the writer develops a manage software on VS2010development platform.Respectively, to achieve function of serial data transmission, fire detection algorithmsand access to database. This manage software provides a good interactive platformthat can be observed parameters of fire features in real-time acquisition and see theresults of the system after the fire judgment. The user can also access the database toview historical data.