Research On Indoor Environment Detection Technology Based On Channel State Information

As the requirements for living and working spaces continue to increase,more and more attention is paid to indoor air pollution online detection technology.In view of the shortcomings of full coverage and complex equipment in the traditional visual camera and sensor monitoring and detection system in the indoor environment,this paper proposes and designs an indoor environment perception detection system based on commercial Wi-Fi.The specific work of the paper is summarized as follows:(1)Summarize and analyze the traditional indoor fine particle pollution detection methods,and propose technical solutions for the classification of indoor fine particle pollution levels using the CSI of the commercial Wi-Fi network for the problems and defects in it;(2)Introduce the basic principles of wireless channel status and parameter collection methods,and build an experimental data collection system;(3)Discuss the experimental method and data processing machine learning algorithm model of indoor fine particulate matter pollution classification system based on CSI;(4)Analyze the impact of different pollution levels on indoor static CSI signals,and use the method of fusing amplitude and phase information to achieve accurate classification of indoor pollution;(5)Analyze one of the causes of indoor pollution,that is,the influence of continuous smoking action characteristics on the indoor dynamic CSI signal,and complete the detection of indoor smoking behavior by extracting and matching the smoking dynamic behavior sequence.