基于信道状态信息的室内环境检测技术研究

RESEARCH ON INDOOR ENVIRONMENT DETECTION TECHNOLOGY BASED ON CHANNEL STATE INFORMATION

室内空气质量是人们广泛关注的问题之一,然而如何对室内空气进行全面监测一直是一个难题,传统的监控摄像头和光学传感器系统都难以全方面覆盖检测区域。基于此,本研究创新性地设计了一种利用现有商用Wi-Fi网络来对室内环境进行实时感知监测的系统。基于室内环境检测技术现状,概述了相关室内环境检测技术的试验方法和机器学习算法模型。通过研究不同污染等级对室内静态CSI信号的影响,实现了对室内污染的精确分类。

Indoor air quality is one of the issues that people are widely concerned about,but how to realize the comprehensive monitoring of indoor air has always been a difficult problem for us.Both traditional surveillance cameras and optical sensor systems are faced with the problem of not covering the detection area in all aspects.Based on the above social background,this paper innovatively designed a system that uses the existing commercial Wi-Fi network to conduct real-time perceptual monitoring of the indoor environment.Based on the current situation of indoor environment detection technology,the experimental method and machine learning algorithm model of related indoor environment detection technology are summarized.By studying the effects of different pollution grades on indoor static CSI signals,the precise classification of indoor pollution was achieved.