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基于被动式定位的教室智能照明方法研究

发表时间:2022-06-27  浏览量:270  下载量:19
全部作者: 彭意贺,霍春光,武浩宇,刘影
作者单位: 辽宁工程技术大学电子与信息工程学院
摘 要: 针对当前教室内人少大面积照明和无人照明的情况,设计了一种基于WiFi的教室智能照明系统。利用WiFi的接收信号强度指示(received signal strength indication,RSSI)对室内人员进行非接触识别,根据反向传播(back propagation,BP)神经网络分析人进入室内后WiFi的RSSI波动规律,反推其传播路径中环境特征,以此来判别室内人员的存在;在获得室内人员的位置信息后,通过WiFi模块将开关具体灯具的命令无线传输给单片机控制系统,借助单片机完成对教室照明灯的智能控制,只打开人所处区域的灯具,以节省电能。最终系统的准确率高达84%,市场发展前景良好。
关 键 词: 信息处理技术;BP神经网络;WiFi指纹;接收信号强度指示;照明控制
Title: Intelligent illumination for classroom based on passive localization
Author: PENG Yihe, HUO Chunguang, WU Haoyu, LIU Ying
Organization: School of Electronics and Information Engineering, Liaoning Technical University
Abstract: Aiming at the problem of large-area-illumination with little people or the light on in empyty classroom, a WiFi-based intelligent illumination system for classroom was designed. Using the received signal strength indication (RSSI) of WiFi for non-contact identification of indoor people, the RSSI fluctuation pattern of WiFi after people enter the room was analyzed according to back propagation (BP) neural network, and the environmental characterisitics in its propagation path were reversely infer, so as to discern the presence of the indoor people. After obtaining the position information of the indoor people, the command to switch the corresponding lights would be transmitted wirelessly to the microcontrollers through WiFi module. In order to save the electricity, the control system would accomplish the intelligent control of classroom lights by switching on the lamps in the area where people were existed through microcontrollers. The accuracy of the final system was 84%. The system might have good market development prospects.
Key words: information processing technology; BP neural network; WiFi fingerprint; received signal strength indication; lightening control
发表期数: 2022年6月第2期
引用格式: 彭意贺,霍春光,武浩宇,等. 基于被动式定位的教室智能照明方法研究[J]. 中国科技论文在线精品论文,2022,15(2):160-167.
 
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