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| A method of home anti-theft monitoring based on channel state information |
| Guo Aying, Xu Zhimeng, Yu Xiangyang |
| College of Physics & Information Engineering, Fuzhou University, Fuzhou 350108 |
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Abstract With the rapid development of information technology, people's living standards have been continuously improved. The traditional home security methods can not meet people's needs. The intelligent home security monitoring method based on sensors and video images is inconvenient to install, involves privacy and is not easy to deal with privacy issues. In order to make up for the blank of the current wireless signal for the anti-theft monitoring of smart home, this paper proposes a method of anti-theft monitoring of smart home based on WiFi channel state information (CSI). The channel state information of WiFi signal is collected, and the data is denoised by Kalman filter. K-nearest neighbor (KNN) algorithm is used to classify the data. Finally, it can realize static, open door, open window monitoring of three indoor environments, and achieve the purpose of intelligent home anti-theft monitoring.
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Received: 15 May 2019
Published: 19 December 2019
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| Cite this article: |
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Guo Aying,Xu Zhimeng,Yu Xiangyang. A method of home anti-theft monitoring based on channel state information[J]. Electrical Engineering, 2019, 20(12): 13-16.
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| URL: |
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http://dqjs.cesmedia.cn/EN/Y2019/V20/I12/13
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[1] 赵静, 麻名蕊, 宋振. 基于物联网的智能家居安全防护系统设计[J]. 电子技术与软件工程, 2017(5): 215-217.
[2] 邓娜, 田增山, 袁正午. 基于达芬奇技术的视频监控系统设计[J]. 电子技术应用, 2015, 14(1): 25-27, 31.
[3] 鲜晓东, 常超, 胡颖, 等. 基于WSNs和GSM的室内环境监测预警系统设计[J]. 传感器与微系统, 2011, 30(6): 141-144.
[4] 张亚楠. 基于kinect及android平台的家庭防盗系统[J]. 电脑知识与技术, 2015, 11(22): 57-58.
[5] Halperin D, Hu Wenjun, Sheth A, et al.Tool release: gathering 802.11n traces with channel state infor- mation[J]. ACM Sigcomm Computer Communication Review, 2011, 41(1): 53.
[6] 党小超, 黄亚宁, 郝占军, 等. 基于信道状态信息的无源室内人员日常行为检测方法[J]. 通信学报, 2019, 40(4): 160-170.
[7] 杨铮, 刘云浩. WiFi雷达: 从RSSI到CSI[J]. 中国计算机学会通讯, 2014, 10(11): 55-60.
[8] 周牧, 耿小龙, 谢良波, 等. 室内Wi-Fi/PDR自适应鲁棒卡尔曼滤波融合定位方法[J]. 电子学报, 2019, 47(1): 9-15.
[9] 吴蔚, 谭献海, 钱晓群, 等. 基于卡尔曼滤波的室内定位可信指纹库研究与实现[J/OL]. 计算机应用研究, 2019, 37(6). http://kns.cnki.net/kcms/detail/51.1196. TP. 20190513.0922.027.html.
[10] 连天友, 余勤. 改进KNN算法对人体身份的识别[J/OL]. 计算机工程与应用, 2018. http://kns.cnki.net/ kcms/detail/11.2127.TP.20181106.1640.007.html.
[11] 刘炳南, 郭谋发, 陈永往. 基于KNN的配电网高阻接地故障识别[J]. 电气技术, 2019, 20(1): 18-23. |
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2019, Vol. 20 
