摘要
信息技术飞速发展不断提高人们的生活水平,传统的家居防盗方法已经不能满足人们的需求,而基于传感器和视频图像的智能家居防盗监测方法具有安装不方便、涉及隐私和不易处理遮挡的问题。为弥补当前无线信号对于智能家居防盗监测的空白,本文提出一种基于WiFi信道状态信息的智能家居防盗监测方法。通过采集WiFi信号的信道状态信息,利用卡尔曼滤波实现数据的去噪,采用K最邻近算法进行分类,最终可以实现静态、开门、开窗3种室内环境的监测,达到智能家居防盗监测的目的。
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.
作者
郭阿英
许志猛
余向阳
Guo Aying;Xu Zhimeng;Yu Xiangyang(College of Physics&Information Engineering,Fuzhou University,Fuzhou 350108)
出处
《电气技术》
2019年第12期13-16,共4页
Electrical Engineering
基金
国家自然科学基金资助项目（61401100）
福建省自然科学基金资助项目（2018J01805）
福州大学人才基金（GXRC-18083）
关键词
信道状态信息
卡尔曼滤波
K最邻近算法
channel state information(CSI)
Kalman filter
K-nearest neighbor (KNN) algorithm
