BeAware: Convolutional neural network(CNN) based user behavior understanding through WiFi channel state information

被引:13
作者
Jia, Leyuan [1 ]
Gu, Yu [2 ]
Cheng, Ken [1 ]
Yan, Huan [1 ]
Ren, Fuji [3 ]
机构
[1] Hefei Univ Technol, Hefei, Peoples R China
[2] Hefei Univ Technol, Sch Comp & Informat, Hefei, Peoples R China
[3] Univ Tokushima, Fac Engn, Tokushima, Japan
关键词
User behavior analysis; WiFi channel state information (CSI); Fresnel zone; RECOGNITION;
D O I
10.1016/j.neucom.2019.09.111
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In modern informatics society, human beings are becoming more and more attached to the computer. Therefore, understanding user behavior is critical to various application fields like sedentary analysis, human-computer interaction, and affective computing. Current sensor-based and vision-based user behavior understanding approaches are either contact or obtrusive to user s, jeopardizing their availability and practicality. To this end, we present BeAware, a contactless Radio Frequency (RF) based user behavior understanding system leveraging the WiFi Channel State Information (CSI). The key idea is to visualize the channel data affected by human movements into time-series heat-map images, which are processed by a Convolutional Neural Network (CNN) to understand the corresponding user behaviors. We prototype BeAware on commodity low-cost WiFi devices and evaluate its performance in real-world environments. Experimental results have verified its effectiveness in recognizing user behaviors. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:457 / 463
页数:7
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