Human Activity Recognition With Commercial WiFi Signals

Chen, Tian; Tian, Yue; Wang, Xianling; Kho, Yau Hee; Zhang, Zhong; Li, Wenda; Xiao, Baiyun

doi:10.1109/access.2022.3223437

Cited by 2 publications

(1 citation statement)

References 32 publications

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“…In recent years, researchers have discovered that WiFi technology serves not only communication purposes but also as a means of sensing specific information. Through the utilization of received signal strength indicator (RSSI) and channel state information (CSI), various applications including indoor localization [5,6], fall detection [7,8], and monitoring physical activity [9,10] have been successfully implemented. CSI, being a form of finegrained physical information, holds a notable advantage in its sensitivity to environmental changes, rendering it more effective in perception.…”

Section: Introductionmentioning

confidence: 99%

Multi-WiIR: Multi-User Identity Legitimacy Authentication Based on WiFi Device

Wei,

Dong

2024

Future Internet

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With the proliferation of WiFi devices, WiFi-based identification technology has garnered attention in the security domain and has demonstrated initial success. Nonetheless, when untrained illegitimate users appear, the classifier tends to categorize them as if they were trained users. In response to this issue, researchers have proposed identity legitimacy authentication systems to identify illicit users, albeit only applicable to individual users. In this article, we propose a multi-user legitimacy authentication system based on WiFi, termed Multi-WiIR. Leveraging WiFi signals, the system captures users’ walking patterns to ascertain their legitimacy. The core concept entails training a multi-branch deep neural network, designated WiIR-Net, for feature extraction of individual users. Binary classifiers are then applied to each user, and legitimacy is established by comparing the model’s output to predefined thresholds, thus facilitating multi-user legitimacy authentication. Moreover, the study experimentally investigated the impact of the number of legitimate individuals on accuracy rates. The results demonstrated that The Multi-WiIR system showed commendable performance with low latency, being capable of conducting legitimacy recognition in scenarios involving up to four users, with an accuracy rate reaching 85.11%.

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