Directional Antenna Systems for Long-Range Through-Wall Human Activity Recognition
CoRR(2024)
摘要
WiFi Channel State Information (CSI)-based human activity recognition (HAR)
enables contactless, long-range sensing in spatially constrained environments
while preserving visual privacy. However, despite the presence of numerous
WiFi-enabled devices around us, few expose CSI to users, resulting in a lack of
sensing hardware options. Variants of the Espressif ESP32 have emerged as
potential low-cost and easy-to-deploy solutions for WiFi CSI-based HAR. In this
work, four ESP32-S3-based 2.4GHz directional antenna systems are evaluated for
their ability to facilitate long-range through-wall HAR. Two promising systems
are proposed, one of which combines the ESP32-S3 with a directional biquad
antenna. This combination represents, to the best of our knowledge, the first
demonstration of such a system in WiFi-based HAR. The second system relies on
the built-in printed inverted-F antenna (PIFA) of the ESP32-S3 and achieves
directionality through a plane reflector. In a comprehensive evaluation of
line-of-sight (LOS) and non-line-of-sight (NLOS) HAR performance, both systems
are deployed in an office environment spanning a distance of 18 meters across
five rooms. In this experimental setup, the Wallhack1.8k dataset, comprising
1806 CSI amplitude spectrograms of human activities, is collected and made
publicly available. Based on Wallhack1.8k, we train activity recognition models
using the EfficientNetV2 architecture to assess system performance in LOS and
NLOS scenarios. For the core NLOS activity recognition problem, the biquad
antenna and PIFA-based systems achieve accuracies of 92.0±3.5 and
86.8±4.7, respectively, demonstrating the feasibility of long-range
through-wall HAR with the proposed systems.
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