WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing

• URL: http://arxiv.org/abs/2402.09430v2
• Date: Tue, 12 Mar 2024 11:48:02 GMT
• Title: WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing
• Authors: Shuokang Huang, Kaihan Li, Di You, Yichong Chen, Arvin Lin, Siying Liu, Xiaohui Li, Julie A. McCann
• Abstract summary: WiMANS is the first dataset for multi-user sensing based on WiFi. We exploit WiMANS to benchmark the performance of state-of-the-art WiFi-based human sensing models and video-based models.
• Score: 8.143761572557539
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: WiFi-based human sensing has exhibited remarkable potential to analyze user behaviors in a non-intrusive and device-free manner, benefiting applications as diverse as smart homes and healthcare. However, most previous works focus on single-user sensing, which has limited practicability in scenarios involving multiple users. Although recent studies have begun to investigate WiFi-based multi-user sensing, there remains a lack of benchmark datasets to facilitate reproducible and comparable research. To bridge this gap, we present WiMANS, to our knowledge, the first dataset for multi-user sensing based on WiFi. WiMANS contains over 9.4 hours of dual-band WiFi Channel State Information (CSI), as well as synchronized videos, monitoring simultaneous activities of multiple users. We exploit WiMANS to benchmark the performance of state-of-the-art WiFi-based human sensing models and video-based models, posing new challenges and opportunities for future work. We believe WiMANS can push the boundaries of current studies and catalyze the research on WiFi-based multi-user sensing.

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