Daily Living Activity Recognition with Frequency-Shift WiFi Backscatter Tags
Hikoto Iseda, Keiichi Yasumoto, Akira Uchiyama, Teruo Higashino
TL;DR
This paper introduces a WiFi-based system using frequency-shift backscatter tags to recognize daily activities in homes, offering privacy and low power consumption.
Contribution
A novel frequency-shift backscatter tag-based method for in-home activity recognition with demonstrated robustness and accuracy.
Findings
Frequency shifts can be detected within a 2 m range with 72% accuracy under line-of-sight conditions.
The system achieves 96.0% accuracy (F-score) in recognizing seven daily living activities.
Frequency shift detection is possible without line-of-sight at 3–5 m with increased packet overlaying.
Abstract
To provide diverse in-home services like elderly care, versatile activity recognition technology is essential. Radio-based methods, including WiFi CSI, RFID, and backscatter communication, are preferred due to their minimal privacy intrusion, reduced physical burden, and low maintenance costs. However, these methods face challenges, including environmental dependence, proximity limitations between the device and the user, and untested accuracy amidst various radio obstacles such as furniture, appliances, walls, and other radio waves. In this paper, we propose a frequency-shift backscatter tag-based in-home activity recognition method and test its feasibility in a near-real residential setting. Consisting of simple components such as antennas and switches, these tags facilitate ultra-low power consumption and demonstrate robustness against environmental noise because a context…
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Taxonomy
TopicsContext-Aware Activity Recognition Systems · Indoor and Outdoor Localization Technologies · IoT-based Smart Home Systems