Continuous Multi-user Activity Tracking via Room-Scale mmWave Sensing
Recommended citation: Argha Sen, Anirban Das, Swadhin Pradhan, and Sandip Chakraborty (2024). Continuous Multi-user Activity Tracking via Room-Scale mmWave Sensing. In 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2024) https://dl.acm.org/doi/10.1109/IPSN61024.2024.00018
Continuous detection of human activities and presence is essential for developing a pervasive interactive smart space. Existing literature lacks robust wireless sensing mechanisms capable of continuously monitoring multiple users’ activities without prior knowledge of the environment. Developing such a mechanism requires simultaneous localization and tracking of multiple subjects. In addition, it requires identifying their activities at various scales, some being macro-scale activities like walking, squats, etc., while others are micro-scale activities like typing or sitting etc. In this paper, we develop a logistics system called Mars using Commercial off-the-shelf (COTS) Millimeter Wave (mmWave) radar, which employs an intelligent model to sense both macro and micro activities. In addition, it uses a dynamic spatial time-sharing approach to sense different subjects simultaneously. A thorough evaluation of MSARS shows that they can initiate activities an accuracy of > 93% and an average response time of ≈ 2 sec, with 5 subjects and 19 different activities. Download paper here
Recommended citation: Argha Sen, Anirban Das, Swadhin Pradhan, and Sandip Chakraborty (2024). Continuous Multi-user Activity Tracking via Room-Scale mmWave Sensing. In 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2024)