Continuous Multi-user Activity Tracking via Room-Scale mmWave Sensing

Published in ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2024) , 2024

Authors: Argha Sen, Anirban Das, Swadhin Pradhan, Sandip Chakraborty
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Developing robust wireless sensing mechanisms for continuously monitoring human activities and presence is crucial for creating pervasive interactive intelligent spaces. The existing literature lacks solutions that continuously monitor multiple users’ activities without prior knowledge of the environment. This requires simultaneous localization and tracking of multiple subjects and identifying their activities at various scales, including macro-scale activities like walking and squats and micro-scale activities like typing or sitting. In this demo, we present MARS, a holistic system using a single off-the-shelf mmWave radar. MARS employs an intelligent model to sense both macro and micro activities and uses a dynamic spatial time-sharing approach to sense different subjects simultaneously. Our thorough evaluation demonstrates that MARS can continuously infer activities with over 93% accuracy and an average response time of approximately 2 seconds, even with five subjects performing 19 different activities.

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