Optimized Monitoring of Activities of Daily Living Using a Smart Watch and a Companion Robot
Fei Liang, Weihua Sheng, Alex J. Bishop, Emily R Roberts · 2025
In this paper, a collaborative activity monitoring system (CAMS) is developed by combining a smart watch and a robot for elderly care. To improve the performance of ADL monitoring, an optimization problem on sensor selection is formulated and solved. First, we presented an overview of the CAMS. Second, to balance activity recognition accuracy, power consumption on the watch, and privacy preferences, we developed a Deep Q-Learning (DQL) model that enables the robot to learn optimal sensor selection strategies, ensuring adaptive and efficient monitoring. Third, the proposed method was evaluated using both offline and real time data, which were collected in a smart home testbed and a real apartment, respectively. The results showed that, compared with the baseline methods, the proposed method could recognize ADLs with higher accuracy while saving energy and respecting users' privacy preferences.