Near-optimal energy allocation for self-powered wearable systems

Wearable internet of things (IoT) devices are becoming popular due to their small form factor and low cost. Potential applications include human health and activity monitoring by embedding sensors such as accelerometer, gyroscope, and heart rate sensor. However, these devices have severely limited battery capacity, which requires frequent recharging. Harvesting ambient energy and optimal energy allocation can make wearable IoT devices practical by eliminating the charging requirement. This paper presents a near-optimal runtime energy management technique by considering the harvested energy. The proposed solution maximizes the performance of the wearable device under minimum energy constraints. We show that the results of the proposed algorithm are, on average, within 3% of the optimal solution computed offline.