LTO BATTERY USEFUL LIFE PREDICTION FOR ALWAYS ON EDGE AIoT BASED STRUCTURAL HEALTH MONITORING

Although many high-sampling sensor systems tend to be power-hungry, critical monitoring applications require reliable battery-powered sensor nodes that can retrieve and compute data on the edge for years. With the advent of Tiny Machine Learning (TinyML), it is becoming increasingly feasible to deploy always-on inference Machine Learning models on constrained battery-powered microcontrollerbased nodes. However, owing to unpredictable and dynamic energy harvesting availability conditions and the limitations of battery technology, long-term operation is still challenging.

In this paper, we present a hardware and software solution for long term continuous solar operation of power-hungry wireless sensor nodes with Lithium titanate oxide (LTO) batteries.