Terracorder: Sense Long and Prosper
This addresses power efficiency for long-term biodiversity monitoring in remote environments, though it is incremental as it builds on existing scheduling methods.
The paper tackles the problem of power consumption in remote sensing devices by introducing Terracorder, a multi-sensor device with an on-device reinforcement learning scheduler, which captures over 80% of events using less than 50% of activations compared to the best fixed schedule.
In-situ sensing devices need to be deployed in remote environments for long periods of time; minimizing their power consumption is vital for maximising both their operational lifetime and coverage. We introduce Terracorder -- a versatile multi-sensor device -- and showcase its exceptionally low power consumption using an on-device reinforcement learning scheduler. We prototype a unique device setup for biodiversity monitoring and compare its battery life using our scheduler against a number of fixed schedules; the scheduler captures more than 80% of events at less than 50% of the number of activations of the best-performing fixed schedule. We then explore how a collaborative scheduler can maximise the useful operation of a network of devices, improving overall network power consumption and robustness.