LocoMote: AI-driven Sensor Tags for Fine-Grained Undersea Localization and Sensing.

Long-term and fine-grained maritime localization and sensing is challenging due to sporadic connectivity, constrained power budget, limited footprint, and hostile environment. In this paper, we present the design considerations and implementation of , a rugged ultra-low-footprint undersea sensor tag with on-device AI-driven localization, online communication, and energy-harvesting capabilities. uses on-chip (< 30 kB) neural networks to track underwater objects within 3 meters with ~6 minutes of GPS outage from 9DoF inertial sensor readings. The tag streams data at 2-5 kbps (< 10 bit error rate) using piezo-acoustic ultrasonics, achieving underwater communication range of more than 50 meters while allowing up to 55 nodes to concurrently stream via randomized time-division multiple access. To recharge the battery during sleep, the tag uses an aluminum-air salt water energy harvesting system, generating upto 5 mW of power. is ultra-lightweight (< 50 grams), tiny (32×32×10 mm), consumes low power (~ 330 mW peak), and comes with a suite of high-resolution sensors. We highlight the hardware and software design decisions, implementation lessons, and the real-world performance of our tag versus existing oceanic sensing technologies.