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

Swapnil Sayan Saha¹, Caden Davis², Sandeep Singh Sandha³

¹STMicroelectronics Inc., Santa Clara, CA 95054, USA (work unrelated to STMicroelectronics Inc.).

IEEE Sensors Journal

|December 6, 2024

Summary

This summary is machine-generated.

LocoMote is a tiny, ultra-low-power undersea sensor tag enabling AI-driven localization and communication. It features energy harvesting and high-resolution sensors for long-term maritime sensing, even with GPS outages.

Keywords:

animal tagging biologging dead reckoning energy harvesting inertial neural networks piezoacoustic sensor tags tinyML underwater

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Area of Science:

Marine technology
Underwater sensor networks
Artificial Intelligence in oceanography

Background:

Maritime localization and sensing face challenges like intermittent connectivity, power limits, and harsh environments.
Existing technologies struggle with long-term, fine-grained underwater data collection.

Purpose of the Study:

To design and implement LocoMote, a rugged, ultra-low-footprint undersea sensor tag.
To enable on-device AI-driven localization, online communication, and energy harvesting for underwater applications.

Main Methods:

Utilized on-chip neural networks (< 30 kB) for AI-driven localization using inertial sensor data.
Implemented piezo-acoustic ultrasonics for underwater data streaming (2-5 kbps) with a 50m+ range.
Integrated an aluminum-air salt water energy harvesting system for battery recharging (up to 5 mW).

Main Results:

Achieved underwater object tracking within 3 meters during ~6 minutes of GPS outage.
Enabled concurrent data streaming from up to 55 nodes using randomized time-division multiple access.
Developed an ultra-lightweight (< 50g), compact tag with low power consumption (~330 mW peak).

Conclusions:

LocoMote offers a viable solution for long-term, fine-grained maritime localization and sensing.
The tag's integrated AI, communication, and energy harvesting address key limitations of current underwater technologies.
Demonstrated real-world performance superior to existing oceanic sensing technologies.