NEC develops underwater acoustic AI model for sonar analysis

TOKYO — NEC Corporation in Tokyo, Japan, is developing an AI foundation model for underwater acoustics that could help defense and maritime users analyze large volumes of sonar and hydrophone data without relying on extensive labeled datasets.

Japan's Agency for Defense Equipment awarded NEC the research contract through its Defense Innovation Science and Technology Institute. The project falls under the agency's Innovative Breakthrough Research program and focuses on technology with both defense and commercial applications.

NEC plans to complete the foundation model by fiscal 2027. The company wants to build a general-purpose system that can learn from large datasets and support various analysis tasks, rather than training a separate AI model for each application.

The approach applies some of the principles behind large language models (LLMs) to underwater sound. Instead of learning patterns across large collections of text, the model will learn patterns and relationships within acoustic data.

Underwater sensing creates a different AI problem

Sound plays an important role in underwater sensing because light and radio-frequency signals do not travel through water as effectively over useful distances. Sonar systems and hydrophones can instead collect acoustic signals that carry information about objects, activity and environmental conditions below the surface.