AI-Powered Oceanographic Data Analysis

Goal: The project aimed to evaluate the feasibility of using Large Language Models (LLMs) to enhance hydrographic data processing, leveraging Bluemvmt’s BlueAI platform to optimize the ingestion, analysis, and interpretation of sonar and lidar data.

Problem:

Traditional hydrographic data analysis is slow, manual, and inefficient, making real-time insights difficult. NAVOCEANO needed a solution that could:

• Process complex sonar (GSF) and bathymetric lidar (LAS) data efficiently

• Automate anomaly detection and feature identification

• Enable real-time SME interaction for AI model training

Solution:

BathyAI leverages the platform to:

• Automate data ingestion – Converts raw GSF/LAS files into AI-ready formats for real-time analysis.

• Enhance AI-driven analytics – Detects navigation hazards, shipwrecks, and seafloor features with superior accuracy.

• Enable real-time SME collaboration – Provides a conversational AI interface for interactive feedback and model tuning.

• Scale with secure AI architecture – Integrates MLFlow, LangChain, and cloud-based data pipelines for future adaptability.

Details:

• Data processing time reduced from days to minutes

• Greater accuracy in sonar and lidar data interpretation

• AI-powered insights streamline oceanographic operations

• Lays the foundation for OceanGPT, a next-gen AI model for marine research