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Project | AI-REEFSHIELD

Duration:
Al-driven Robotic Ecosystem Exploration Framework for Securing Habitat Integrity and Life Diversity

Al-driven Robotic Ecosystem Exploration Framework for Securing Habitat Integrity and Life Diversity

The AI-REEFSHIELD project aims to develop an AI-supported learning and robotics system for monitoring marine restoration areas, in particular for the reintroduction of the European oyster in the North Sea. An autonomous underwater vehicle (AUV) equipped with high-performance cameras and AI algorithms will be used to map large reef areas precisely, efficiently, and with less human intervention. This will replace the previous cost- and emission-intensive monitoring methods. The innovative approach includes an explainable active vision approach for targeted autonomous monitoring, combining machine vision, reinforcement learning, explainable AI (XAI), and model-based learning methods. In addition to environmental and climate protection goals, the project also aims to improve biodiversity monitoring. The system will be validated in the pilot area of the oyster reefs in the Borkum Riffgrund nature reserve and should be transferable to other environmental applications.

Partners

Universität Bremen

Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung

Contact Person

Dr.-Ing. Rebecca Adam Dr.-Ing. Bilal Wehbe

Funding Authorities

BMUV - Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection

67KIA4036A

BMUV - Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection