From AI-Based Image Recognition to Next-Generation Reef Monitoring

The CORA(i)L project proposes an automatic and non-invasive detection of coral reef health through image analysis using Artificial Intelligence. Part of the project aims to determine the feasibility of real-time reef monitoring by local populations and tourists in the affected regions.

CORA(i)L will combine interdisciplinary approaches to:

  1. Assess the physiological significance of these attributes using multi-omic data from long-term monitoring studies.
  2. Extract photos of coral colonies from long-term photogrammetric studies, which will be used by AI systems to determine health-related attributes.
  3. Determine if affordable, non-invasive images of coral colonies and AI analyses can be used as substitutes for assessing the health of coral reefs.

The development of non-invasive photography and AI-based approaches with accessible equipment will enable the deployment of these tools within local communities to monitor corals and evaluate the benefits of management and/or restoration projects.


Project Leaders :

Eric GILSON and Eric RÖTTINGER (IRCAN)
 

Project Partners:

IRCAN (Eric Gilson, Eric Rottinger)

MSI - Center of Modeling, Simulation and Interactions (Marco Milanesio)

ITCA  (Vincent Tricard, Jean-Cristophe Gay)

CRIOBE (Letitia Hedouin)

UNIPA - State University of Papua (Selvi Tebay)

UNUD – Udayana University (Gede Hendrawan, Nyoman Sunarta)

Foundations and NGO:

Misool Foundation. Sorong, Indonesia

Kahi Kai. Eze, France

CTC - Coral Triangle Center. Bali, Indonesia