AI for Development and Sustainability
Research involving artificial intelligence and digital technology for sustainable development, conducted by IRD and its partners.
- Agriculture
- Great Green Wall
- Sustainability
- Agroecology
- Appropriation
- Soil degradation
- Carbon sequestration
- Nutrition
- Aquaculture
- Dilemmas
- Agriculture de précision
- Biais algorithmiques
- Diagnostic médical assisté par IA
- Épidémiologie & modélisation des maladies
- Éthique & Gouvernance de l’IA
- Gestion durable des sols
- IA & Agriculture durable
- IA & Biodiversité
- IA & Climat
- IA & Gestion de l’eau
- IA & Partenariats Sud-Sud / Sud-Nord
- IA & Santé
- IA au service des ODD
- IA pour le développement durable
- Modélisation climatique
- Prévention des risques climatiques
- Prévision des ressources hydriques
- Qualité de l’eau
- Renforcement des capacités locales
- Souveraineté des données
- Télédétection & IA
- Transfert technologique
- Grant agreement
- Scientific article
- Project
- Research project
- Best practice
FISH-PREDICT: generating ecological indicators and predictive models of biodiversity
FISH-PREDICT: generating ecological indicators and predictive models of biodiversity
This project aims to generate ecological indicators and predictive models of biodiversity in disturbed ecosystems by combining artificial intelligence methods with known assessment approaches. It will thus enable the creation of the first marine biodiversity knowledge base and, subsequently, the development of prediction and interpretation models. It also aims to reveal intelligent solutions for nature in order to ensure the sustainability of coastal socio-ecological systems.
marine biotechnology, marine ecology, biological oceanography
IA et aménagement du territoire pour des écosystèmes socio-écologiques durables
IA et aménagement du territoire pour des écosystèmes socio-écologiques durables
There is an important gap between biodiversity research and the management of natural areas. This research project aims to reduce this gap by proposing spatial planning methods that robustly and accurately integrate socio-ecological issues. Artificial intelligence will play a central role and will make it possible to remove the methodological obstacles that prevent us from properly addressing the complexity and heterogeneity of sustainability issues in the management of ecosystems.
DIG-AI or "Decrypting plant genotype-phenotype interactions using knowledge graphs and AI"
DIG-AI or "Decrypting plant genotype-phenotype interactions using knowledge graphs and AI"
EARLI : de l’IA pour prévoir tsunamis et séismes
EARLI : de l’IA pour prévoir tsunamis et séismes
"The rise of machine learning allows us to consider a completely different approach, without any physical assumptions, based solely on empirical data. The idea is to feed the algorithms with all the quantitative observations of natural phenomena that we can muster, to see if they can identify factors that have so far escaped the attention of specialists."
AIME : L'IA au service des indicateurs de biodiversité marine
AIME : L'IA au service des indicateurs de biodiversité marine
The AIME project utilises artificial intelligence to integrate heterogeneous data — satellite imagery, underwater images and videos, environmental DNA, GPS coordinates and telemetry — and to produce marine biodiversity indicators at different scales. The methods combine deep learning, ontologies and knowledge bases, natural language processing, machine learning and dynamic Bayesian networks, with a hybridisation of symbolic and sub-symbolic approaches aimed at enhancing the robustness and accuracy of the indicators.
marine biology, bioindicators, oceanography, artificial intelligence
LMI IDEAL: Artificial intelligence, data analysis and Earth observation applied to the sustainability laboratory
LMI IDEAL: Artificial intelligence, data analysis and Earth observation applied to the sustainability laboratory
IDEAL is a joint international laboratory comprising IRD, UFPB and other research institutions in north-eastern Brazil. We focus on transdisciplinary research, linking agroecology, artificial intelligence and social sciences to develop pathways for transition towards socio-ecological co-viability. We also support governance and education projects, with integrative approaches aimed at ecological restoration, social inclusion and bioeconomies.
ELDORA project: artificial intelligence to optimise the prevention of sudden cardiac arrest
Led by a multidisciplinary team involving IRD, Sorbonne University and AP-HP, the ELDORA project aims to transform sudden death prevention. Its main objective is to develop artificial intelligence models applied to electrocardiograms (ECGs) in order to better identify the risks associated with long QT syndrome (LQTS) and myocarditis induced by immune checkpoint inhibitors (ICIs).
AI and cameras to count deep-sea fish
AI and cameras to count deep-sea fish
The management of snapper stocks is key to the sustainability of New Caledonia's fisheries. To assess their abundance and diversity, scientists from the IRD and their partners have deployed baited stereo cameras on the seamounts where these fish live, at depths of between 47 and 557 metres. Artificial intelligence then takes over to analyse the hours of recorded video.
feed resources, agricultural economics, biological oceanography, fisheries
Implementation of Peru's earthquake early warning system
Implementation of Peru's earthquake early warning system
On 19 May 2025 in Cañete, Peru, the sirens sounded even before the tremors: a first for the country. This early-warning system, designed by the IRD and the Instituto Geofísico del Perú, uses just a single seismic station — as soon as the first seismic waves are detected, AI algorithms estimate the magnitude and location within seconds, then issue an automatic alert. Just a few seconds, but enough time to get out of a building or reach a safe area, and thus to save lives.
ABOUT THE GT AI
The "Groupe de Travail sur l'IA" and Digital Technology, launched in 2025, is a forum for discussion and reflexion on collaborative research related to artificial intelligence, digital technology, and associated data. This research may focus on the development of these objects themselves (in connection with CSS5), their use (across all IRD scientific fields), or their impact on society.
Bringing together scientists from all IRD departments and from various thematics, the GT IA aims to identify research to be promoted on these subjects, but also to organize meetings and events on research related to digital objects. Finally, the GT is a forum for identifying future thematic fields related to digital technology on which the IRD should work, in collaboration with the CSS5 and the various scientific departments.
ABOUT THIS SITE
This site allows us to:
- provide news about the community,
- raise awareness of our actions and our roadmap,
- map and share interdisciplinary projects related to digital technology and AI issues,
- open up to broader contributions from scientists
Our publication process
We would like to publish some of your work on the COSAV digital platform; if you are interested, you can send the document or link via the contact form below.
The published documents are related to the following themes:
- Governance
- Inclusion
- Security and human rights
- Mediation and conflict management
- Resilience
These resources can be of various types: reports or studies (technical, academic), journal articles, short notes or policy briefs, conference proceedings.
We give priority to recent resources (from 2010 to the present), but we are happy to extend our search to older resources according to the needs and suggestions of users and the relevance of certain resources.
Upon receipt of the documents, the platform administrator updates the document base.
For each document:
- He/she ensures that he/she has the publication rights and, if necessary, a formal request for authorization is sent to the owner of the rights to the document
- Once the rights have been obtained, the document is registered on the digital platform
- The indexing process is carried out by identifying the appropriate keywords and classification categories (themes, types and geographical areas)
- The document is put online.
Do not hesitate to let us know about any problem, we are in a continuous improvement process!
The COSAV Team