AI4Nature Project
Key Facts
Acronym: AI4Nature
Title: Artificial Intelligence for Environmental Risk and Biodiversity Restoration
Duration: 24 months
Program: PN Research, Innovation and Competitiveness 2021–2027
Reference Actions:
Action 1.1.2 – Support for strategic research supply chains
Action 1.1.3B – Validation and networking of research clusters
Action 1.4.3 – Strengthening competencies for the innovation ecosystem
Lead Organization: National Biodiversity Future Center
Co-proposer: Fondazione FAIR
Partners: 17 among universities, research centers, and companies
Total Budget: €8,997,880.77 (combined across the three actions)
Application Areas:
- Environmental monitoring
- Climate risk management
- Biodiversity conservation and restoration
Target Regions: Focus on Less Developed Regions (Basilicata, Calabria, Campania, Molise, Puglia, Sardinia, Sicily)
Description
The AI4Nature project — Artificial Intelligence for Environmental Risk and Biodiversity Restoration* — is an industrial research and experimental development initiative funded under the National Program “Research, Innovation and Competitiveness for the Green and Digital Transition 2021–2027”, with the goal of developing advanced Artificial Intelligence solutions for the analysis and management of environmental risks and to support biodiversity protection strategies.
The project, promoted by Fondazione NBFC in collaboration with Fondazione FAIR, fits within the framework of national and European policies for the ecological transition, fostering the integration of advanced digital technologies and environmental sciences. In particular, AI4Nature develops innovative tools for ecosystem monitoring, the forecasting of complex environmental phenomena, and sustainable land management.
Through a broad, multidisciplinary partnership, the project combines scientific and industrial expertise to address critical challenges related to climate change, biodiversity loss, and ecosystem resilience, with a specific focus on the regions of Southern Italy.
Project activities are organized around three main areas:
- Environmental monitoring and analysis: Development of artificial intelligence models for the analysis of complex environmental data and risk assessment
- Risk management and resilience: Predictive tools for the prevention and mitigation of environmental impacts
- Biodiversity restoration: Support for conservation and ecosystem regeneration strategies
The overarching goal is to strengthen research and innovation supply chains in less developed regions, fostering technology transfer and the adoption of advanced solutions in real operational contexts.