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AI4Nature Project

Artificial Intelligence for Environmental Risk and Biodiversity Restoration

Programme: PON Research and Innovation 2021–2027

Reference Actions

Action 1.1.2 – Support for Strategic Research Value Chains
Action 1.1.3B – Validation and Networking of Research Aggregations
Action 1.4.3 – Strengthening Skills for the Innovation Ecosystem

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)

Key Facts

Lead Partner: National Biodiversity Future Center
Co-Proponent: FAIR Foundation
Partners: 17 universities, research centres, and companies
Total Budget: €8,997,880.77 (overall across the three actions)

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.

Project Partners