Imagine having a smart map that tells you exactly which plants and birds live in an area just by analyzing sounds and photos. It's like a digital nature detective that helps people decide where to build or farm without destroying the environment. By using AI, it turns messy nature data into clear guides for better planning.
Companies struggle to balance infrastructure development with strict biodiversity laws due to a lack of accurate, real-time nature data. This leads to regulatory delays, project costs, and environmental damage.
A suite of Decision Support Applications (DSAs), an open bird sound recognition model (AvesEcho), and an AI-driven vegetation survey tool for multi-species prediction.
If you are a developer dealing with environmental impact assessments for wind or solar farms — this project developed Decision Support Applications (DSAs) that provide high-resolution maps of biodiversity and habitats. This allows you to place infrastructure where it does the least harm to nature.
If you are a farm manager dealing with soil health and crop diversity requirements — this project developed an upgraded Pl@ntNet vegetation survey tool. It uses AI to provide automated multi-species predictions and cover estimates for your land plots.
If you are a construction firm dealing with coastal zoning laws and biodiversity protection — this project developed predictive models of ecosystem status indicators. This helps you navigate local management policies and avoid costly project delays caused by environmental non-compliance.
Based on available project data, no pricing information is provided as the project focuses on open modelling components and research deliverables.
The project demonstrated scalability by deploying tools across 5 case studies in France, Greece, Spain, Cyprus, and Madagascar, and expanding the Pl@ntNet model to 86k species.
The project emphasizes open modelling components and released AvesEcho as an open bird sound recognition model, though specific commercial licenses are not detailed.
It provides policy-relevant indicators and DSAs that help users reshape the policy landscape and make informed decisions across different sectors and scales.
The tools are delivered as developer REST/JSON services and integrated into existing systems like Naturalis' 'Arise' and Xeno-canto.
The consortium is research-heavy with 9 research organizations and 3 universities, but maintains a significant industrial presence with 4 industry partners and 5 SMEs (a 22% industry ratio). This balance suggests the technology is grounded in deep science but has been vetted for practical application by small and medium enterprises across 8 countries.
Contact CIRAD EPIC in France for technical specifications on the DSAs.
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