PRIME is a project conceived and led by Ud’Anet within the National Biodiversity Future Center (NBFC), with the goal of bringing technological innovation to the service of environmental protection and biodiversity.
The initiative addresses one of the most urgent challenges of our time: monitoring, protecting, and enhancing natural ecosystems, with a particular focus on the protected marine and terrestrial areas of the central Adriatic—fragile territories of significant ecological and cultural value.
At the core of the project is a fleet of autonomous mobile robots (AMRs), equipped with an advanced set of sensors, including high-resolution cameras, multispectral and infrared sensors, as well as acoustic and environmental instruments for detecting wildlife, vegetation, pollution levels, and signs of human activity.
These robotic systems operate in synergy with a network of IoT sensors distributed across the ტერიტორი, creating a technological ecosystem capable of collecting complex, multidimensional data continuously, accurately, and at scale.
The collected data is not merely stored—it is processed using artificial intelligence algorithms and machine learning models to generate predictive insights on ecosystem health and the evolution of environmental risks such as erosion, wildfires, pollution, and habitat loss.
All information is made available as open data, accessible through cloud platforms, interactive dashboards, and dynamic GIS maps, supporting scientists, protected area managers, and policymakers in their conservation and enhancement strategies.
As project lead, Ud’Anet designed, developed, and implemented the entire PRIME system, combining technological expertise with strategic vision.
Key activities included:
Development and programming of the AMR robotic platform;
Integration of advanced sensor systems;
Design of AI and machine learning algorithms for data analysis;
Development of the cloud platform and visualization dashboards;
Creation of a dedicated mobile app to engage local communities and support participatory data collection (citizen science);
Overall project coordination, including risk management, scientific supervision, and dissemination of results in line with FAIR principles (Findable, Accessible, Interoperable, Reusable).