Environmental Monitoring
Artificial Intelligence
Biodiversity
Deep Learning
Machine Learning
FKZ 02WDG1758
BioDroneAI
Non-Invasive Automatic Multimodal Animal Detection Using Drones and Deep Learning
Duration: November 1, 2025 – October 31, 2027
Consortium:
- Fraunhofer Institute for Energy Economics and Energy System Technology (IEE)
- Office for Applied Ecology and Faunistics - naturkultur GmbH
- Trans Atmospheric Operations GmbH
- University of Kassel (Department of Intelligent Embedded Systems)
Contact Person (Coordinator)
Dr. Christoph Scholz
Fraunhofer Institut für Energiewirtschaft und Energiesystemtechnik (IEE)
Joseph-Beuys-Straße 8
34117 Kassel
What the project is about
The BioDroneAI project uses low-noise LTA-UAV drones and AI-powered technology to make the monitoring of animal populations more comprehensive, efficient, and less disruptive to wildlife. The use of multimodal sensors, including thermal imaging and high-resolution cameras as well as acoustic detection, enables precise and comprehensive species surveys in large and hard-to-reach areas.
BioDroneAI aims to protect biodiversity in sensitive ecosystems such as peatlands and strengthen their role as CO₂ sinks. Automated data collection and analysis are intended to alleviate the shortage of skilled workers in biodiversity monitoring and accelerate planning processes for sustainable energy infrastructure projects. In the long term, BioDroneAI supports species conservation and the achievement of the UN Sustainable Development Goals through an innovative combination of environmental technology, robotics, and artificial intelligence.