29 Jul AI early warning system aims to speed up forest fire detection

An AI-supported early warning system designed to detect forest fires at the earliest possible stage is being tested under real-world conditions in Germany as part of the SmartForestFire project.

The technology combines AI-powered image analysis, environmental sensors and wireless communications to identify smoke and potential fire hazards before they develop into larger incidents. The system is currently undergoing trials in the Tennenloh Forest near Erlangen.

Developed by the Fraunhofer Institute for Integrated Circuits IIS and the Fraunhofer Institute for Material Flow and Logistics IML as part of the Fraunhofer Cluster for Cognitive Technologies CCIT, the project also brings together emergency services, forestry organisations and public authorities.

At the centre of the system are specially trained multi-stage AI models that analyse camera images to detect smoke while distinguishing it from clouds, fog and dust. By combining image data with sensor readings and geospatial information, the project aims to improve detection accuracy while significantly reducing false alarms.

Data from cameras and sensors is transmitted using the mioty® low-power wide-area wireless technology, enabling reliable communications even where existing infrastructure is unavailable or disrupted. A central visualisation platform then provides emergency responders with live information, including image sequences, location data, weather conditions, forest status and accessibility to support incident assessment and operational planning.

The project is also evaluating radio-based positioning of sensors and plans to expand the monitoring network with additional devices measuring factors including air and soil moisture, temperature and CO₂ to further enhance situational awareness.

According to Tobias Raczok, Research Associate at Fraunhofer IIS and SmartForestFire Project Coordinator, the system relies on the combination of AI-based image analysis, sensor technology, resilient radio communications and operational expertise to deliver reliable and cost-effective early fire detection.

Initial testing has already demonstrated reliable detection of smoke during its earliest stages. Once the internal testing phase is complete, potential forest fires will be reported automatically to emergency services and the Nuremberg Integrated Control Centre.