Controlling forest fires with technology

We combine drones, artificial intelligence and decision support systems to increase resilience and coordinate the deployment of security authorities in the event of forest fires.

KIWA, "KI-basierte Waldüberwachung" (‘AI-based forest monitoring’), offers municipalities and regions the opportunity to recognise fires in monitored forest areas at an early stage and coordinate local task forces based on real-time data.

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An image of a drone flying over an area affected by a wildfire

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The Challenges

Our Approach

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Drones

The BMUV-funded project is investigating the use of unmanned drones to assess the situation of forest and wildfires. Drones are equipped with cameras to identify fires. The recorded images and videos are transmitted via interfaces and analysed using artificial intelligence.

Mockup of the AI of KIWA identifying fire & smoke

Artificial intelligence

By using artificial intelligence, the drone images can be analysed in real time. This means that even fast-spreading forest fires can be responded to quickly and accurately.

Decision Support

The KIWA project is trialling the use of decision support systems for fire brigades and disaster control authorities, which are based on the current situation and the forecasts of artificial intelligence.

Research Questions

1

How accurate are forest fire risk predictions using artificial intelligence, remote sensing data and climate models?

2

How effective are drones at monitoring and mapping areas affected by wildfires?

3

How well can decision support systems help improve response to wildfire threats?

Our Value Proposition

Ensuring Information and decision-making

Through real-time monitoring and precise early detection of forest fires using artificial intelligence, we want to support municipalities and regions to act proactively and minimise the impact of fires.

Enhanced safety

We prioritise the safety of people, animals, infrastructure and nature in and around forest areas. The early detection of forest fires should help to save lives and organise the safe evacuation of endangered areas and promote the resilience of the community and region.

Promoting sustainability

Early detection and control of forest fires helps to reduce ecological damage and preserve forests. Through the use of forecasting and decision support systems, existing resources can be used more sustainably.

Economic efficiency through innovation

Fighting forest fires is expensive, both in terms of the ecological consequences and the financial burden on municipalities and regions. Through early detection and precise early intervention, the ecological consequences and financial costs can be minimise

Efficient use of resources

Our AI technology supports you in precisely locating sources of fire and predicting their spread. In this way, resources for firefighting can be used more effectively and valuable time can be saved.

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Latest Updates

Graphic Summarising the features of the KIWA Projekt

Jun 2024

Useful use of AI in forest fire monitoring

The [ui!] employees Tobias Heuser and Karim Gari have dedicated themselves to the topic: "KIWA – AI-based forest monitoring: making forest fires in Germany even more manageable".

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