Extreme weather events such as heavy rain and heatwaves are becoming increasingly frequent and severe in Germany - this also poses new challenges for the rescue services. The AIRCIS project aims to remedy this situation by producing forecasts that take into account various weather conditions and thus make rescue operations more efficient and easier to plan.
Climate change is making more frequent extreme weather events likely in Germany. At the same time, there are fewer resources available in many areas of the emergency services - for example, there has been an extreme shortage of personnel for years. Under these circumstances, it is very important to be able to train and plan operations as precisely as possible in order to optimise the use of available resources.
Control centres are already collecting data from many operations. This can be helpful in making forecasts for future rescue operations. This allows capacities and resources to be planned more precisely - for example, for extreme weather conditions. This is precisely where our AIRCIS project comes in: Firstly, data already collected from control centres as well as weather and geographical data are evaluated. Based on this, a model is being developed for which an AI algorithm will be used to make precise forecasts of how rescue chains can run under the respective circumstances.
Subsequently, a dynamic simulation is designed that can be used to map forecasts for the development of use in the area under investigation.
At the end of the project, incident commanders and control centre dispatchers will have decision-making aids for operations displayed in their system. To this end, special software is being developed for use in the control centre for forecasting and planning operations.
The AIRCIS research project, led by the Björn Steiger Stiftung, is being funded by the Federal Ministry for Digital and Transport with around 2.98 million euros over the next three years until the end of 2025 as part of the mFUND innovation initiative. AIRCIS is being tested as an example for the model region of Lusatia.
More at https://aircis.de
