Data- and AI-supported early warning system
December 2021 – November 2024
This project was funded by the Federal Ministry for Economic Affairs and Climate Action on the basis of a decision by the German Bundestag
The aim of DAKI-FWS is to produce an early warning system based on various data sources and leveraging novel methods (including artificial intelligence), which will strengthen economic resilience in Germany. The early warning system (EWS) will integrate key data sources but remain modular, allowing different sectors to use the system to mitigate the impacts of hazards.
For DAKI-FWS, industry and science combine forces to derive and process warnings for economic purposes. The potential applications and the dimensions of such an early warning system are enormous. For instance, SMEs are partnering with university and non-university research institutions to develop a generic model (including a data and analysis platform) to manage hazards such as epidemics/pandemics, floods, windstorms, and heat waves. In addition, the consortium (particularly, the industrial partners) will demonstrate the impact and usability of the technology for selected industries and entrepreneurial value chains in the form of service interfaces. Thanks to its modular structure, the early warning system can be used in different sectors and can provide insight into hazard-related processes and impacts (e.g., seasonal effects on agriculture and any resulting long-term damage). Another beneficial feature is the transnational scalability, which supports future and ongoing European developments.
The EWS provides economic, political, and administrative decision-makers and the general public with critical information during a disaster and, thanks to its user-friendly interface, it encourages everyone to gain founded knowledge about an ongoing crises and their possible impacts. This increases anticipatory planning, which can result in greater resilience. The beneficiaries of this technology are highly diverse (e.g., companies, associations, counties, cities, and countries). In particular, small organizational units or associations will appreciate that this tool can be applied without having to disclose internal processes and strategies.
- Fraunhofer HHI (Konsortialführung)
- HANZA Tech Solutions GmbH
- Charité - Universitätsmedizin Berlin
- D4L - data4life gGmbH
- Justus-Liebig-Universität Gießen
- Logiball GmbH
- NET CHECK GmbH
- Robert Koch-Institut
- Zuse Institut Berlin