Data and AI-supported early warning system to stabilise the German economy
The DAKI-EWS consortium project
...(data and AI-supported early warning system for stabilising the German economy) has set itself the goal of using AI technologies to link and evaluate data from different data sources. Based on this data, an early warning system is to be developed that can be used in future crisis situations such as a pandemic or a natural disaster to better describe the development and course. In addition, the impact of crises on economic aspects is to be better assessed. DAKI-FWS is part of the "KI Innovation Competition" of the Federal Ministry for Economic Affairs and Energy (BMWi) and is funded with approx. 12 million euros. DAKI-FWS started at the beginning of December 2021 and will run for three years.
In the DAKI-EWS project, researchers are developing new intelligent methods by combining crisis-specific data with socially relevant data (e.g. mobile phone data, traffic data, meteorological data). In this way, an AI-supported early warning system is to be developed to detect pandemic outbreaks and climate extremes such as floods, storms and heat waves at an early stage and to predict their course more accurately. Due to the more comprehensive data, experts are better able to make appropriate economic decisions. For example, value chains can be maintained for longer. Such an early warning system can be applied in almost all sectors (logistics, food supply, sales, services, agriculture, groundwater and drinking water management, etc.) and thus strengthen the resilience of the entire German economy.
The aim of the sub-project "EWS Application - Logistics in SMEs" submitted by LOGIBALL is to develop alerting and optimisation services for logistics systems, especially for SMEs, based on warnings from the DAKI EWS. By mapping the warnings of the DAKI EWS to specific risks and consequences for the logistics domain, SMEs with logistics chains receive innovative added value, as not only access to a "digital situation centre" is offered, but concrete and, if necessary, automated recommendations for action are possible down to the operational level of the logistics software used.
In addition to LOGIBALL, Budelmann Elektronik GmbH, Charité - Universitätsmedizin Berlin, D4L - data4life gGmbH, the Fraunhofer Heinrich Hertz Institute, the Hasso Plattner Institute for Digital Engineering, Justus Liebig University Giessen, NET CHECK GmbH, the Robert Koch Institute, the Zuse Institute Berlin and, as subcontractors, the German Climate Computing Centre and Esri Deutschland GmbH are involved. Other associated partners are the Association of German Chambers of Industry and Commerce, Here Technologies, Schönborner Armaturen, the Hessian Agency for Nature Conservation, Environment and Geology and the German Weather Service.
|?||Can AI solve the update problem of digital environmental models|
|?||What can AI, in whatever form, reveal about location data – lanes, lowered kerbs, parking zones, drop-off zones, etc.|
|?||Can AI create content for the virtual world, and in doing so massively reduce costs and accelerate processes for training and testing|
|?||Can AI construct navigation maps by itself from many different data streams, and do it for all roads worldwide|
|?||Can AI detect errors in location data faster than any person and existing processes|
|?||Can AI solve dispatching problems quicker and in a more holistic way|
|?||Can we create a universal AI system which knows the answer to any question regarding whereabouts|
|?||Will Google be replaced by an omniscient location intelligence system|
There are many questions and many answers which we are addressing within our research department.
It goes without saying that we will also find the right answers for you. Come and talk to us.