just better DATA
Efficient and highly accurate data generation for AI applications in autonomous driving
Start: 10.2024
End: 09.2027
The energy transition presents electricity grid operators with significant challenges, mainly due to the large-scale integration of PV systems, battery storage systems, heat pumps, and charging infrastructure into the electricity distribution grid. Digital twins of electricity grids can help to overcome these challenges.
In the AMAZING project funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK), the FZI investigates AI-based processes that derive and calibrate highly automated digital twins of electricity grids from various data sources of the electricity grid operators. The practical added value of the generated digital twins is being tested using several energy industry use cases and implemented at the five electricity grid operators involved in the project. This will ensure the practical relevance of the project results for future digitalized electricity grid operations. At the same time, the research results can be demonstrated in practice and used as a blueprint for widespread use.
This research focus includes the research and design of sustainable IT innovations in the cross-sectional areas of energy, mobility, production, water management, and logistics. This involves developing systems that promote the ecologically, socially, and economically sustainable use of resources, and providing strategic consultancy services to companies, particularly SMEs, on their path to greater sustainability.
In this research focus, the FZI concentrates on practical research into the key technology of Artificial Intelligence (AI). Innovative AI solutions are developed and transferred to application areas such as mobility, robotics, healthcare technology, logistics, production, and supply and disposal on behalf of our partners and customers.
Funding notice:
The AMAZING project is funded by the Federal Ministry for Economic Affairs and Energy
Project partners:
Efficient and highly accurate data generation for AI applications in autonomous driving
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