AI4REALNET
AI for REAL-world NETwork operation
Project Description
Artificial intelligence (AI) can be a powerful tool in the management of critical systems that have traditionally been under human control. The EU-funded AI4REALNET project will develop methods to prioritise trustworthiness in AI-assisted human control, incorporating augmented cognition, hybrid human-AI co-learning, and autonomous AI, all while maintaining a focus on the resilience, safety, and security of critical infrastructures. The project will also expedite the development and validation of new AI algorithms by the consortium and the broader AI community. It will do this by leveraging open-source AI-friendly digital environments capable of simulating realistic scenarios involving the operation of physical systems and human decision-making. Finally, AI4REALNET will contribute to addressing the critical aspects of decarbonisation, digitalisation, and resilience.
Our Role
Within the framework of the AI4REALNET project, we contribute by leading the project’s economic analysis through the use of a proprietary Cost–Benefit Analysis model and its application across the three specific AI4REALNET domains (Railway, Power Grid, and ATM).
Observatories involved: Artificial Intelligence Observatory
Consortium
INESC TEC (coordinator), Flatland, SBB Swiss Federal Railways, University of Applied Sciences and Arts Northwestern Switzerland, Zurich University of Applied Sciences, NAV Portugal, Digitale Schiene Deutschland, Tennet, RTE France, EnliteAI, Linköping University, TU Delft, University of Amsterdam, Politecnico di Milano, University of Kassel, Fraunhofer IEE, IRT SystemX
Status
Ongoing
Project website
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