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AI is already a part of our everyday life. If we want to find the cheapest connection to the workplace in the morning, AI can do it for us. However, what seems easy to operate for the user is complicated to set up below the surface. It’s not only about programming an algorithm but also about integrating it into a productive environment. AI needs to be considered as part of a whole framework of technology and processes that are finally geared at the customer benefit. In this panel, we focus on the role of AI in mobility and future urban planning. Be it better customer information on the punctuality of local trains, the prediction of future mobility demand in cities, energy efficiency or the protection of people against crime and harassment in public transport. The analytics of historic and actual data, combined with machine learning, open up new opportunities for satisfying the needs of an ever more mobile society.
/ Current opportunities and limits of AI
/ Use cases from prognostics, edge computing, and predictive maintenance
/ Smart city and mobility scenarios