Speaker
Description
In this talk, we propose to discuss the Smarter Mobility Data Challenge organised by the AI Manifesto, a French business network promoting AI in industry, and TAILOR, a European project aiming to provide the scientific foundations for trustworthy AI. The challenge required participants to test statistical and machine learning prediction models to predict the statuses of a set of electric vehicle (EV) charging stations in the city of Paris, at different geographical resolutions. The competition attracted 165 unique registrations, with 28 teams submitting a solution and 8 teams successfully reaching the final stage. After providing an overview of the context of electric mobility and the importance of predicting the occupancy of a charging station for smart charging applications, we describe the structure of the competition and the winning solutions.
| Classification | Both methodology and application |
|---|---|
| Keywords | Data Challenge, Machine Learning, Forecasting, Smart Charging, AI Manifesto |