Indigma AI Presents Research on Privacy-Preserving EV Demand Prediction at IWAPS Workshop (ARES Conference)
Indigma, winner of the O-CEI Horizon 1st Open Call, will present the paper “Federated Learning for Electric Vehicle Energy Demand Prediction Across Distributed Users,” at the International Workshop on Advances on Security and Privacy Technologies and Solutions (IWAPS), held in conjunction with the International Conference on Availability, Reliability and Security (ARES).
This work directly builds upon Indigma’s ARIEL initiative (federAted oRchestration In Ev fLeets) within O-CEI Pilot 3, demonstrating how Edge AI and Federated Learning can enable smart, privacy-preserving energy management for large-scale electric vehicle (EV) fleets without centralizing sensitive operational data. By keeping raw telemetry localized at fleet depots and charging stations, while sharing only trained model parameters, Indigma’s work provides a trustworthy, scalable, and privacy-first foundation for European smart grid management and logistics fleets.
