TelematiQ

TelematiQ is a collaborative R&D project developing an AI-powered, interoperable platform that transforms heterogeneous mobility data into real-time, simulation-ready intelligence. The initiative bridges the gap between data fusion, analytics, and digital-twin simulation, enabling safer, cleaner, and more efficient mobility systems aligned with emerging global AI regulations such as the EU AI Act and GDPR. TelematiQ integrates multi-source mobility data—from telematics, cameras, IoT sensors, and geospatial imagery—into a unified fusion layer that continuously updates high-fidelity digital twins of real-world environments. The system employs advanced deep-learning architectures for multi-level feature fusion, anomaly detection, and spatio-temporal reasoning, generating predictive insights for risk, safety, and efficiency. These outputs are automatically transformed into simulation scenarios (OpenDRIVE/OpenSCENARIO) for ADAS, autonomous driving, and urban mobility testing, supported by a federated governance framework ensuring transparency and compliance. The project aims to deliver an end-to-end ecosystem connecting data producers, AI analytics, and simulation platforms—accelerating the adoption of trustworthy, data-driven mobility technologies and setting the foundation for next-generation intelligent transport systems.