Distributed Multi-Modal Traffic Monitoring with 6G Networks: from Compression to Semantics

Research Project, 2025 – 2026

The advent of 6G communication systems offers unprecedented capabilities in urban traffic management. However, the integration of vast amounts of sensory data into the 6G framework presents significant challenges, primarily due to the sheer volume of data generated by sensors. This issue is compounded by the necessity for higher levels of data compression for automated systems, like traffic control, without compromising performance or system integrity. The field of semantic communication1, leveraging artificial intelligence, presents a promising solution to efficiently handle, compress, and interpret this sensory data.

This project aims to bridge the expertise of specialists in transportation, distributed sensing, and 6G communication to pioneer semantic distributed processing tailored for transportation performance metrics. The core objectives are to develop innovative integration and compression techniques for diverse sensing technologies (6G sensing, cameras, and radars) and to tailor semantic optimization techniques for 6G systems. These advancements are expected to prioritize and enhance transportation metrics, including real-time traffic management, predictive maintenance, and safety, moving beyond traditional communication
performance indicators.

The intended beneficiaries of this project are (i) urban planners and traffic management authorities seeking to employ advanced 6G capabilities for enhanced traffic efficiency and safety; (ii) 6G communication industry, which can integrate methods in the edge and core networks.