Smart City Intersections: Intelligence Nodes for Future Metropolises
It addresses traffic management and privacy concerns in urban environments, but is incremental as it builds on existing edge-computing paradigms.
This paper tackles the problem of deploying computing and intelligence services at traffic intersections for smart cities, focusing on high-bandwidth, low-latency applications, and presents experimental results from the COSMOS testbed in New York City.
Traffic intersections are the most suitable locations for the deployment of computing, communications, and intelligence services for smart cities of the future. The abundance of data to be collected and processed, in combination with privacy and security concerns, motivates the use of the edge-computing paradigm which aligns well with physical intersections in metropolises. This paper focuses on high-bandwidth, low-latency applications, and in that context it describes: (i) system design considerations for smart city intersection intelligence nodes; (ii) key technological components including sensors, networking, edge computing, low latency design, and AI-based intelligence; and (iii) applications such as privacy preservation, cloud-connected vehicles, a real-time "radar-screen", traffic management, and monitoring of pedestrian behavior during pandemics. The results of the experimental studies performed on the COSMOS testbed located in New York City are illustrated. Future challenges in designing human-centered smart city intersections are summarized.