  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.
