This project will design a 5G-enabled smart traffic management system that leverages edge computing and real-time data analytics to optimize urban traffic flow. Using vehicle-to-infrastructure (V2I) communication, the system will collect real-time traffic data from sensors, cameras, and connected vehicles. Edge computing will be used to process data locally, reducing latency and ensuring faster response times. The system will implement AI-based predictive analytics to control traffic signals dynamically, reduce congestion, and improve emergency response times. It will also integrate a mobile app for drivers, providing real-time traffic updates and optimal route suggestions.
Supervisor
Mahmoud Naser
Committee
Dr. Samer Abdullah - Dr. Amer Waleed
Students
Mohammed Adel - Raghad Sultan
