Optimization of Urban Traffic Through Integration of Dijkstra’s Algorithm with Edge Computing

This study proposes a decentralized urban traffic optimization approach by integrating Dijkstra’s algorithm with edge computing. The system models road networks as dynamic graphs, using real-time data from IoT sensors to adapt routing decisions. A three-layer architecture reduces latency and improves scalability. Simulation results show a 42% decrease in response time and a 25% reduction in congestion compared to centralized systems. The approach demonstrates high reliability and potential for smart city applications.