Enhancing Traffic Flow and Reducing Congestion: A Smart City Approach with an IoT-based Intelligent Traffic Management System

With burgeoning populations and booming industries straining urban landscapes, traffic management has become a critical issue for cities worldwide. Traffic congestion is a significant challenge modern cities face, leading to wasted time, increased fuel consumption, and air pollution. This research investigates how Smart City technologies can revolutionize urban traffic management. We propose an Intelligent Traffic Management System (ITMS) utilizing the Internet of Things (IoT) to tackle traffic congestion, a significant hurdle for modern cities. The ITMS gathers real-time traffic data (vehicle count, speed, lane occupancy) through strategically positioned sensors at intersections. A central control system analyzes this data and dynamically adjusts traffic signals, allocating green time based on actual traffic flow. This approach aims to optimize traffic flow, significantly reduce congestion, and improve efficiency. The paper explores the potential benefits of the proposed system, including shorter travel times, improved air quality, and enhanced safety for pedestrians and vehicles. Finally, the proposed system indicates significant potential benefits, including reductions in waiting time $\mathbf{1 7. 3 7 \%}$; congestion time $\mathbf{1 8. 4 3 \%}$, leading to smoother traffic flow and improved phase departure time $\mathbf{2 9. 2 0 \%}$ or higher increase in throughput, signifying that more vehicles can pass through intersections within a given timeframe.