Smart Traffic Light System Using Internet of Things

Abstract

The rapid urbanization and increasing traffic density in metropolitan areas have led to several road safety and traffic management challenges. One of the key factors contributing to these issues is the inefficiency of traditional traffic light systems, which operate based on predetermined schedules and fail to adapt to changing traffic conditions. In this research paper, we propose a smart traffic light system that leverages advanced technologies such as Internet of Things (IoT), and machine learning to optimize traffic flow and enhance road safety. The proposed system incorporates real-time traffic monitoring, predictive analytics, and adaptive signal control algorithms to dynamically adjust traffic light timings based on the current traffic situation. We evaluate the performance of the proposed system using simulations and real-world experiments, demonstrating significant improvements in traffic flow efficiency and reduction in travel time and traffic congestion. The results of this research demonstrate the potential of smart traffic light systems to revolutionize traffic management and improve road safety in urban areas.