Traffic Signal Automation by Sensing and Detecting Traffic Intensity Through IR Sensors

The rapid urbanization and increasing traffic congestion pose significant challenges for traffic management systems. To alleviate these issues, we proposed an innovative solution for traffic signal automation using Internet of Things (IoT) technology. The objective is to develop a smart traffic management system that can dynamically adapt traffic signal timing based on real-time traffic intensity. This research paper presents a novel approach to traffic signal automation using IoT technology and IR sensors. The proposed system provides realtime traffic monitoring, adaptive signal control, and efficient decision-making, leading to enhanced traffic management and improved overall urban mobility. Traffic congestion is a persistent problem in urban areas, leading to increased travel times, fuel consumption, and environmental pollution. To address these challenges, this study proposes an Internet of Things (IoT)-based traffic signal automation system that utilizes infrared (IR) sensors to sense and detect traffic intensity at intersections. The objective of this research is to develop an efficient and reliable traffic signal control mechanism that dynamically adapts to varying traffic conditions. The proposed system employs IR sensors strategically placed at different locations to monitor the presence and movement of vehicles. These sensors detect infrared radiation emitted by vehicles, enabling the system to estimate traffic density and occupancy.