Traffic congestion has become a major challenge in urban transportation systems due to the increasing number of vehicles and inefficient fixed-time traffic signal operations. Conventional traffic signals provide equal signal durations irre-spective of traffic density, resulting in unnecessary delays and in-creased fuel consumption. This paper presents an adaptive smart traffic signal control system based on ESP32 microcontrollers and infrared (IR) sensors for real-time traffic density monitoring. The proposed system dynamically allocates signal timings according to vehicle density at multiple junctions. Two master ESP32 controllers process the sensor data and determine appropriate signal durations to improve traffic flow efficiency. Experimental analysis demonstrates that the proposed system reduces waiting time and congestion while providing better utilization of road infrastructure. The system offers a low-cost and scalable solution for intelligent transportation and smart city applications.

Paper presents an adaptive smart traffic signal control system based on ESP32 and infrared sensors for real-time traffic density monitoring. Unlike conventional fixed-time traf-fic signals, the proposed system dynamically allocates signal durations according to traffic conditions, thereby reducing congestion and improving traffic flow efficiency. The devel-oped system offers a cost-effective, reliable, and scalable solution for intelligent transportation systems and smart city applications. Future enhancements can further improve system performance by incorporating advanced technologies such as artificial intelligence and cloud connectivity.

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