It is an IoT-based traffic signal controller that gives priority to emergency vehicles and tries to minimize the delay caused by intersections. This system is made with an Arduino UNO microcontroller, NodeMCU, IR sensors, and a GPS module. An IR sensor monitors the density value, and the location of emergency vehicles is taken by the GPS module. The NodeMCU, with ESP8266 as its processor, is given the responsibility to send traffic data to the cloud through the Blynk application. The system adjusts signal timings in real-time based on the available real-time data so that it will not disturb other flows of traffic, but give preference to emergency vehicles. Hence, this solution ensures a fast destination for emergency vehicles and reduces response time, as well as the risk of accidents or delays. Efficient management of traffic and reduction in congestion, this system will contribute to urban mobility and safety by offering a scalable and cost-effective method for solving emergency traffic management in cities.

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IoT-Enabled Adaptive Traffic Signal Control System for Real-Time Emergency Vehicle Prioritization and Traffic Flow Optimization

  • K. Kanchana,
  • J. Thangatamilselvan,
  • Suriya Praba

摘要

It is an IoT-based traffic signal controller that gives priority to emergency vehicles and tries to minimize the delay caused by intersections. This system is made with an Arduino UNO microcontroller, NodeMCU, IR sensors, and a GPS module. An IR sensor monitors the density value, and the location of emergency vehicles is taken by the GPS module. The NodeMCU, with ESP8266 as its processor, is given the responsibility to send traffic data to the cloud through the Blynk application. The system adjusts signal timings in real-time based on the available real-time data so that it will not disturb other flows of traffic, but give preference to emergency vehicles. Hence, this solution ensures a fast destination for emergency vehicles and reduces response time, as well as the risk of accidents or delays. Efficient management of traffic and reduction in congestion, this system will contribute to urban mobility and safety by offering a scalable and cost-effective method for solving emergency traffic management in cities.