IoT based Intelligent Traffic Management System with Dynamic Lane Prioritization and Emergency Vehicle Clearance

In fast expanding cities, urban traffic congestion creates major problems for general transportation efficiency and emergency response times. Using real-time sensor data and cloud analytics, this study offers an Internet of Things (IoT)-enabled Smart Traffic Signaling System that dynamically prioritizes emergency vehicles and improves traffic flow. The system uses NodeMCU ESP8266 for wireless data transfer to the ThingSpeak cloud platform, Arduino Nano microcontroller for local signal control, Radio Frequency Identification (RFID) readers for emergency vehicle identification, and Infrared (IR) sensors for vehicle detection. The device also tracks pedestrian pathway infractions and records them to the cloud for enforcement. Prototype testing revealed great performance with 95% vehicle identification accuracy, 98% emergency vehicle prioritization efficiency, and 97% cloud-based integration reliability. This study offers a useful and efficient tool for smart traffic control in smart metropolitan areas by tackling important concerns such environmental robustness, sensor fusion, real-time flexibility, and scalability.