IoT-Enabled Smart Traffic Management and Alert System with Green Corridor for Emergency Vehicles

This paper presents a Smart Traffic Management Alert System (STMAS) designed to improve emergency medical response time in urban environments by leveraging Internet of Things (IOT) technology. The system addresses the critical delays ambulances face due to conventional, fixed-time traffic signal patterns that fail to adapt to real-time emergency needs. Our approach integrates GPS- enabled ambulance tracking, microcontroller-based traffic signal control, cloud-based data processing, and digital display boards to ensure prioritized passage for emergency vehicles. When an ambulance is detected within a predefined radius of an intersection, the system first activates LED display boards with warning messages to alert nearby drivers and pedestrians. Once the path is cleared, the corresponding traffic signal is switched to green in the ambulance’s direction. Tests and simulations show that the system can greatly reduce the time ambulances spend in traffic and improve coordination between emergency services and traffic control. This determining the patient’s chances of survival. Unfortunately, traditional traffic control systems, which are based on fixed-time signal patterns, lack the flexibility to adapt to real-time traffic conditions or prioritize specific vehicles. As a result, ambulances often face unnecessary delays while navigating through crowded intersections, even when their journey is time-critical. These delays can be the difference between life and death, highlighting the urgent need for an intelligent, responsive traffic management system. The advancement of the Internet of Things (IoT), cloud computing, and real-time data analytics has opened up new opportunities to address these challenges. IoT makes it possible for devices and systems to share data instantly, allowing traffic lights, sensors, and emergency vehicles to communicate project adds to the field of intelligent transportation systems (ITS) by offering an automated, scalable, and dependable solution for giving priority to emergency vehicles, which can help save more lives in critical situations.