Published Paper Details:

Rapid urbanization and increased traffic congestion make it difficult for emergency vehicles to navigate crowded areas, causing delays that can be life-threatening. Traditional traffic systems rely on static infrastructure, which lacks real-time adaptability. This project proposes an IoT and AI-driven system that uses sensors and deep learning algorithms to monitor traffic density and detect emergency vehicles. It dynamically adjusts lanes to create clear paths, activating road changes through a microcontroller-based unit like Arduino or Raspberry Pi.The system also includes LED indicators, audio alerts, and digital screens on traffic signals to guide drivers. IoT integration allows cloud-based data processing and remote monitoring, enabling real-time optimization of emergency paths. By automating traffic management, this system reduces response times and enhances overall efficiency, contributing to smart city goals with a more adaptive, intelligent approach to urban traffic.