Title:Optimizing Urban Mobility: An AI and IoT-Based Smart Traffic System


Authors:Aditya Birthare, Arnima Dubey, Abhinav Rathore, Amresh Kadam, Aayushman Babele, Vandana Kate


Published in: Volume 3 Issue 1 Jan June 2026, Page No.416-421


Keywords:Smart cities; Traffic management; Intelligent Transportation Systems; Artificial intelli gence; Internet of Things


Abstract: Urban traffic congestion is a major problem for modern cities. It leads to longer travel times, higher fuel use, and more pollution. Traditional traffic management systems, which depend on fixed time signals, often fail to adjust to real-time changes in traffic. This results in poor traffic flow. This paper suggests a smart traffic management system that uses the Internet of Things (IoT) and digital display boards to improve city mobility and road safety. The proposed system employs IoT sensors, like cameras and infrared devices, to gather real time information on vehicle numbers, speeds, and traffic conditions at key intersections. This data goes to a central control unit, where a flexible algorithm processes it to adapt traffic signal timings. The system also features Variable Message Sign (VMS) boards, or digital boards, that show real-time information to drivers, including traffic updates, alerts for in cidents, and suggestions for alternative routes. This integrated strategy seeks to lower traffic delays by controlling signals dynamically and providing drivers with instant, useful information. The system can also give priority to emergency vehicles by creating clear paths at intersections, which can improve response times and potentially save lives. The main goal is to develop a more effective, responsive, and safer urban transportation network that supports a more sustainable and enjoyable ”smart city” environment.


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