• Rekha Gavit
• Purthviraj Patil
• Anil Bande
• Darshan chaudary
• Pooja dalvi

The increasing complexity of urban transportation systems has led to widespread traffic congestion, higher pollution levels, and inefficiencies in daily commute times. Traditional traffic management approaches often fail to adapt to dynamic road conditions, leading to suboptimal traffic flow. This project proposes a Smart Traffic Management System (STMS) that utilizes Internet of Things (IoT) sensors, machine learning algorithms, and real-time data analytics to optimize traffic flow and reduce congestion. By monitoring traffic patterns and adapting traffic signal timings dynamically, the system improves the overall efficiency of urban transportation, enhances road safety, and contributes to environmental sustainability. The implementation of this system offers significant potential for reducing traffic delays, minimizing fuel consumption, and lowering emissions in metropolitan areas..

" SMART TRAFFIC MANAGEMENT SYSTEMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.l381-l387, May-2025, Available :http://www.jetir.org/papers/JETIR2505C31.pdf

" SMART TRAFFIC MANAGEMENT SYSTEMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppl381-l387, May-2025, Available at : http://www.jetir.org/papers/JETIR2505C31.pdf