Smart Flow: Revolutionizing Traffic Management with Intelligent Systems

Traffic congestion is a persistent challenge in urban areas, leading to delays, fuel wastage, and increased pollution. The Intelligent Traffic Management System (ITMS) is designed to address these issues by leveraging real-time data collection, machine learning algorithms, and dynamic traffic signal control. The system continuously monitors traffic conditions using data from sensors and vehicles, optimizing signal timings to improve traffic flow and reduce congestion.Initial testing and simulations indicate that ITMS achieves 88 % accuracy in time optimization, demonstrating its effectiveness in real-time traffic management. The system outperforms traditional traffic control methods by making data-driven decisions that adapt to changing traffic patterns, particularly during peak hours. Future work will focus on enhancing machine learning capabilities, refining algorithms, and conducting large-scale real-world testing to ensure scalability and reliability across diverse urban environments. The proposed system aims to create a smarter, more efficient, and responsive traffic management solution that enhances commuter experiences and urban mobility.