LANE MORPH: Machine Learning Powered Divider For Traffic Volume Adaptation

LaneMorph is a machine learning-powered system designed to optimize urban traffic management using IoT and real-time video processing. By dynamically adjusting road dividers based on traffic density, the system enhances lane utilization, reduces congestion, and prioritizes emergency vehicles. This paper details the architecture, implementation, and potential impact of LaneMorph in smart city infrastructure. Additionally, the system integrates various sensor technologies, predictive algorithms, and automation mechanisms to improve traffic flow efficiency and ensure road safety.