In modern urban areas, the management of traffic is a significant challenge, and efficient traffic flow is crucial to reduce congestion, travel time, and air pollution. Traditional traffic light systems are based on fixed schedules and do not consider real-time traffic conditions, leading to inefficient traffic flow and traffic congestion. The Smart Traffic Light Management System (STLMS) is a ground-breaking solution that makes use of cutting-edge technologies like the Internet of Things, Artificial Intelligence, and Machine Learning to optimize traffic flow and relieve congestion by using data on the amount of traffic on various road segments. To reduce the congestion and waiting time at the intersection, an algorithm is proposed to control the green light time of the traffic light based on the traffic density on different road segments. The result shows the proposed algorithm outperformed the other researches performed in this area.