Secure Design and Implementation of Smart Traffic Light Management System

By identifying areas of heavy congestion, smart traffic management systems can then implement measures to alleviate that problem. In order to accomplish this, it analyzes and synchronizes data from sensors in real-time. The input data are used to determine when the traffic signal blinks due to congestion. This method has the potential to lessen air pollution and make roads safer for everyone. In this research, we offer a smart technique for accurate traffic estimate prediction using random forest. In the majority of instances, the approximate traffic estimate is better than the shortest route with respect to overall travel time and fuel cost. Based on our findings, we were able to decrease the average waiting time of vehicles while still accurately forecasting traffic.