Connecting Traffic Signals to Electric Vehicles Using IoT and AI/ML

Nowadays the growth of traffic congestion on roads leads to hours of traffic jams and creates chaos. Also, during traffic jams, we can observe a lot of noise pollution and fuel wastage, because sometimes people do not turn off their car engines, which add on to the air pollution. One problem which the working sector of the country faces is reaching their workspaces on time, and due to congested traffic control systems, it often leads to delay whether roads are loaded with traffic or not due to traffic signals countdown mechanism. Effective traffic management can save markable percentage of resources. The research work presents IoT- and ML-based traffic analysis and control system. The proposed method consists of AI-driven vehicle, sensors to track the vehicle speed and road density, leading to accident-free journey. The concept also utilizes the infrared sensors along with the ARPA camera and machine learning to detect streamline and the flow of electric vehicles. The proposed method reduces vehicle waiting time and thus the congestion.