Minimizing Air pollution using Artificial Intelligence

Air pollution in urban environments, particularly on city highways, poses a significant threat to public health and the environment. Traffic congestion is the leading cause to air pollution in today's world. This study investigates the potential of machine learning and artificial intelligence (AI) for improving traffic management and reducing Air Pollution. This research paper investigates the traffic volumes in the city highways and introduces a system which will adjust the traffic signal timing based on traffic predictions and Air Quality Index (AQI) data. The results provide insights into the potential of machine learning for traffic prediction and the use of AI for optimizing green light control. With the help of these techniques traffic management systems could potentially improve traffic flow reducing congestion, and enhancing urban air.