Intelligent Traffic Management System using Computer Vision and Machine Learning

Abstract

With urban traffic management becoming more and more complex, a ground-breaking system called "Intelligent Traffic Management System using Computer Vision and Machine Learning" was created to address these issues. It makes use of the strength of two innovative technologies: computer vision and machine learning. The system can receive and analyze visual data from cameras placed across roads thanks to computer vision, and machine learning gives it the ability to learn from this data and come to wise conclusions without explicit programming.
The subject of artificial intelligence known as computer vision enables computers to interpret and comprehend visual data from the environment, including photos and movies. To assess traffic patterns and recognize different objects on the road, such as vehicles, pedestrians, and traffic signals, the system uses a wide range of algorithms, including image recognition, object detection, and tracking. Contrarily, a subset of artificial intelligence known as machine learning gives the system the capacity to learn from data and enhance its performance over time. The system can recognize trends, forecast traffic flow, and improve traffic management methods based on real-time inputs after being trained on enormous volumes of previous traffic data.