AI-POWERED SMART TRAFFIC MANAGEMENT AND ACCIDENT ALERT SYSTEM USING COMPUTER VISION AND IOT
Keywords:
Artificial Intelligence (AI), Computer Vision, Intelligent Traffic Management, Accident Detection, Internet of Things (IoT), Smart Cities, Deep Learning, YOLO, Real-Time Monitoring, Emergency Alert SystemAbstract
The rapid increase in vehicle population has led to significant challenges in traffic management and road safety. Conventional traffic systems rely on fixed signal timings and man-ual monitoring, which are inefficient under dynamic conditions. This paper presents an AI-Powered Smart Traffic Management and Accident Alert System using Computer Vision and IoT technologies. The system captures real-time traffic data through smart cameras and processes it using image processing and deep learning techniques to detect vehicles and estimate traffic density. Based on this analysis, traffic signals are dynamically controlled to optimize traffic flow and reduce congestion. In addition, the system incorporates an automatic accident detection mechanism that identifies abnormal events such as collisions or sudden stops. Upon detection, alerts are instantly sent to nearby hospitals and police stations along with location details. The system also notifies family members using a secure cloud-based database, ensuring timely communication during emergencies. The proposed solution integrates traffic control, ac-cident detection, and emergency response into a unified platform, improving efficiency, reducing response time, and enhancing road safety. This system is scalable and suitable for smart city applications.
