Abstract:

Traffic congestion and accidents are significant challenges in urban areas, causing economic losses and delays in emergency response. SmartRoads proposes an AI-powered traffic incident detection system using Convolutional Neural Networks (CNN) for image-based detection and Random Forest (RF) for traffic pattern classification. The system analyzes real-time traffic camera feeds and sensor data to identify incidents such as accidents, congestion, and unusual traffic patterns. Experimental results demonstrate high detection accuracy, reduced false alarms, and improved response times, showcasing the system's potential to enhance road safety and traffic management efficiency.

Description:

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