An AI-powered road damage detection system built with YOLOv8 that automatically identifies and localizes road defects in images and videos. Trained on the Omdena road damage dataset via Roboflow.
Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Road Damage Detection System Project uses AI and computer vision to identify potholes and cracks in roads, enabling faster maintenance and improving road safety.
An integrated YOLOv8/v10/v11 framework for real-time road damage detection and classification. Features a Streamlit-based monitoring dashboard with automated GPS telemetry logging.
AI-powered pothole and road-hazard detection using YOLO26, ByteTrack, OpenCV and Streamlit.
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