Road Damage Detection System — AI-powered Pothole & Crack Identification For Smart City

An advanced road damage detection platform leveraging deep learning algorithms to automatically identify and classify surface defects — including potholes, longitudinal cracks, transverse cracks, and alligator cracking — from standard road imagery. Utilising convolutional neural networks (CNN) and real-time object detection (YOLOv8), the system processes images captured via smartphones or dashcams without requiring specialised hardware. Designed for integration into smart city infrastructure management workflows, enabling transport departments and municipal authorities to automate road condition surveys, prioritise maintenance schedules, and reduce inspection costs significantly.

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