Abstract: Potholes are a major concern on roads and highways, causing accidents, vehicle damage, and traffic delays. Detecting potholes in a timely and accurate manner is crucial for ensuring safe and efficient transportation. Various technologies are being used for pothole detection, including laser-based systems, machine learning algorithms, computer vision techniques, and acoustic sensors. Laser-based systems use high-precision measurements to detect the road surface's irregularities, including potholes. Machine learning algorithms analyze images of road surfaces captured by cameras mounted on vehicles to identify potholes. Computer vision techniques analyze road surface images captured by cameras or drones to detect potholes. Acoustic sensors can detect the vibrations generated by vehicles driving over potholes. Overall, the use of these technologies has improved pothole detection accuracy and efficiency, enabling faster repairs and safer roads.

Keywords: Machine Learning, Deep Learning, IoT, Pothole.

PDF | DOI: 10.17148/IJARCCE.2023.12506

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