Automated Road Safety Enhancement Through Deep Learning A Robust Convolutional Neural Network Approach for Pothole Detection

When potholes are present, there is a tremendous threat to the safety of road equipment and driving. This study proposes a unique approach that employs Convolutional Neural Networks (CNNs) to automate the process of recognising potholes in road visualisations. Convolutional neural network (CNN) model development and training, input preparation, and model correctness verification are the phases in the process. The findings reveal that potholes can be appropriately found using the recommended technology, which makes it practical to implement safer and better road repair procedures.