Abstract: Potholes are becoming a growing cause of concern, resulting in numerous road accidents across the country. To address this problem, a smart pothole reporting system has been developed that can report and address potholes as soon as they occur. The system ensures transparency and accountability between citizens and the government while being user-friendly. The smart system employs an image recognition-based method that uses machine learning techniques, such as the Classification Algorithm using TensorFlow, to identify potholes. The system collects data and uses it to represent areas with a higher density of potholes on a map. If the density of potholes in a certain area is high, the road appears red on the map. Conversely, if the potholes have been patched up or there are no potholes, the road appears green. Color codes are used to warn and alert drivers about the observed road conditions. The smart pothole reporting system enables prompt reporting and resolution of potholes by the appropriate authorities. The system allows the government to prioritize areas that require attention and repair, leading to a more efficient allocation of resources. Additionally, the system helps to eliminate the threat posed by potholes and ensures safer roads for everyone. In conclusion, the smart pothole reporting system is an easy- to-use solution that addresses the growing concern about potholes and provides a safer road network for citizens. The system ensures transparency and accountability between the government and citizens, using advanced technology to identify and report potholes promptly.

Keywords: Potholes, Smart Reporting, Classification Algorithm, TensorFlow, Colour code, Alert

| DOI: 10.17148/IARJSET.2024.11481