Road transport is the most common mode of transport worldwide, so regulatory authorities should pay more attention to the safety of passengers. Despite the various causes of road safety problems, poorly maintained roads are important, as potholes appear to be a major cause of accidents worldwide. This paper proposes a comprehensive approach to identifying potholes, autonomous filling of them, and maintaining a database with constant updates on the potholes and their clearance to prevent accidents and improve road safety. A web-based portal reports the potholes to concerned authorities by sending the location, size, depth, and predictive analytics to anticipate pothole-related issues. Implemented as a monocular vision autonomous car prototype using an Arduino UNO as a processing chip. This paper highlights the importance of proactive measures to enhance road safety in addition to pothole prevention. Regulators are urged to invest in remediation and technical improvements to reduce the risks associated with poor roads. Together, we may assist in reducing accidents and improving overall road safety by encouraging good driving practices and citizen participation in reporting accidents on the roads. However, combined with the latest innovations like predictive analytics and automated vehicle technology, this collaborative approach has a chance to build safer routes for communities across the world.
Advanced Pothole Detection Using Image Processing
04.07.2024
784121 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch