• BHOOMIKA VASU
• DIPIKA MANJUNATH
• MEGHANA G
• DR. SREENIVASA SETTY

The preservation of roads is one of the most important issues in emerging nations. The economy of the nation is significantly boosted by well-maintained roadways. Finding pavement problems like potholes helps drivers prevent collisions or vehicle damage and also aids in road maintenance. Numerous ongoing efforts in the field of transport networks aim to give drivers pertinent information about the roads and traffic patterns. Indian secondary roads frequently have potholes, some of which may be wet or dry. Therefore, it is crucial to spot potholes and gauge their depths in both situations to ensure safe driving. A cost-effective automated method for identifying potholes and other issues with the road's surface is therefore becoming increasingly necessary. In this project, we create a sensing model that uses cameras to identify potholes in real time.

Deep Learning, Pothole detection, YOLO v7.

"DETECTION OF POTHOLES AND ROAD SURFACE CONDITIONS USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.i648-i652, July-2023, Available :http://www.jetir.org/papers/JETIR2307891.pdf

"DETECTION OF POTHOLES AND ROAD SURFACE CONDITIONS USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppi648-i652, July-2023, Available at : http://www.jetir.org/papers/JETIR2307891.pdf