Potholes are a major concern for road infrastructure, causing damage to vehicles, accidents, and disrupting traffic flow. Traditional methods of pothole detection procedures are slow, inefficient, and resource-intensive. The proposed cloud-based pothole analysis system offers a promising solution by fetching data from a camera implanted in the car. The mounted camera captures images throughout the destination routes and transmit the captures ones to a cloud-based system where the detection to analyze the presence of potholes is achieved using YOLO v4 models. The analysis considers both pothole and accelerometer image data’s to define uniqueness by analyzing the detected potholes for their severity and to trigger corrective measures. The resulting system will show a dashboard to visualize the classification along with the location of the pothole with accuracy of 93%. This will help the concerned authorities to take immediate action based on the location and severity of potholes along with appropriate percentages.