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Road transport is the most widely used means of transportation around the world. With this high use of road transport, the safety of travellers’ becomes the prime concern for any governing authority. While some safety concerns arise from driver errors and environmental factors, most cases are a result of poor maintenance of these roads. Potholes, specifically, are one of the leading causes of road accidents throughout the world and need to be taken care of immediately, by the authorities. This paper presents a solution that makes use of civilians’ mobile sensors, along with image-based alternatives to detect potholes in real-time, using Machine Learning. The concerned authorities are then notified about the same through a web-based portal, to take the necessary action. The solution also incorporates pivoting existing complaints, location tagging and prioritization. Additionally, the solution provides a forecast of the likelihood of issues regarding potholes, constantly updating time series data of the locations.