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Singh, Prabhat, Bansal, Abhay, Kamal, Ahmed E. and Kumar, Sunil (2024) Mobile sensors-based detection of road conditions and quality. International Journal of Embedded Systems, 16 (5/6). pp. 323-330. ISSN 1741-1068
Road infrastructure is a lifeline of transportation in modern society. Due to the frequent use of roads, maintenance, and monitoring at regular intervals become important. Indian roads have many factors such as poor construction quality, heavy traffic, poor drainage, weak sub grade, and large variations in temperature that can contribute to the creation of potholes, cracks, etc. Hence, authors are focusing on developing the most efficient and accessible application for road quality detection, that can focus on more problematic areas. In the first part the work is done on the collection of data sets with the help of Android in-built mobile sensors. The second part employs the machine learning algorithm on the dataset to depict the quality of the road. The third part focuses on the deployment of the machine learning model on the server-side and reverting the results to the application. The algorithm is based on machine learning algorithms and comparing the accuracies based on accelerometer data. Best accuracy w
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