Article: Mobile sensors-based detection of road conditions and quality Journal: International Journal of Embedded Systems (IJES) 2023 Vol.16 No.5/6 pp.323 - 330 Abstract: 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 was received by gradient boosting classifier technique. The accuracy obtained was 94.07% with 88% precisions core for detection of road quality so that accidents can be reduced. Inderscience Publishers - linking academia, business and industry through research

Title: Mobile sensors-based detection of road conditions and quality

Authors: Prabhat Singh; Abhay Bansal; Ahmed E. Kamal; Sunil Kumar

Addresses: Department of Computer Science, Amity School of Engineering and Technology, Noida, Uttar Pradesh 201301, India ' Department of Computer Science, Amity School of Engineering and Technology, Noida, Uttar Pradesh 201301, India ' Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA ' Computer Science and Engineering Department, Amity School of Engineering and Technology, India

Abstract: 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 was received by gradient boosting classifier technique. The accuracy obtained was 94.07% with 88% precisions core for detection of road quality so that accidents can be reduced.

Keywords: real-time road monitoring; smart phone; sensor; Android; machine learning; flutter.

DOI: 10.1504/IJES.2023.141928

International Journal of Embedded Systems, 2023 Vol.16 No.5/6, pp.323 - 330

Received: 07 Oct 2022
Accepted: 26 May 2023
Published online: 03 Oct 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: Mobile sensors-based detection of road conditions and quality

Keep up-to-date