Enhancing Winter Road Maintenance via Cloud Computing
Document Type
Article
Publication Date
4-1-2023
Department
Department of Civil, Environmental, and Geospatial Engineering
Abstract
In this study, we developed an AI-enhanced cloud computing framework to enable the autonomous decision-making quality and precision of winter road operations for connected living, namely Smart Maintenance Decision Support System (SmartMDSS). With the support from the Federal Highway Administration (FHWA) and Michigan Department of Transportation, we are among the first to develop AI-enabled tools for practical winter road maintenance decision-making. On the front end, SmartMDSS provides a user-friendly graphical interface showing all the valuable data and winter operations for specific points on the road and sends necessary warnings and notifications. On the back end, SmartMDSS extracts and analyzes data and makes winter road maintenance decisions. Convolutional Neural Network (CNN) has been successfully employed to identify the snow coverage on the road surface. Decision-making algorithms were proposed and implemented to support the road engineers and operators for real-time winter maintenance operations.
Publication Title
IEEE Internet Computing
Recommended Citation
Tavakoli, H.,
Liu, Z.,
Azmoon, B.,
&
Yuan, X.
(2023).
Enhancing Winter Road Maintenance via Cloud Computing.
IEEE Internet Computing.
http://doi.org/10.1109/MIC.2023.3265651
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/17082