Enhancing Winter Road Maintenance via Cloud Computing

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 (...

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Bibliographic Details
Published in:IEEE internet computing 2023-07, Vol.27 (4), p.1-8
Main Authors: Tavakoli Dastjerdi, Mohammad Hossein, Liu, Zhen, Azmoon, Behnam, Yuan, Xiaoyong
Format: Article
Language:English
Subjects:
Chemicals
Decision making
Maintenance engineering
Meteorology
Roads
Snow
Temperature measurement
Citations: Items that this one cites
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Summary: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.
ISSN:1089-7801
1941-0131
DOI:10.1109/MIC.2023.3265651