Winter Service Session 17 - Use of AI for winter maintenance
Thursday, March 12
11:30
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13:00
Chair: Hiroki Matsushita, Civil Engineering Research Institute for Cold Region, Japan
Room: Hall E
This session highlighted the growing role of artificial intelligence in winter maintenance, with speakers from the call for papers. Presentations showcased deep learning applications for snow and ice condition estimation, real-time road weather classification, scalable detection of weather-related hazards, and AI-based disaster search systems. Together, these innovations demonstrated how intelligent technologies could enhance safety, efficiency, and resilience in winter service operations.
Welcome and session introduction
• Hiroki Matsushita, Civil Engineering Research Institute for Cold Region, Japan
Presentations
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The test implementation of a wide-area road snow and ice condition estimation system using road CCTV cameras and deep learning
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Real-Time Road Weather Classification Using Neural Networks and Surveillance Cameras
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Scalable Detection of Weather-Related Road Conditions Through Color Space Analysis and Deep Learning on Traffic Camera Images
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Utilization of a road disaster search system using deep learning techniques and its applications.
Questions and Answers
• Moderator: Hiroki Matsushita, Civil Engineering Research Institute for Cold Region, Japan
Conclusion
• Hiroki Matsushita, Civil Engineering Research Institute for Cold Region, Japan
Organization
Session Organiser: Horst Hanke, Leader of the German Winter Service Committee, Germany
Session Secretary: [To be confirmed]