Welcome to the Smart Bridge SHM System
Transforming Smart Bridge Monitoring by Computer Vision and Edge Computing.
Transforming Smart Bridge Monitoring by Computer Vision and Edge Computing.
Many Australian high-value bridges are approaching their service life, posing risks to community and sustainable growth. Given a high number of assets but a limited budget, this project aims to leveraging emerging computer vision and edge computing technologies to develop a cost-effective, easy-to-deploy monitoring system to assist in real-time bridge monitoring and optimizedmaintenance. Collaborating with Main Roads WA, the expected outcome is the development and application of a market-ready edge computing sensing system deployable to a population of existing bridges. This project will enhance bridge safety, reduce lifecycle maintenance costs and uplift the service life of transport infrastructure for smart city and remote operations
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⭐ Project Lead: Dr. Zhen Peng Google Scholar Zhen.Peng1@curtin.edu.au
Responsible for project leadership, system architecture, and core research direction.
⭐ Primary Developer & Researcher: Dr. Yue Zhong Personal Website Yue.Zhong@curtin.edu.au
Responsible for system code, data collection, data processing, and web system development.
This project is conducted in collaboration with Main Roads Western Australia (MRWA).
This research is supported by the ARC Early Career Industry Fellowship (2025–2028) titled
“Transforming Smart Bridge Monitoring by Computer Vision and Edge Computing.”
We gratefully acknowledge the partnership and support from Main Roads WA.