An AI-based Early Warning Platform for Bridge Scour

Scourcast provides a platform for real-time scour forecast and risk assessment.

ScourCast Platform

Bridge scour has been the number one cause of bridge failure and has imposed significant risk to infrastructure safety in various parts of the world, such as the US, Australia, UK, among other countries.

ScourCast is an AI-powered web-based platform for real-time forecast of bridge scour for early warning and risk assessment, harnessing emerging AI technology and sensor monitoring to enable superior bridge scour management.

It is also a platform for a central database of historic and real-time scour monitoring database across the world and provides advanced data processing and smoothing technics to reveal the true trends from noisy sensor readings. The gathered data will be accessible for public via this platform, to promote data-driven research for better understanding of bridge scour and improving public safety.

This collaborative research invites the practitioners, government authorities, and researchers/academics working in this field across the world, to take part in a data mining effort for sharing available sensor data from scour monitoring programs with public.

Collaborators and Partners

Meet the Team

Start working with our team at University of Melbourne.

Team Lead
Dr Negin Yousefpour

University of Melbourne

Senior Lecturer

Current Member
Dr Bo Wang

University of Melbourne

Research Fellow

Former Member
Dr Tahrima Hashim

University of Melbourne

Research Fellow (2022)

Former Member
Dr Oscar Correa

University of Melbourne

Research Fellow (2020-2021)

Contact us

Have Question ? Get in touch!

We’re ready to partner with you for research and implementation of ScourCast for bridge scour management. Take a moment to tell us about yourself, and we’ll be in touch shortly. You can also contact [email protected] directly for any enquiries.