THEME ALIGNMENT

INDUSTRY PROBLEM

The increasing significance of advanced sensing technologies in Structural Health Monitoring (SHM) has underscored the need for more sophisticated decision support systems (DSS). Over the past decade, there have been notable advanced sensor-based monitoring systems to collect and analyse diverse sources of bridge operation data. Integration of different sensors in SHM require enhancement in decision process in order to derive optimized management plans supported by a decision support system for the robust and efficient maintenance of the infrastructure assets. 

However, a significant gap persists in current bridge management systems: the absence of a Digital Twin (DT)-based intelligent Decision Support platform capable of effectively gathering and analysing diverse sources of bridge monitoring data. This gap hinders the development of optimised management plans supported by robust decision-making frameworks for infrastructure maintenance.

Therefore, this project intends to address this industry gap by providing a comprehensive Intelligent Bridge Management System (iBMS) that not only utilises the advantageous features of Digital twins, but also develops and innovative system that integrates a powerful Decision Support System (DSS) based on Artificial Intelligence (AI).  This system is specifically designed to enhance the efficiency of bridge asset management by facilitating more reliable decision-making in the realm of remediation strategy planning.