Digital Twin Infrastructure: Building Safer Bridges with AI

Artificial intelligence is emerging as a powerful tool to improve the safety and resilience of bridges. Researchers at the University of St. Thomas have demonstrated how AI can optimize structural design from the earliest stages of a project. By analyzing thousands of potential design options, AI identifies the best materials and dimensions to reduce stresses from water flow and traffic loads. Professor John Abraham, who led the study, highlighted that AI can not only improve the thickness and configuration of components such as gusset plates but also extend its use into real-time monitoring. This capability allows engineers to detect weaknesses before they evolve into critical failures.

At the University of Florida, researchers are advancing this concept further by developing AI-driven digital twins. These virtual replicas of bridges integrate real-time data from sensors, weigh stations, and structural health monitoring systems. By continuously updating a bridge’s condition and simulating potential scenarios, digital twins provide engineers with predictive insights to address problems before they occur. This approach reduces reliance on manual inspections, which can be hazardous and prone to human error, and allows both existing and new bridges to benefit from enhanced monitoring.

With nearly 46,100 bridges in the United States rated structurally deficient, the adoption of AI-based design and monitoring systems offers significant promise. From preventing tragedies like the I-35W and FIU pedestrian bridge collapses to supporting safer long-term infrastructure management, AI is reshaping how engineers approach structural safety. The integration of these technologies marks an important step toward a more resilient and data-driven civil infrastructure system.

Check out the following video for more information on how AI can improve bridges and dams safety.