Leveraging AI and remote sensor technology in transportation infrastructure management

Many organizations responsible for bridge infrastructure face workforce shortages and an increasing backlog of aging bridges. Addressing these challenges requires a multi-faceted solution involving owner/operators, engineering consultants, and the entire infrastructure industry. Leveraging the latest technology to improve current workflows is crucial. The collection of reality data with a UAS and the creation of a digital twin have proven valuable in augmenting traditional inspections through remote visualization. As technology matures, advances in tools used alongside the digital twin continue to assist inspectors. This paper highlights how Collins Engineers used these tools to augment their workflows for the Minnesota Department of Transportation in inspecting and rehabilitating the Robert Street Bridge. This includes photo navigation with the 3D model, georeferenced inspection forms, AI assisted defect detection and mobile tools in the field. The technology and workflow used by Collins saved over 30% in inspection hours and improved data collection quality, generating a 20% savings in construction costs. Additionally, the paper covers other tools within a digital twin, augmented reality model visualization, and IoT sensors for structural health monitoring. Other AI detectors under development will be discussed, showcasing how these innovations will continue to transform traditional workflows. The transformation from traditional inspection workflows has the potential to enhance safety, reduce costs, and improve the accuracy of inspection results.