Bridge Engineering Center

About the research

To extract the necessary data and features from the bridge plan sets and inspection records, a manual process is currently in place. This means that, even for a simple query, the engineer/staff member in charge needs to browse several pages, locate appropriate details, determine quantities, and note down the required information. The process becomes further demanding if the scope of the query is extended to several bridge elements, involving a post-processing of various sources of information. However, with the advancements made in machine learning and artificial intelligence (ML/AI), new opportunities have emerged to move from a manual to an automated process for data and feature extraction from bridge plan sets and inspection records. Thus, this research project aims at developing the first-known computational platform with the capabilities to perform (1) automated final bridge plan review, (2) automated data and feature extraction from bridge plans, and (3) automated damage detection and quantification. The ultimate goal will be a quick delivery of high-quality information about bridge structures. The main features of this platform include distinguishing different physical objects, determining their boundaries and dimensions, extracting relevant datasets and features of interest, and finally providing qualitative and quantitative condition assessment measures for bridge elements in desired output formats. Further to the listed capabilities, an important benefit of this platform is that, after training and quality control, it can work with no immediate supervision, minimizing the time and effort required to plan preventive and corrective actions for bridge structures.