Most public agency assets include pavement and, therefore, require crack detection survey and maintenance. Given that traditional pavement assessment practices and technology are time-consuming and inaccurate, Benesch explored integrating artificial intelligence (AI) and machine learning (ML) into their field data collection workflows, targeting crack detection in pavement. However, they faced challenges closing the gap between digitally identifying cracks and classifying the cracks based on condition assessment. Therefore, they sought to develop their pavement crack detection technology solution.

They selected Bentley’s iTwin Capture Modeler, AssetWise, and iTwin to pilot their digital innovation at three active project sites in the United States, creating digital twins of the sites. Bentley technology harnessed the power of AI and ML, streamlining the crack detection process and feeding the data into the digital twin for analysis. The solution automates digitization of the crack linework data and saves 75% in field time, and is expected to save USD 144,000 in 100 airport inspections without impacting traffic and/or airport operations.