AI Put to Work to Help Assess Structural Integrity of Bridges - AI Trends

AI is being applied to assess the health of civil infrastructure through systems that test the integrity of bridges. A civil engineering assistant professor at The University of Texas at Arlington is working to better understand a bridge's structural health by combining machine learning with traditional monitoring measurements, according to a press release from the University of Texas at Arlington (UTA). The 18-month, $122,000 grant to Dr. Suyun Ham of the Civil Engineering department is part of UTA's membership in the Transportation Consortium of South-Central States (Tran-SET), a U.S. Department of Transportation Center administered by Louisiana State University. He will test his models in Dallas and Fort Worth. The systems in place to monitor bridges today are weight-in-motion systems with sensors that measure vibrations, strain, and deflection.