A new research project at the University of New Orleans is exploring how augmented reality can improve the accuracy and efficiency of civil infrastructure inspections. Supported by the Louisiana Transportation Research Center, the study integrates extended reality (XR) technologies with machine learning and computer vision to assist inspectors in evaluating structural conditions in real time.
Anika Tabassum Sarkar, assistant professor of civil and environmental engineering, serves as principal investigator for the project Extended Reality for Infrastructure Assessment. The grant award supports development of an immersive inspection assistant that leverages augmented reality to enhance traditional structural evaluation methods.
By combining elements of virtual reality (VR), augmented reality (AR), and mixed reality (MR), XR provides a new dimension to structural health monitoring (SHM). The research will initially focus on AR tools, enabling inspectors to overlay real-time data, such as crack locations and strain patterns, onto physical structures during field assessments. Devices like the Magic Leap 2 and Varjo XR-3 will be used to visualize lab-tested specimens, in conjunction with Digital Image Correlation Sensor data.
The goal is to create a semi-automated system that incorporates computer vision and machine learning to detect defects, guide inspectors through assessment procedures, and predict future maintenance needs. According to Sarkar, this integrated approach offers the potential to streamline workflows, reduce human error, and support timelier data-driven decisions.
The project comes at an important time for Louisiana. The state received a D+ on its most recent Infrastructure Report Card and ranks among the highest nationally for structurally deficient bridges. Traditional inspection techniques rely heavily on subjective visual evaluations and are often constrained by limited documentation methods. SHM systems offer improved accuracy and real-time monitoring, but challenges such as high costs and complex implementation have slowed adoption.
Sarkar鈥檚 research addresses these barriers by introducing a more intuitive, visual, and collaborative framework for infrastructure assessment. By harnessing XR鈥檚 immersive capabilities and the analytical power of AI, the project aims to improve safety, extend asset life cycles, and support long-term infrastructure resilience in Louisiana and beyond.
