UTC 2022 Funding - Cycle 3 Research Projects

Project No.: CY3-OSU-08
Title: AI-Driven 2D/3D Visual Analytics System for Automated Bridge Deck Inspection
Performing Institution: Oklahoma State University
Principal Investigator: Joshua Q. Li
Start and Anticipated Completion Dates: 1/1/26-1/15/27
Abstract: Bridge inspections are essential for ensuring structural safety and effective maintenance planning, yet traditional manual methods are time-consuming, labor-intensive, and often subjective. Following field practices in the Oklahoma Bridge Inspection Manual (BrM), this project aims to develop an AI-powered bridge inspection system that automates the detection, classification, and visualization of deck-level defects by integrating 2D and 3D imagery. The automated system can offer a scalable solution that reduces inspection time, cost, and labor while improving consistency and early detection of bridge deck deterioration. The core objectives include developing a visual analytics framework for identifying cracks, spalls, delamination, and joint-related defects and building a scalable system prototype that fits within ODOT’s existing workflows. The project will include a feasibility assessment for statewide deployment and provide thorough documentation and validation results. The outcome will lay the groundwork for scalable, data-driven tools that support more effective and proactive bridge management across Oklahoma.
Click to read more