Bridge Inspection Training and Enhanced Operations using Augmented Reality

This research project addresses the one of the main concerns of infrastructure managers i.e., data access during field inspections by designing and implementing a database and developing a new method for connecting the inspector to the datacenter using Augmented Reality (AR). This method will provide inspectors with data in the field so they will be able to compare inspections over time and make more comprehensive decisions. This is in line with the interest of the New Mexico Department of Transportation (NMDOT) that observes performing frequent, thorough, and objective inspections of infrastructure as a crucial way of preventing bridge decay. The database and data connection method will be tested in field inspections in implementation phase and the limitations will be identified. Based on the assessment of the method in these infrastructure inspections the tools will be modified and improved for real-world field inspections. This research proposes a new method for accessing the bridge inspection manuals and procedures by developing a dropdown menu containing the bridge inspection instructions that can be accessed in the field. The menu will be based on the DOT bridge inspection procedures and the instruction will contain explanatory relevant figures and data about the inspection details such as types and criteria for defects on bridges. Then this menu will be assessed in real-world bridge inspections with NMDOT, and these evaluations direct the research team to the correct direction for improving the menu. The research team will test several AR tools developed for field inspections in bridge or other infrastructure inspections and by that will evaluate AR implementation for real-world inspection process. These AR tools such as concrete crack characterization, steel crack detection, and eyetracking software have different purposes in inspection process such as measurement, detection, or inspection quantification. Finally, this research will include employing a new method with AR for transforming the training process of the next generations of bridge inspectors, who can use this technology especially with the advance of AR headsets in the future and will be the ones that can modify it best for the future of infrastructure inspections. The project will include a training phase through which the volunteer inspectors receive professional-inspection training and instructions based on the NMDOT bridge department specifications in a transformed 3D environment using AR visualization capabilities. Finally, this project will facilitate workforce development by providing basic training in AR technology and its capabilities to the engineers in NMDOT bridge department.

• Supplemental Notes:
  • 22STUNM52

Language

• English

Project

• Status: Active
• Funding: $130000
• Contract Numbers:

  69A3551747106

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Transportation Consortium of South-Central States (Tran-SET)

  Louisiana State University
  Baton Rouge, LA  United States  70803
• Project Managers:

  Mousa, Momen

• Performing Organizations:

  University of New Mexico, Albuquerque

  MSC01 1070
  Albuquerque, New Mexico  United States  87131-0001
• Principal Investigators:

  Moreu, Fernando

• Start Date: 20220401
• Expected Completion Date: 0
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Bridges; Databases; Inspection; Simulation; Training
• Subject Areas: Bridges and other structures; Data and Information Technology; Education and Training; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01844941
• Record Type: Research project
• Source Agency: Transportation Consortium of South-Central States (Tran-SET)
• Contract Numbers: 69A3551747106
• Files: UTC, RIP
• Created Date: May 9 2022 5:51AM