Automated Interpretation of Culvert Inspection Videos Using Artificial Intelligence and Computer Vision

This research will automate the interpretation process of culvert inspection videos, allowing it to be more efficient and resource-saving.

Language

Status: Active
Funding: $50000
Contract Numbers:
24-8333
Sponsor Organizations:
Utah Department of Transportation

Research and Innovation Division
Salt Lake City, UT United States 84114
Managing Organizations:
Utah Department of Transportation

Research and Innovation Division
Salt Lake City, UT United States 84114
Project Managers:
Loveless, Brad

(801) 940-2583

bloveless@utah.gov

Nichol, Kevin

(801) 870-4033

knichol@utah.gov
Performing Organizations:
University of Utah

Department of Civil and Environmental Engineering
110 Central Campus Drive Suite 2000
Salt Lake City, UT United States 84112
Principal Investigators:
Rashidi, Abbas

Univ. of Utah

abbas.rashidi@utah.edu
Start Date: 20230919
Expected Completion Date: 20250915
Actual Completion Date: 0
USDOT Program: Transportation Performance Management, Asset Management, and Maintenance

TRT Terms: Artificial intelligence; Computer vision; Culverts; Information processing; Inspection; Video
Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation;