Smart Feedback System for Bridge Asset Management through the Development of Generating Artificial Intelligence Network (GAIN) Members

The research team proposes developing smart bridge components, such as girders, equipped with sensors and/or computer vision technologies to generate data for analysis using artificial intelligence (AI). These components, referred to as Generating Artificial Intelligence Network (GAIN) members, will provide bridge owners with enhanced asset management information. GAIN members will supply data to the bridge network, offering real-world feedback. When deployed at strategic locations, both at the state level and nationwide, GAIN members could deliver valuable insights into state and national networks, supporting bridge construction, mobility, welfare operations, and emergency evacuations. The anticipated benefits of such a system include monitoring performance metrics (e.g., temperature and strain in steel and concrete) during fabrication, construction (e.g., pile driving), and service, including live load/performance monitoring. The information collected can inform state bridge owners on quality assurance during fabrication and construction, as well as maintenance, repair, and replacement (MRR) decisions.

• Record URL:
  • https://abc-utc.fiu.edu/smart-feedback-system-for-bridge-asset-management-through-the-development-of-generating-artificial-intelligence-network-gain-members-2/

Language

• English

Project

• Status: Active
• Funding: $69,000.00
• Contract Numbers:

  69A3552348322

• Sponsor Organizations:

  Innovative Bridge Technologies/Accelerated Bridge Construction University Transportation Center (IBT/ABC-UTC)

  Florida International University
  Miami, FL  United States 

  Office of the Assistant Secretary for Research and Technology

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

  University of Georgia Research Foundation (UGARF)

  310 E. Campus Rd.,
  Athens, GA  United States  30602
• Principal Investigators:

  Chorzepa, Mi

• Start Date: 20250101
• Expected Completion Date: 0
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Artificial intelligence; Asset management; Bridges; Data collection; Monitoring; Sensors
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01973313
• Record Type: Research project
• Source Agency: Innovative Bridge Technologies/Accelerated Bridge Construction University Transportation Center (IBT/ABC-UTC)
• Contract Numbers: 69A3552348322
• Files: UTC, RIP
• Created Date: Dec 2 2025 4:29PM