SPR-5013: AI-Driven Vision Inspection Analytics to Assist with Quality Control of Bridge Inspection Documentation

By leveraging INDOT’s extensive archive of inspection images and reports, the study will develop and validate an AI-driven system to support defect detection, condition assessment, and verification of inspector documentation. The deliverables include a calibrated AI model, technical reports, training materials, and a system ready for integration into INDOT’s workflow. The expected outcomes are enhanced inspection reliability, improved asset management, and reduced safety risks—advancing INDOT’s goals in innovation, safety, quality assurance, and infrastructure sustainability.

Language

• English

Project

• Status: Active
• Funding: $180,000.00
• Contract Numbers:

  SPR-5013

• Sponsor Organizations:

  Purdue University/Indiana Department of Transportation JHRP

  Purdue University
  1284 Civil Engineering Building, Room 4154
  West Lafayette, IN  United States  47907-1284
• Principal Investigators:

  Kang, Kyubyung

  Seo, Jungil

• Start Date: 20250901
• Expected Completion Date: 20270831
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Artificial intelligence; Asset management; Bridges; Inspection; Quality control
• Identifier Terms: Indiana Department of Transportation
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01966177
• Record Type: Research project
• Source Agency: Indiana Department of Transportation
• Contract Numbers: SPR-5013
• Files: RIP, STATEDOT
• Created Date: Sep 18 2025 4:01PM