Video-Sensor Data Fusion for Enhanced Structural Monitoring

Specific sub-objectives of this project include: 1. Identification and refinement of an optimal computer vision method for infrastructure monitoring 2. An approach to image measurement that supports data fusion 3. A data fusion algorithm capable learning the statistical associations between full field video measurements and sensor data 4. Experimental validation of all algorithms Impact on Practice The proposed research has the potential for significant impact on practice and is in direct alignment with the Center's mission for improving integrated asset management for condition assessment of infrastructure such as highway and rail bridges using remote sensing-based measurements. The research will advance efforts to understand the best approaches for implementing computer vision in asset management. In particular, achievement of the project sub-objectives will provide engineers with best practices for camera-based monitoring, and will explore how such technologies can be used to supplement the many monitoring systems that are already employed by infrastructure managing agencies. These monitoring technologies do not require specialized and sophisticated equipment, further facilitating the potential for rapid implementation


    • English


    • Status: Active
    • Funding: $GMU Fed Core $43,533 GMU Match $43,534
    • Contract Numbers:


    • 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:

      Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)

      Pennsylvania State University
      University Park, PA  United States  16802
    • Project Managers:

      Donnell, Eric

    • Performing Organizations:

      George Mason University

      School of Engineering
      CEIE Dept., MSN-6C1
      Faifax, VA  United States  22030
    • Principal Investigators:

      Lattanzi, David

    • Start Date: 20200901
    • Expected Completion Date: 20210831
    • Actual Completion Date: 20220428
    • USDOT Program: University Transportation Centers Program

    Subject/Index Terms

    Filing Info

    • Accession Number: 01751311
    • Record Type: Research project
    • Source Agency: Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)
    • Contract Numbers: 69A3551847103
    • Files: UTC, RIP
    • Created Date: Sep 2 2020 6:26PM