Project TitleVideo-Sensor Data Fusion for Enhanced Structural Monitoring
UniversityGeorge Mason University
Principal Investigator(s)David Lattanzi (PI)
PI Contact Information
Funding Source(s) and Amounts Provided (by each agency or organization)Federal Share — $43,533
Match — $43,534
Total Project Cost$87,067
Start and End Dates09/01/2020 — 08/31/2021
Brief Description of Research ProjectSpecific 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.