Often, advanced sensor technologies can assess highway bridge infrastructure. TRB hosted a webinar on Monday, February 22, 2021 from 2:00-3:30 PM Eastern that explored how artificial intelligence (AI) and deep learning (DL) may be used to predict the deterioration of bridges. Presenters discussed recent case studies related to the application of AI in integrating highway data to better explain and predict system performance. They also identified how AI and DL may improve sensor signal data, and explained how these technologies can provide support design, operations, and management of highway systems.

This webinar was organized by the TRB Standing Committee on Testing and Evaluation of Transportation Structures.

The slides and recording are available.

Webinar agenda and presenters

1. Introduction to AI and DL: Hoda Azari, Federal Highway Administration
2. AI in highway asset management: Devin Harris, University of Virginia
3. Emerging sensing and analytical technologies: Nora El-Gohary, University of Illinois, Urbana-Champaign
4. Future applications of AI: Shamim Pakzad, Lehigh University
5. Question and answer session: Moderated by Sreenivas Alampalli, New York State Department of Transportation (ret.)

The first 60 minutes of the webinar will be for presentations and the final 30 minutes will be reserved for audience questions.

Learning Objectives

At the end of this webinar, participants will be able to:

1. Identify current applications of AI in highway asset management
2. Identify emerging sensing and analytical technologies
3. Discuss future applications of AI in highway asset management

Professional Development Hours

Professional Development Hours (PDHs) earned on completion of this program were reported to the Registered Continuing Education Program (RCEP). Certificates of Completion are issued to all participants via the RCEP.net online system. Complaints about registered providers may be addressed to RCEP, 1015 15th Street, NW, 8th Fl., Washington, DC, 20005.