INSPIRE Archived Webinars
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Webinar Date
23 Mar 2021, 10 am
Abstract
Advancements in sensor, Artificial Intelligence (AI), and robotic technologies have formed a foundation to enable a transformation from traditional engineering systems to complex adaptive systems. This paradigm shift will bring exciting changes to civil infrastructure systems and their builders, operators and managers. Funded by the INSPIRE University Transportation Center (UTC), Dr. Qin’s group investigated the holism of an AI-robot-inspector system for bridge inspection. Dr. Qin will discuss the need for close collaboration among the constituent components of the AI-robot-inspector system. In the workplace of bridge inspection using drones, the mobile robotic inspection platform rapidly collected big inspection video data that need to be processed prior to element-level inspections. She will illustrate how human intelligence and artificial intelligence can collaborate in creating an AI model both efficiently and effectively. Obtaining a large amount of expert-annotated data for model training is less desirable, if not unrealistic, in bridge inspection. This INSPIRE project addressed this annotation challenge by developing a semi-supervised self-learning (S3T) algorithm that utilizes a small amount of time and guidance from inspectors to help the model achieve an excellent performance. The project evaluated the improvement in job efficacy produced by the developed AI model. This presentation will conclude by introducing some of the on-going work to achieve the desired adaptability of AI models to new or revised tasks in bridge inspection as the National Bridge Inventory includes over 600,000 bridges of various types in material, shape, and age.
Biography
Dr. Ruwen Qin is an Associate Professor of Civil Engineering at Stony Brook University. She received her Ph.D. degree in Industrial Engineering and Operations Research from Pennsylvania State University - University Park. Her research focuses on creating analytics and systems methods for forming, operating, and coordinating complex adaptive systems such as cyber-physical-human systems, smart connected systems, and intelligent automation systems. Her research has been sponsored by National Science Foundation, U.S. Department of Transportation, Department of Education, state Departments of Transportation, and industries. She is a member of IEEE, INFORMS, and ASEM.
Recommended Citation
Qin, Ruwen, "Human-Robot Collaboration for Effective Bridge Inspection in the Artificial Intelligence Era" (2021). INSPIRE Archived Webinars. 15.
https://scholarsmine.mst.edu/inspire_webinars/15
Department(s)
Civil, Architectural and Environmental Engineering
Research Center/Lab(s)
INSPIRE - University Transportation Center
Document Type
Video - Presentation
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2021 Missouri University of Science and Technology, All rights reserved.
