Join GTI for this Transportation Speaker Series event, featuring Professor James Tsai. James Tsai will be speaking on the topic of "Smart Cities Transportation Asset Health Condition Assessment Using Emerging 3D Technology and Artifical Intellegence".
ABSTRACT: Roadway infrastructures, including pavements, bridges, and signs are deteriorating rapidly due to material aging, improper usage, harsh environments, and damages resulting from natural or man-made hazards. With the advancement of sensor technologies, it become feasible to collect the large-scale in-field detailed infrastructure data, such as 3D pavement surface data, using high-performance cameras, lasers, LiDARs, and Inertial Navigation System (INS) to gain better insight understanding of the large-scale in-filed infrastructure behavior. An intelligent sensing system will be presented, using 2D Imaging, Laser, LiDAR, and GPS/GIS Technologies with artificial intelligent and pattern recognition to automatically detect pavement surface distress, including rutting, cracking, raveling, etc. along with an innovative crack fundamental element (CFE) model that is a topological representation of cracks to support crack classification, diagnosis, and intelligent pavement management. Cases of automatic roadway health condition assessment and intelligent infrastructure system management will be presented. In addition, utilization of 3D technology for roadway safety improvement study will also be presented.
BIO: Dr. James Tsai is a professor of School of Civil and Environmental Engineering (CEE) and an adjunct professor of School of Electrical and Computer Engineering at Georgia Tech. After working as a senior research engineer in the Center of GIS at Georgia Tech for 10 years, Dr. Tsai has joined the faculty in CEE in 2007. Dr. Tsai has received his Ph.D. and MS degrees from Georgia Tech in 1994 and 1996 respectively. Dr. Tsai’s research focuses on the development of spatial information and sensing optimization methodologies, using 2D imaging, 3D Laser, LiDAR, UAV, mobile devices, and GPS/GIS technologies along with artificial intelligence and pattern recognition. Dr. Tsai and his research team have developed a large-scale pavement asset management system and it has been successfully implemented by the Georgia Department of Transportation (GDOT) to cost effectively manage its 18,000 centerline miles of highway system for the past 19 years. Dr. Tsai was selected as a Chinese Changjiang Scholar in 2009, one of the most prestigious scholar’s honor awarded by the Chinese government, in recognition of his research on applying sensor and information technology to infrastructure management. His research project, “Implementation of automatic sign and pavement condition evaluation on Georgia’s interstate highways”, sponsored by GDOT has been competitively selected to receive the 2017 AASHTO High Research Value Award. He also initiated a Smart City Infrastructure Vertically Integrated Project (VIP), an interdisciplinary and problem-solving oriented undergraduate course.