CIT Spotlight
Zhenhua Zhu: Detecting and Assessing Damage and Defects in Civil Infrastructure
An expert in machine vision technologies for automating the assessment of civil infrastructure, Ph.D. candidate Zhenhua Zhu joined the School of Civil and Environmental Engineering at Georgia Tech in 2009.
Zhu’s research topic is “Machine Vision-Based Concrete Column Recognition and Crack Properties Retrieval”. The research is collaborated with the Georgia Search & Rescue team in the Fulton County Fire Department and it is financially supported by the National Science Foundation. The goal of this project is to automatically evaluate the safety of entry into a reinforced concrete structure for emergency responders and residents. So far, a rapid building safety evaluation framework has been proposed. The prototype can collect videos of a concrete structure, recognize its critical load bearing members, detect the cracks on the members, and calculate the crack properties. The work of assessing the damage states of the members is being integrated into the prototype.
Prior to joining Georgia Tech, Zhenhua holds a B.E. in civil engineering and an M.E. in computer science and technology. Zhenhua Zhu is an active member in several academic and professional organizations, and officially serves as a reviewer for ASCE journals including the Journal of Construction Engineering and Management and the Journal of Computing in Civil Engineering. In 2009, he received the Best Paper Award of the ASCE Construction Research Congress.
Abbas Rashidi: Reciprocal Reconstruction and Recognition of constructed facilities
Abbas Rashidi is a second year PhD student at School of Building Construction. He joined Construction Information Technology Library(CITL) in fall 2009.
Currently he is working under supervision of professor Ioannis Brilakis and professor Patricio Vela. His research topic is “Reciprocal Reconstruction and Recognition for 3D modeling of constructed facilities.
The objectives of this research, which is supported by the National Science Foundation, directly address two of the greatest challenges identified by the “National Academy of Engineering” grand challenges in infrastructure: (1) the need for more automation in construction, through advances in computer science and robotics, and (2) the lack of viable methods to map and label existing infrastructure.
The motivation behind this project which is supported bye National Science Foundation stems from the need for viable methods to map and label existing infrastructure.
The project is expected to generate the as-built geometric object model of buildings by combining 3D reconstruction and recognition concepts in a reciprocal manner. The contribution of this project is that, instead of manually recognizing each element every time it is encountered, we need only recognize its characteristics once and automatically detect it each subsequent time.
Abbas Rashidi received his M.S. in Construction Engineering and Management from Amirkabir University of Technology, Tehran, Iran. Prior to joining CITL, he worked as a lecturer at Islamic Azad University of Iran from 2004-09. At the same time, he was a consultant in the field of project planning and scheduling for a number of construction projects in Iran. Joining CITL, provided him a great opportunity to work on a number of the most state of the art research projects in the field. It also helped him to expand his knowledge on applications of information technologies in construction industry.
Man Woo Park: Automated 3D Vision Tracking
A Ph.D. candidate in Civil & Environmental Engineering at Georgia Institute of Technology, Man Woo Park joined Construction Information Technology Laboratory (CITL) in spring 2009.
Since his main research interest was the sensing technologies in civil engineering, it was a great chance for him to work with his advisor Dr. Brilakis in CITL.
Park’s Ph.D. research topic is “Automated 3D Vision Tracking of Construction Resources and Vehicles” which is associated with the NSF CMMI project. The proposed 3D vision tracking is the integration of the various major machine vision technologies. It includes camera calibration, object recognition, 2D vision tracking, and 3D reconstruction. To get involved and take the main position in the project, Park took Computer Science and Electrical Engineering courses with excellent grades while acquiring the knowledge of the essential machine vision theories.
One of the greatest challenges noted by the report is the need for more automation in construction, through advances in computer science and robotics. Automated tracking of project related entities in construction sites is one of the topics in this area. Automated 3D vision tracking has great advantages to be used in construction. It can track a large number of construction entities in a congested large-scale site without requiring the installation of tags or sensors on the entities. The equipment required is only a set of two or more cameras and the computer for saving and processing the incoming video data. Hence, it could be a cost-effective technology.
Prior to joining CITL, Park had studied and worked on the structural engineering. He obtained his MS in 2003 at the Department of Civil and Environmental Engineering at Seoul National University. His master thesis was about System Identification which is applicable to structural damage detection. After graduation, he had worked for a civil engineering company as a structural engineer in South Korea for four years. He participated in the projects of rail construction, road construction and subway station construction working on various types of work ranging from the fundamental design to the detailed structural analysis.