Structural health monitoring of concrete bridges requires accurate and efficient surface crack detection. Early detection of cracks helps prevent further damage. Safety inspection tests are conducted at regular intervals to assess deterioration. Traditional methods involve detection of cracks by human visual inspection. These methods are costly, inefficient and labor intensive, especially for long-span bridges. This thesis presents the use of computer vision and pattern recognition techniques in assessment of cracks on a concrete bridge surface. Bridge deck images are first collected using high-resolution cameras mounted on a robot. Statistical inference algorithms are then implemented to build an automated crack detection system. The proposed machine learning method reduces manual effort and enables automatic labeling over large bridge deck areas to quantify size and location for future reference or comparisons. A panoramic camera is used for the purpose of context localization. Additionally, we demonstrate image-stitching to obtain a coherent spatial mosaic of the bridge deck.

This proceedings book focuses on innovation, cooperation, and sustainable development in the fields of construction management and real estate. The book provides a detailed analysis and description of the disciplinary frontiers in the field of building management and real estate and how they can be promoted in the context of the epidemic. A wide variety of papers provide a reference value for both scholars and practitioners. The proceedings book is the documentation of “the 25th International Symposium on Advancement of Construction Management and Real Estate” (CRIOCM 2020), which was held at the School of Public Administration, Central China Normal University, Wuhan, China, in 2020.

This book of CRIOCM 2021 (26th International Conference on Advancement of Construction Management and Real Estate) presents the latest developments in real estate and construction management around the globe. The conference was organized by the Chinese Research Institute of Construction Management (CRIOCM) working in close collaboration with Tsinghua University. Written by international academics and professionals, the book discusses the latest achievements, research findings and advances in frontier disciplines in the field of construction management and real estate. Covering a wide range of topics, including building information modeling, big data, geographic information systems, housing policies, management of infrastructure projects, intelligent construction and smart city, real estate finance and economics and urban planning and sustainability, the discussions provide valuable insights into the implementation of advanced construction project management and real estate market in China and abroad. The book offers an outstanding resource for academics and professionals.

Infrastructure Computer Vision delves into this field of computer science that works on enabling computers to see, identify, process images and provide appropriate output in the same way that human vision does. However, implementing these advanced information and sensing technologies is difficult for many engineers. This book provides civil engineers with the technical detail of this advanced technology and how to apply it to their individual projects. Explains how to best capture raw geometrical and visual data from infrastructure scenes and assess their quality Offers valuable insights on how to convert the raw data into actionable information and knowledge stored in Digital Twins Bridges the gap between the theoretical aspects and real-life applications of computer vision

Bridge decks deteriorate over time as a result of deicing salts, freezing-and-thawing, and heavy use, resulting in internal defects. According to a 2006 study by the American Society of Civil Engineers, 29% of bridges in the United States are considered structurally deficient or functionally obsolete. Ground penetrating radar (GPR) is a promising non-destructive evaluation technique for assessing subsurface conditions of bridge decks. However, the analysis of GPR scans is typically done manually, where the accuracy of the detection process depends on the technician's trained eye. In this work, a framework is developed to automate the detection, locailzation, and characterization of subsurface defects inside bridge decks. This framework is composed of a fractal-based feature extraction algorithm to detect defective regions, a deconvolution algorithm using banded-ICA to reduce overlapping between reflections and to estimate the depth of defects, and a classification algorithm using principal component analysis to identify main features in defective regions. This framework is implemented and simulated using MATLAB and GPR real scans of simulated concrete bridge decks. This framework, as demonstrated by the experimental results, has the following contributions to the current body of knowledge in ground penetrating radar detection and analysis techniques, and in concrete bridge deck condition assessment: 1) developed a framework that integrated detection, localization, and classificationof subsurface defects inside concrete bridge decks, 2) presented a comparison between the most common fractal methods to determine the most suitable one for bridge deck condition assessment, 3) introduced a fractal-based feature extraction algorithm that is capable of detecting and horizontally labeling defective regions using only the underlying GPR B-scan without the need for a training dataset, 4) developed a deconvolution algorithm using EFICA to detect embedded defects in bridge decks, 5) introduced an automated identification methodology of defective regions which can be integrated into a CAD system that allows for better visual assessment by the maintenance engineer and has the potential to eliminate human interpretation errors and reduce condition assessment time and cost, and 6) presented an investigation and a successful attempt to classify some of the common defects in bridge decks.

This book highlights the latest advancements in the use of automated systems in the design, construction, operation and future of the built environment and its occupants. It considers how the use of automated decision-making frameworks, artificial intelligence and other technologies of automation are presently impacting the practice of architects, engineers, project managers and contractors, and articulates the near future changes to workflows, legal frameworks and the wider AEC industry. This book surveys and compiles the use of city apps, robots that operate buildings and fabricate structural elements, 3D printing, drones, sensors, algorithms, and advanced prefabricated modules. The book also contributes to the growing literature on smart cities, and explores the impacts on data privacy and data sovereignty that arise through the use of sensors, digital twins and intelligent transport systems. It provides a useful reference for further research and development in the area of automation in design and construction to architects, engineers, project managers, superintendents and construction lawyers, contractors, policy makers, and students.