The Application of Advanced Information Technologies in Civil Infrastructure Construction and Maintenance

Information technologies have widely been used in the construction and maintenance of civil infrastructure. The advantages of information technologies provided a broader range of methods for infrastructure and enhanced its level of maintenance. However, a systematic summary of the research development of information technologies used in civil infrastructure is limited. This study aims to supplement this field by providing an objective, systematic summary of relevant literature in mainstream journals employing bibliometric retrieval and quantitative analysis from 2010 to 2020. The following results are obtained: (1) This study discusses the application of advanced information technologies in different phases and provides a critical analysis of the application of these existing information technologies, which includes wireless sensor networks (WSN), fiber optic sensing (FOS), building information modelling (BIM), radio frequency identification (RFID) and other advanced information technologies. (2) The digital twins can be used as tools for the planning and management of next-generation smart infrastructure, making the future of civil infrastructure smarter and more sustainable

A Data-Driven Approach to Trace the Development of Lean Construction in Building Projects: Topic Shift and Main Paths

Due to the varied ideas of lean philosophy adopted in the construction industry, it is challenging to trace the development of lean philosophy in terms of how the field evolved by adopting the lean ideas and how the topic shifted. However, it is challenging to extract useful information from the massive body of literature and to trace the development of Lean Construction in Building Projects. Previous studies have conducted longitudinal analyses of scientific areas depending on the authors’ interpretation and explanation, which is time-consuming and labor-intensive. To address this concern, this study proposes a data-driven approach integrating N-gram extraction, citation analysis, and a global key-route algorithm to trace the development. Based on the collected literature of Lean Construction in Building Projects, N-grams were extracted as topics from the raw texts of titles, abstracts, and keywords, and the shifts in topics were measured. Then, the references were extracted from the literature to create a citation network to represent the knowledge flows, and the global key-route algorithm was used to identify the most valuable flows reflecting the main paths of the development. The results illustrate how Lean Construction in Building Projects evolved and how the topics shifted, providing an exciting opportunity to reveal this development by using a data-driven approach rather than personal judgments. The findings can help us to understand that the field of Lean Construction in Building Projects was driven and motivated not only by the “lean theory”, but also by problems in the practice of building projects. Moreover, lean theory leads to flourishing research on informatization, and BIM will be an important tool to better achieve lean thinking in construction

The Application of Advanced Information Technologies in Civil Infrastructure Construction and Maintenance

Information technologies have widely been used in the construction and maintenance of civil infrastructure. The advantages of information technologies provided a broader range of methods for infrastructure and enhanced its level of maintenance. However, a systematic summary of the research development of information technologies used in civil infrastructure is limited. This study aims to supplement this field by providing an objective, systematic summary of relevant literature in mainstream journals employing bibliometric retrieval and quantitative analysis from 2010 to 2020. The following results are obtained: (1) This study discusses the application of advanced information technologies in different phases and provides a critical analysis of the application of these existing information technologies, which includes wireless sensor networks (WSN), fiber optic sensing (FOS), building information modelling (BIM), radio frequency identification (RFID) and other advanced information technologies. (2) The digital twins can be used as tools for the planning and management of next-generation smart infrastructure, making the future of civil infrastructure smarter and more sustainable

Foundation pit displacement monitoring and prediction using least squares support vector machines based on multi-point measurement

© 2018, The Author(s) 2018. Foundation pit displacement is a critical safety risk for both building structure and people lives. The accurate displacement monitoring and prediction of a deep foundation pit are essential to prevent potential risks at early construction stage. To achieve accurate prediction, machine learning methods are extensively applied to fulfill this purpose. However, these approaches, such as support vector machines, have limitations in terms of data processing efficiency and prediction accuracy. As an emerging approach derived from support vector machines, least squares support vector machine improve the data processing efficiency through better use of equality constraints in the least squares loss functions. However, the accuracy of this approach highly relies on the large volume of influencing factors from the measurement of adjacent critical points, which is not normally available during the construction process. To address this issue, this study proposes an improved least squares support vector machine algorithm based on multi-point measuring techniques, namely, multi-point least squares support vector machine. To evaluate the effectiveness of the proposed multi-point least squares support vector machine approach, a real case study project was selected, and the results illustrated that the multi-point least squares support vector machine approach on average outperformed single-point least squares support vector machine in terms of prediction accuracy during the foundation pit monitoring and prediction process

Schedule risks in prefabrication housing production in Hong Kong: A social network analysis

© 2016 Elsevier Ltd.Various schedule risks beset prefabrication housing production (PHP) in Hong Kong throughout the prefabrication supply chain, from design, manufacturing, logistics, to on-site assembly. Previous research on the risks in prefabrication construction projects has mainly focused on the construction stage and has been confined to issues of completeness and accuracy without consideration of stakeholder-related risks and their cause-and-effect relationships. However, in reality, the supply chain is inseparable as precast components should be manufactured and transported to sites to fit in with the schedule of on-site assembly in seamless connection manner, and most risks are interrelated and associated with various stakeholders. This study applies social network analysis (SNA) to recognize and investigate the underlying network of stakeholder-associated risk factors in prefabrication housing construction projects. Critical risks and relationships that have important roles in structuring the entire network of PHP are identified and analyzed. BIM (Building Information Modeling)-centered strategies are proposed to facilitate stakeholder communication and mitigate critical schedule risks and interactions underlying the risk network. This study not only provides an effective method to analyze stakeholder-associated risk factors and to evaluate the effect of these risk factors from a network perspective, but also offers a new visual perspective in the promotion of the use of the Internet of things (IoT) and helps identify housing construction problems in Hong Kong.Link_to_subscribed_fulltex

The application of BIM in the AECO industry

Building information Modeling (BIM) has been applied to the whole life cycle planning of construction projects, becoming the latest “engineering brain”. Currently, researches on BIM involve various stages, but most of the review fields are relatively single and lack of systematic review and analysis. In order to comprehensively analyze the research trend of BIM in the field of engineering management, this paper takes the holistic analysis method as the framework. In the first stage, 2066 research projects were quantitatively analyzed by bibliometrics to clarify their research environment. In the second stage, scientometric analysis method is adopted to identify scholars, countries, key words and journal sources that have achieved fruitful results and influence in BIM research, and to clarify the research environment. In the last stage, indepth qualitative discussion is carried out to achieve three objectives: (1) to divide the whole life cycle of the article and summarize the research hotspots in each stage; (2) identify BIM application problems; (3) determine the future research direction. This work is helpful for researchers and practitioners in this field to quickly find influential and fruitful research or journals, and to understand the current research hot spots and trends for the next research planning