Intelligent and Computer Technologies Application in Construction II

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: closed (10 December 2023) | Viewed by 10592

Special Issue Editors


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Guest Editor
School of Civil Engineering, Tsinghua University, Beijing 100190, China
Interests: intelligent construction; virtual construction (VC)/virtual prototyping (VP); building information modeling (BIM); digital construction security management
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Civil Engineering, Tsinghua University, Beijing, China
Interests: intelligent design; construction process modeling; building information model (BIM); machine learning; digital twin
Special Issues, Collections and Topics in MDPI journals
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
Interests: construction engineering; construction informatics and automation; occupational safety and health
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The construction industry has long been an engine of global economic growth. Despite the boom, the construction industry is faced with many challenges, such as lagging productivity, labor sustainability, and environmental sustainability. Considering the above challenges, industrial transformation and upgrading have become critical for the continuous and healthy development of the construction industry.

Intelligent construction provides a solution to these challenges. In the past two decades, we have witnessed significant efforts in leveraging intelligent and computer technologies to enhance the construction project delivery process. Examples include but are not limited to smart site supervision, construction robotics, automatic safety, and health management with the IoT. Intelligent construction is a complicated topic related to the whole life cycle of a project. With the advancement of intelligent and computer technologies, there is still room for researchers and industry practitioners to further facilitate digital and intelligent transformation in construction.

This Special Issue aims to provide a platform to explore state-of-the-art knowledge, practical implementation, and cutting-edge innovations in the area of intelligent and computer technologies’ application in construction.

Dr. Hongling Guo
Dr. Jia-Rui Lin
Dr. Yantao Yu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent construction
  • construction robotics
  • internet of things
  • computer vision
  • blockchains
  • deep learning
  • artificial intelligence
  • 3D printing
  • building information modeling
  • digital twin

Published Papers (5 papers)

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22 pages, 10403 KiB  
Article
Aesthetic Assessment of Free-Form Space Structures Using Machine Learning Based on the Expert’s Experiences
by Yaser Shahbazi, Mahsa Ghofrani and Siamak Pedrammehr
Buildings 2023, 13(10), 2508; https://doi.org/10.3390/buildings13102508 - 3 Oct 2023
Cited by 3 | Viewed by 993
Abstract
Parametric form findings of free-form space structures and qualitative assessment of their aesthetics are among the concerns of architects. This study aims to evaluate the aesthetic aspect of these structures using ML algorithms based on the expert’s experiences. First, various datasets of forms [...] Read more.
Parametric form findings of free-form space structures and qualitative assessment of their aesthetics are among the concerns of architects. This study aims to evaluate the aesthetic aspect of these structures using ML algorithms based on the expert’s experiences. First, various datasets of forms were produced using a parametric algorithm of free-form space structures written in Grasshopper. Then, three multilayer perceptron ANN models were adjusted in their most optimal modes using the results of the preference test based on the aesthetic criteria including simplicity, complexity, and practicality. The results indicate that the ANN models can quantitatively evaluate the aesthetic value of free-form space structures. Full article
(This article belongs to the Special Issue Intelligent and Computer Technologies Application in Construction II)
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27 pages, 5919 KiB  
Article
Data-Driven Quantitative Performance Evaluation of Construction Supervisors
by Cheng Yang, Jia-Rui Lin, Ke-Xiao Yan, Yi-Chuan Deng, Zhen-Zhong Hu and Cheng Liu
Buildings 2023, 13(5), 1264; https://doi.org/10.3390/buildings13051264 - 11 May 2023
Viewed by 2018
Abstract
The performances of construction supervisors are essential for the monitoring, control, and coordination of the construction process of a project in order to adhere to a predefined schedule, cost, quality and other factors. However, it is challenging to evaluate their performance due to [...] Read more.
The performances of construction supervisors are essential for the monitoring, control, and coordination of the construction process of a project in order to adhere to a predefined schedule, cost, quality and other factors. However, it is challenging to evaluate their performance due to limitations such as data deficiency, human error, etc. Thus, this paper proposes an approach to data-driven quantitative performance evaluation of construction supervisors by integrating an analytic hierarchy process (AHP) and activity tracking. The proposed approach contains three parts, namely, index extraction, weighting, data-driven index calculation, and then validation by case study. Firstly, performance indexes were developed based on a literature review as well as surveys and function analysis of the information system for construction supervision (CSI system). Then, the weights of and relationships among of the indexes are determined by AHP. After that, with daily workflow and inspection activities tracked in the CSI system, a method and a software module for automatic calculation of indexes were developed. Lastly, the proposed approach was validated by a real-world case. The result showed that the proposed approach can quantify the performance of a construction supervisor systematically and automatically, which shed lights on how to evaluate the performance of a worker based on the tracking of daily activities. The data-driven process enhanced our strong interpretation of member actions and evaluation indexes, and can boost the performance of every member in an organization. Full article
(This article belongs to the Special Issue Intelligent and Computer Technologies Application in Construction II)
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20 pages, 13486 KiB  
Article
Automatic Generation Construction Shop Design Model of the MEP Hanger Based on BIM
by Jinxin Hu, Quanxi Bao, Tuanjie Zhou, Kun Li, Liang Shang, Jicang Zhang and Xuehai Fu
Buildings 2023, 13(4), 867; https://doi.org/10.3390/buildings13040867 - 26 Mar 2023
Cited by 1 | Viewed by 2159
Abstract
Due to the growing complexity of mechanical, electrical and plumbing (MEP) functions, the design, production and installation of hanger based on MEP has become low efficiency in traditional ways. Compared with the Computer-Aided Design (CAD) approach, the MEP hanger three-dimensional (3D) design approach [...] Read more.
Due to the growing complexity of mechanical, electrical and plumbing (MEP) functions, the design, production and installation of hanger based on MEP has become low efficiency in traditional ways. Compared with the Computer-Aided Design (CAD) approach, the MEP hanger three-dimensional (3D) design approach has not received adequate attention in the process of engineering practice. Based on Building Information Modeling (BIM) and Revit secondary development technology, an automatic generation construction shop design model system of MEP hanger (MEP hanger-CDM) for the quick placement of hanger components, automatic grouping of hanger components and hanger component constructability checking was developed. By conducting investigations with the construction companies and construction sites in China, four basic forms of MEP hanger layouts were identified to accommodate different types of MEP layouts. In addition, the design requirements of the family of LOD 400 BIM models were summarized along with the analysis of user requirements. The results of the case studies indicate a 70% reduction in the manpower number on the MEP hanger shop design and an 85.9% reduction in the number of working hours. Moreover, the efficiency of the hanger construction model design and the accuracy of the output of material lists and shop drawings could be improved. Thus, the process of designing MEP hanger could be optimized in a visualized method. Full article
(This article belongs to the Special Issue Intelligent and Computer Technologies Application in Construction II)
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20 pages, 4358 KiB  
Article
Autonomous Concrete Crack Semantic Segmentation Using Deep Fully Convolutional Encoder–Decoder Network in Concrete Structures Inspection
by Rundong Pu, Guoqian Ren, Haijiang Li, Wei Jiang, Jisong Zhang and Honglei Qin
Buildings 2022, 12(11), 2019; https://doi.org/10.3390/buildings12112019 - 18 Nov 2022
Cited by 6 | Viewed by 2680
Abstract
Structure health inspection is the way to ensure that structures stay in optimum condition. Traditional inspection work has many disadvantages in dealing with the large workload despite using remote image-capturing devices. This research focuses on image-based concrete crack pattern recognition utilizing a deep [...] Read more.
Structure health inspection is the way to ensure that structures stay in optimum condition. Traditional inspection work has many disadvantages in dealing with the large workload despite using remote image-capturing devices. This research focuses on image-based concrete crack pattern recognition utilizing a deep convolutional neural network (DCNN) and an encoder–decoder module for semantic segmentation and classification tasks, thereby lightening the inspectors’ workload. To achieve this, a series of contrast experiments have been implemented. The results show that the proposed deep-learning network has competitive semantic segmentation accuracy (91.62%) and over-performs compared with other crack detection studies. This proposed advanced DCNN is split into multiple modules, including atrous convolution (AS), atrous spatial pyramid pooling (ASPP), a modified encoder–decoder module, and depthwise separable convolution (DSC). The advancement is that those modules are well-selected for this task and modified based on their characteristics and functions, exploiting their superiority to achieve robust and accurate detection globally. This application improved the overall performance of detection and can be implemented in industrial practices. Full article
(This article belongs to the Special Issue Intelligent and Computer Technologies Application in Construction II)
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21 pages, 6724 KiB  
Case Report
Digital-Twin-Based High-Precision Assembly of a Steel Bridge Tower
by Jiulin Li, Qingquan Li, Qingzhou Mao and Hao Xu
Buildings 2023, 13(1), 257; https://doi.org/10.3390/buildings13010257 - 16 Jan 2023
Cited by 3 | Viewed by 1791
Abstract
Steel structures that benefit from having lightweight, ductility, and seismic behaviors are capable of improving the overall performance of civil engineering in environmental protection, project quality, process management, and ease of construction, making the procedure more feasible for builders. The application of steel [...] Read more.
Steel structures that benefit from having lightweight, ductility, and seismic behaviors are capable of improving the overall performance of civil engineering in environmental protection, project quality, process management, and ease of construction, making the procedure more feasible for builders. The application of steel structure techniques has been widely used in bridges, tall buildings, and complex projects around the world. Increasing demand for planning and design has led to structural projects upgrading in structural complexity and geometrical irregularity. However, steel structure projects are still limited by the principal disadvantage of susceptibility to deformation. Therefore, the challenges of the assembly and manufacturing process for steel structures are important. In this paper, to achieve full-loop tracking and control of the assembly and manufacturing process, we propose an integrated approach to undertake the aforementioned challenges via digital twin technology, which combines three modules: (1) deformation detection, (2) pose estimation and optimization, and (3) deformation correction and pose control. This proposed methodology innovatively merges gravitational deformation analysis with geometrical error analysis. Furthermore, the validity of this method’s implementation is demonstrated by the New Shougang Bridge project. The results show that the assembly precision satisfies the standard of less than H/4000, nearing H/6000. Moreover, the elevation difference is less than 20 mm, which satisfies the control precision of the geometric pose. The new method that we propose in this paper provides new ideas for structural deformation control and high-precision assembly, as it realizes dynamic deformation sensing, real-time deviation analysis and manufacturing, and efficient optimization of the assembly process. Full article
(This article belongs to the Special Issue Intelligent and Computer Technologies Application in Construction II)
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