Special Issue "Data-Driven and Intelligent Decision Support Systems in Digitized Construction"

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 (31 December 2022) | Viewed by 12409

Special Issue Editors

Dr. Zhen Lei
E-Mail Website
Guest Editor
Offsite Construction Research Centre (OCRC), Department of Civil Engineering, University of New Brunswick, Fredericton, NB, Canada
Interests: offsite construction; prefabricated construction; digital technologies in construction; data analytics and decision making in construction; building information modeling (BIM) and virtual design and construction (VDC)
Special Issues, Collections and Topics in MDPI journals
Dr. SangHyeok Han
E-Mail Website
Guest Editor
Building, Civil and Environmental Engineering, Concordia University, Montreal, QC, Canada
Interests: automation in construction; equipment management; modular construction; BIM
Dr. Hexu Liu
E-Mail Website
Guest Editor
Department of Civil and Construction Engineering, Western Michigan University, Kalamazoo, MI, USA
Interests: off-site construction; Building Information Modelling (BIM); BIM-GIS asset management; human-centered AR/VR/AI application
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

The construction industry has been stagnant in terms of efficiency and productivity for the past two decades, especially if compared to other industry sectors (e.g., manufacturing). However, the recent development of digital technologies enables the construction industry to make use of data-driven systems to improve its decision-making processes and construction efficiency. In particular, various digital applications have been developed in aiding this digital transformation: the Internet-of-things (IoT), simulation and optimization-based systems, machine learning and artificial intelligence, among others. Potential submission candidates of this Special Issue include: (1) smart data collection systems in construction (e.g., IoT applications, image/vision-based); (2) real-time/near-real-time decision-making systems (e.g., optimization, simulation); (3) hybrid data visualization systems in construction (e.g., dashboard systems, virtual reality/augmented reality/mixed reality/augmented virtuality); and (4) frameworks for construction digitization implementation and strategies.

Dr. Zhen Lei
Dr. SangHyeok Han
Dr. Hexu Liu
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 2000 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

  • Internet-of-Things (IoT) in construction
  • Sensors and wearables
  • Computer vision and imaging processing
  • Artificial intelligence (AI) and Machine Learning (ML)
  • Simulation and optimization in construction
  • Augmented/virtual/mixed reality and immersive environments
  • Digital twin and cyber physical systems
  • Blockchain and smart contracts
  • Building information modelling (BIM)/Virtual Design and Construction (VDC)
  • Decision support systems
  • Roadmaps, frameworks and strategies of digitization in construction industry

Published Papers (10 papers)

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Research

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Article
MODI: A Structured Development Process of Mode-Based Control Algorithms in the Early Design Stage of Building Energy Systems
Buildings 2023, 13(2), 267; https://doi.org/10.3390/buildings13020267 - 17 Jan 2023
Viewed by 352
Abstract
The growing share of renewable energy sources in building energy systems leads to more complex energy conversion and distribution systems. The current process of developing appropriate control functions for energy systems is insufficient and consequently error-prone. Regarding this problem, a new method is [...] Read more.
The growing share of renewable energy sources in building energy systems leads to more complex energy conversion and distribution systems. The current process of developing appropriate control functions for energy systems is insufficient and consequently error-prone. Regarding this problem, a new method is expected to systematically develop appropriate control functions for buildings and reduce design errors in this process. This paper introduces the MODI method, aiming at a structured development process of mode-based control algorithms to reduce errors in the early design stages of buildings. A complete framework and a standardized application process of the MODI method will be established to systematically design mode-based control algorithms described through signal-interpreted Petri nets. Furthermore, we performed a simulation-assisted evaluation approach to test and improve the performance of the control algorithms generated by MODI. In a case study, we applied MODI to develop a mode-based control strategy for an energy system containing heating and cooling supply networks. The desired control strategy was tested and tuned in a simulation phase. Compared to a reference control, the mode-based control algorithm shows an improvement in system efficiency by 4% in winter and 8% during the transitional season phase. Full article
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Article
Bayesian Network Models for Evaluating the Impact of Safety Measures Compliance on Reducing Accidents in the Construction Industry
Buildings 2022, 12(11), 1980; https://doi.org/10.3390/buildings12111980 - 15 Nov 2022
Cited by 1 | Viewed by 502
Abstract
Construction is one of the most hazardous industries worldwide. Implementing safety regulations is the responsibility of all parties involved in a construction project and must be performed systematically and synergistically to maximize safety performance and reduce accidents. This study aims to examine the [...] Read more.
Construction is one of the most hazardous industries worldwide. Implementing safety regulations is the responsibility of all parties involved in a construction project and must be performed systematically and synergistically to maximize safety performance and reduce accidents. This study aims to examine the level of safety compliance of construction personnel (i.e., top management, frontline supervisors, safety coordinators/managers, and workers) to gain insight into the top safety measures that lead to no major or frequent accidents and to predict the likelihood of having a construction site free of major or frequent accidents. To achieve the objectives, five safety measures subsets were collected and modeled using six combinations of five different Bayesian networks (BNs). The performance of these model classifiers was compared in terms of accuracy, sensitivity, specificity, recall, precision, F-measure, and area under the receiver operating characteristic curve. Then, the best model for each data subset was adopted. The inference was then performed to identify the probability of the commitment to safety measures to reduce major or frequent accidents and recommend enhancement regulations and practices. While the context in this paper is the Jordanian construction industry, the novelty of the work lies in the BN modeling methodology and recommendations that any country can adopt for evaluating the safety performance of its construction industry. This research endeavor is, therefore, a significant step toward providing knowledge about the top safety measures associated with reducing accidents and establishing efficiency comparison benchmarks for improving safety performance. Full article
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Article
Software Architecture and Non-Fungible Tokens for Digital Twin Decentralized Applications in the Built Environment
Buildings 2022, 12(9), 1447; https://doi.org/10.3390/buildings12091447 - 14 Sep 2022
Viewed by 1303
Abstract
Blockchain technology (BCT) can enable distributed collaboration, enhance data sharing, and automate back-end processes for digital twin (DT) decentralized applications (dApps) in the construction industry (CI) 4.0. The aim of this paper was to propose a software architecture and to develop a framework [...] Read more.
Blockchain technology (BCT) can enable distributed collaboration, enhance data sharing, and automate back-end processes for digital twin (DT) decentralized applications (dApps) in the construction industry (CI) 4.0. The aim of this paper was to propose a software architecture and to develop a framework of smart contracts for blockchain-based digital twin (BCDT) dApps throughout the lifecycle of projects in CI 4.0. This paper leveraged the existing literature and action research interviews to identify and validate the critical industry problems, functional requirements (FRs), and non-functional requirements (NFRs) to be addressed by BCDT dApps in CI 4.0. Basic use cases were developed to design a framework of smart contracts for BCDT dApps throughout the lifecycle of projects. The analysis of an online survey was used to identify the key requirements and enablers to propose a software architecture for BCDT applications and to validate the requirements for developing the framework of a smart contract for BCDTs. The findings were: (1) The identification of key problems in CI 4.0 for each BIM/BCDT dimension (3D, 4D, 5D, 6D, 7D, 8D, and contractual (cD)) and the related FRs and NFRs for BCDT applications. Additionally, key use cases were designed to address the problems identified. (2) The proposed BCDT architecture permitted us to narrow gaps in the literature on blockchain-based decentralized digital twins. Moreover, the proposed BCDT architecture and smart-contract framework addressed the main requirements in the literature on BCDTs. (3) The study leveraged the non-fungible token (NFT) standard to develop a framework for smart contracts that addressed the key use cases and the related industry problems and functional requirements that were identified. The study also considered the contractual dimension (cD) as an overarching dimension in relation to the other BCDT dimensions. (4) We also compared the costs of several public blockchains for executing the proposed smart-contract framework throughout the lifecycle of a medium-sized building project. The cost analysis permitted the development of criteria to evaluate the suitability of blockchain networks for BCDT applications in CI 4.0 depending on the principal blockchain networks’ properties (security, decentralization, scalability, and interoperability). Finally, this study resulted in a novel framework that included software architecture, smart-contract use cases, and selection criteria among blockchain networks for BCDT dApps in CI 4.0. Full article
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Article
Integration of Building Information Modeling (BIM) and Virtual Design and Construction (VDC) with Stick-Built Construction to Implement Digital Construction: A Canadian General Contractor’s Perspective
Buildings 2022, 12(9), 1337; https://doi.org/10.3390/buildings12091337 - 31 Aug 2022
Cited by 1 | Viewed by 1216
Abstract
Building information modeling (BIM) and virtual design and construction (VDC) are useful management processes and methodologies to enhance project communication and coordination. Over the past few decades, researchers and practitioners have made efforts to promote the adoption of BIM and VDC in the [...] Read more.
Building information modeling (BIM) and virtual design and construction (VDC) are useful management processes and methodologies to enhance project communication and coordination. Over the past few decades, researchers and practitioners have made efforts to promote the adoption of BIM and VDC in the construction industry. However, currently, the promotion and adoption of BIM and VDC are relatively slow in North America. This paper focuses on developing an approach to drive the adoption of the technologies through cooperation among project stakeholders and proposing a method of collaboration through a case study. In this paper, the authors surveyed and interviewed a major Canadian general contractor on its implementation of BIM and VDC in construction projects. The was to benchmark the status of BIM and VDC applications in the Atlantic region of Canada from a general contractor’s perspective. Both surveys and interviews were conducted with various project participants throughout the organization. Based on the results, a “Digital Construction Framework for the Future” is proposed to increase the adoption of BIM and VDC. This research can provide a general understanding of BIM and VDC adoption in this particular general contractor and areas of improvement in transitioning to a more digital working construction environment. Full article
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Article
A Predictive Analytics Framework for Mobile Crane Configuration Selection in Heavy Industrial Construction Projects
Buildings 2022, 12(7), 960; https://doi.org/10.3390/buildings12070960 - 05 Jul 2022
Viewed by 643
Abstract
Predictive analytics have been used to improve efficiency and productivity in the construction industry by leveraging the insights from historical data with a variety of applications in project management. In the planning process of heavy industrial construction projects, mobile crane selection plays a [...] Read more.
Predictive analytics have been used to improve efficiency and productivity in the construction industry by leveraging the insights from historical data with a variety of applications in project management. In the planning process of heavy industrial construction projects, mobile crane selection plays a critical role in the project’s success, and poor choice of mobile crane configurations can lead to unnecessary cost-overrun and delayed schedules. In this research, the authors propose a predictive analytics framework for crane configuration selection using combined heuristic search and artificial neural network (ANN) approaches for heavy industrial construction projects. The heuristic search allows the practitioners to select the crane configurations based on engineering rules, while the ANN model utilizes the historical project data to help select crane configurations. The K-fold cross-validation is conducted to validate the designed ANN model and improve the accuracy of predictions. The results from the cross-validation test set have shown 70% accuracy. Full article
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Article
An Off-Site Construction Digital Twin Assessment Framework Using Wood Panelized Construction as a Case Study
Buildings 2022, 12(5), 566; https://doi.org/10.3390/buildings12050566 - 28 Apr 2022
Cited by 6 | Viewed by 1154
Abstract
Off-site construction is an innovative type of construction with the philosophy of standardizing the process and deploying the latest technological enablers. Many technologies, such as the Building Information Model (BIM), Internet of Things (IoT), etc., are concerned with virtual representation and manipulation of [...] Read more.
Off-site construction is an innovative type of construction with the philosophy of standardizing the process and deploying the latest technological enablers. Many technologies, such as the Building Information Model (BIM), Internet of Things (IoT), etc., are concerned with virtual representation and manipulation of the physical site. However, a holistic view of the off-site construction processes is lacking in the exploration of the technological advances, resulting in inconsistency when applying these advances in practice. The concept of Digital Twin is useful for addressing this challenge. Digital Twin is a philosophy and a collection of technologies aimed toward seamless physical and virtual connections. Therefore, a holistic Off-site Construction Digital Twin model is necessary for any research concerning this topic, and an assessment framework is useful in helping off-site construction industry companies in approaching systematic Digital Twin. This research first proposes a model for Off-site Construction Digital Twin. To quantify this model, an assessment tool named Off-site Construction Digital Twin Maturity Level is proposed. The validation and evaluation of this assessment framework are conducted through a case study with ACQBuilt, an off-site construction company in Edmonton, Canada. The resulting assessment framework contributes to the body of knowledge in two ways: Firstly, it sets the foundation for an Off-site Construction Digital Twin, which is anticipated to significantly reduce waste and to improve efficiency. Secondly, it enables easier technology application in practice by offering a holistic Digital Twin framework. Full article
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Article
Towards Automated Construction Quantity Take-Off: An Integrated Approach to Information Extraction from Work Descriptions
Buildings 2022, 12(3), 354; https://doi.org/10.3390/buildings12030354 - 15 Mar 2022
Viewed by 1359
Abstract
Construction-oriented quantity take-off (QTO) refers to the process of determining the quantities for construction items or work packages in accordance with their descriptions. However, the current construction-oriented QTO practice relies on estimators’ manual interpretation of work descriptions and manual processes to look up [...] Read more.
Construction-oriented quantity take-off (QTO) refers to the process of determining the quantities for construction items or work packages in accordance with their descriptions. However, the current construction-oriented QTO practice relies on estimators’ manual interpretation of work descriptions and manual processes to look up proper building objects for quantity calculation. Hence, this research aims to develop natural language processing (NLP) and rule-based algorithms to automate the information extraction (IE) from work descriptions for QTO in building construction. Specifically, several named entity recognition (NER) models, including Hidden Markov Model (HMM), Conditional Random Field (CRF), Bidirectional-Long Short-Term Memory (Bi-LSTM), and Bi-LSTM+CRF, were developed to identify construction activities, material, building component, product features, measurement unit, and additional information (e.g., work scope) from work descriptions. Cost items in the RSMeans database are used to evaluate the developed models in terms of F1 scores. HMM was found to achieve a 5% higher F1 score in the NER than the other three algorithms. Then, labeling rules and active learning strategies were applied along with the HMM model, which improved F1 score by 3% and reduced the labeling efforts by 26%. The results showed that the proposed IE method successfully interprets the desired information from the work description for QTO. This research contributed to the body of knowledge by the NLP-based information extraction model integrating HMM and formalized labeling rules that automatically process work descriptions and lay a foundation for automated QTO and cost estimation. Full article
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Article
A Robust Construction Safety Performance Evaluation Framework for Workers’ Compensation Insurance: A Proposed Alternative to EMR
Buildings 2021, 11(10), 434; https://doi.org/10.3390/buildings11100434 - 26 Sep 2021
Cited by 4 | Viewed by 1396
Abstract
The construction work environment remains one of the most hazardous among all industries. Construction injuries directly impact the workers and the work itself, including personal suffering, construction delays, productivity losses, higher insurance premiums, and possible liability suits for all parties involved in the [...] Read more.
The construction work environment remains one of the most hazardous among all industries. Construction injuries directly impact the workers and the work itself, including personal suffering, construction delays, productivity losses, higher insurance premiums, and possible liability suits for all parties involved in the project. The costs resulting from personal injuries, combined with the associated financial impact resulting from schedule disruptions, insurance hikes, and workers’ compensation, can impact a project’s profitability. Many of these impacts can be minimized or avoided through the continuous assessment and improvement of safety policies and practices. This paper aims to propose a new safety assessment methodology that equips insurance companies and construction managers with an optimal mechanism for evaluating the safety performance of construction companies. The proposed model consists of 20 evaluation criteria that are used to establish the efficiency benchmarks and provide comparison feedback for improving the company’s safety plans and procedures. These criteria are determined based on leading and lagging safety performance indicators. The data envelopment analysis (DEA) technique is used as the underlying model to assess the relative efficiency of safety practices objectively. Two illustration case studies are provided to demonstrate the dual effectiveness of the DEA model. The presented research contributes to the body of knowledge by formalizing a robust, effective, and consistent safety performance assessment. The model equips the company with the ability to track both the progression and the retrogression over time and provides feedback on ineffective practices that need more attention. Simultaneously, the model gives them more detailed safety performance information that can replace the current experience modification rating (EMR) approach. It provides insurance companies with an objective and robust evaluation model for selecting optimum rates for their clients. In addition, the data comparison utility offered by the DEA model and its criteria can be helpful for insurance companies to provide effective advice to their clients on which safety aspects to improve in their future strategies. Full article
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Review

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Review
Additive Manufacturing in Off-Site Construction: Review and Future Directions
Buildings 2022, 12(1), 53; https://doi.org/10.3390/buildings12010053 - 06 Jan 2022
Cited by 4 | Viewed by 2398
Abstract
Additive manufacturing (AM) is one of the pillars of Industry 4.0 to attain a circular economy. The process involves a layer-by-layer deposition of material from a computer-aided-design (CAD) model to form complex shapes. Fast prototyping and waste minimization are the main benefits of [...] Read more.
Additive manufacturing (AM) is one of the pillars of Industry 4.0 to attain a circular economy. The process involves a layer-by-layer deposition of material from a computer-aided-design (CAD) model to form complex shapes. Fast prototyping and waste minimization are the main benefits of employing such a technique. AM technology is presently revolutionizing various industries such as electronics, biomedical, defense, and aerospace. Such technology can be complemented with standardized frameworks to attract industrial acceptance, such as in the construction industry. Off-site construction has the potential to improve construction efficiency by adopting AM. In this paper, the types of additive manufacturing processes were reviewed, with emphasis on applications in off-site construction. This information was complemented with a discussion on the types and mechanical properties of materials that can be produced using AM techniques, particularly metallic components. Strategies to assess cost and material considerations such as Production line Breakdown Structure (PBS) and Value Stream Mapping are highlighted. In addition, a comprehensive approach that evaluates the entire life cycle of the component was suggested when comparing AM techniques and conventional manufacturing options. Full article
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Other

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Perspective
Digital Technologies in Offsite and Prefabricated Construction: Theories and Applications
Buildings 2023, 13(1), 163; https://doi.org/10.3390/buildings13010163 - 09 Jan 2023
Viewed by 753
Abstract
Due to its similarity to industrialized products, the offsite construction industry is seen as a focus for the transformation of Construction 4.0. Many digital technologies have been applied or have the potential to be applied to realize the integration of design, manufacturing, and [...] Read more.
Due to its similarity to industrialized products, the offsite construction industry is seen as a focus for the transformation of Construction 4.0. Many digital technologies have been applied or have the potential to be applied to realize the integration of design, manufacturing, and assembly. The main objective of this review was to identify the current stage of applying digital technologies in offsite construction. In this review, 171 related papers from the last 10 years (i.e., 2013–2022) were obtained by collecting and filtering them. They were classified and analyzed according to the digital twin concept, application areas, and specific application directions. The results indicated that there are apparent differences in the utilization and development level of different technologies in different years. Meanwhile, the introduction, current stages, and benefits of different digital technologies are also discussed. Finally, this review summarizes the current popular fields and speculates on future research directions by analyzing article publication trends, which sheds light on future research. Full article
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