Automation and Information and Knowledge Model Technologies in Construction Engineering

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 (28 February 2023) | Viewed by 16223

Special Issue Editors


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Guest Editor
Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Maribor, Slovenia
Interests: automation and digitalization for built environment; infrastructure and building information modeling; procedural modeling; knowledge engineering; information modeling and standardization for public transport

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Guest Editor
Department of Civil, Construction and Environmental Engineering, University of Naples Federico II, 80125 Naples, Italy
Interests: offshore civil engineering; coastal engineering; data mining; intelligent transportation system
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Special Issue Information

Dear Colleagues,

The ubiquity of digitalization in construction enables new levels of automation for processes and workflows that create and maintain digital assets throughout the building and infrastructure lifecycle stages. Research in the various fields of computer science and informatics combined with research in construction creates new research opportunities for construction informatics. At its core, information and knowledge modeling accounts for fundamental achievements such as building information modeling and knowledge-based representation of building data (such as ifcOWL ontology), which is boosting research in the automation of many BIM-based methods, including digital twins and digital building logbooks as well as semantic web and linked data approaches for material data, GIS data, product manufacturer data, sensor data, classification schemata, social data, and more.

Original research papers on the following topics are welcome:

BIM-based automation, semantic web and linked data for automation, ontology driven workflows, digital twins, digital building logbooks, automation and classification systems, IFC extensions, construction robots, autonomous machines for construction, automation of building, automation for construction safety, automation of modular construction, ethical automation in construction, smart construction materials and automation, and building management automation systems.

Dr. Andrej Tibaut
Dr. Salvatore Antonio Biancardo
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

  • BIM-based automation
  • semantic web and linked data for automation in construction
  • digital twins
  • digital building logbooks
  • construction robots and autonomous machines for construction
  • automation of modular construction
  • ethical automation in construction
  • automation for construction safety

Published Papers (5 papers)

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Research

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15 pages, 5417 KiB  
Article
An Automatic Generation Method of Finite Element Model Based on BIM and Ontology
by Jing Jia, Jieya Gao, Weixin Wang, Ling Ma, Junda Li and Zijing Zhang
Buildings 2022, 12(11), 1949; https://doi.org/10.3390/buildings12111949 - 11 Nov 2022
Cited by 10 | Viewed by 2685
Abstract
For the mechanical analysis work in the structural design phase, data conversion and information transfer between BIM model and finite element model have become the main factors limiting its efficiency and quality, with the development of BIM (building information modeling) technology application in [...] Read more.
For the mechanical analysis work in the structural design phase, data conversion and information transfer between BIM model and finite element model have become the main factors limiting its efficiency and quality, with the development of BIM (building information modeling) technology application in the whole life cycle. The combined application of BIM and ontology technology has promoted the automation of compliance checking, cost management, green building evaluation, and many other fields. Based on OpenBIM, this study combines IFC (Industry Foundation Classes) and the ontology system and proposes an automatic generation method for converting BIM to the finite element model. Firstly, the elements contained in the finite element model are generalized and the information set requirement, to be extracted or inferred from BIM for the generation of the finite element model, is obtained accordingly. Secondly, the information extraction technical route is constructed to satisfy the acquisition of the information set, including three main aspects, i.e., IFC-based material information, spatial information, and other basic information; ontology-based finite element cell selection method; and APDL statement generation methods based on JAVA, C#, etc. Finally, a complete technical route and a software architecture, designed for converting BIM to the finite element model, are derived. To assess the feasibility of the method, a simple structure is tested in this paper, and the result indicates that the automatic decision-making reasoning mechanism of constructing element type and meshing method can be explored by ontology and IFC. This study contributes to the body of knowledge by providing an efficient method for automatic generation of the BIM structure model and a reference for future applications using BIM in structural analysis. Full article
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32 pages, 14105 KiB  
Article
Semantic Web Technologies for Indoor Environmental Quality: A Review and Ontology Design
by Alex Donkers, Dujuan Yang, Bauke de Vries and Nico Baken
Buildings 2022, 12(10), 1522; https://doi.org/10.3390/buildings12101522 - 23 Sep 2022
Cited by 10 | Viewed by 2771
Abstract
Indoor environmental quality (IEQ) affects occupants’ satisfaction, health, productivity, comfort, and well-being. IoT developments enable better monitoring of IEQ parameters; however, integrating the various types of heterogeneous data from both the IoT and BIM domains is cumbersome and capital intensive, and therefore, limits [...] Read more.
Indoor environmental quality (IEQ) affects occupants’ satisfaction, health, productivity, comfort, and well-being. IoT developments enable better monitoring of IEQ parameters; however, integrating the various types of heterogeneous data from both the IoT and BIM domains is cumbersome and capital intensive, and therefore, limits the potential of smart buildings. Semantic web technologies can reduce heterogeneity issues, which is necessary to facilitate complex IEQ models. An ontology integrating data related to a building’s topology and its static and dynamic properties is still lacking. The outline of this research is twofold. First, a systematic literature review was conducted to find state-of-the-art semantic web technologies related to building topology, static properties, and dynamic properties from the IoT and BIM domains. By graphically reviewing various ontologies, their valuable patterns, commonalities, and best practices were revealed. Secondly, those results were used to develop a new ontology that integrates topological building information with static and dynamic properties. This Building Performance Ontology (BOP) provides a generic upper-level description of properties and two lower-level ontologies representing observations and actuation. The ontology results in intuitive queries and is both horizontally and vertically extensible. Multiple levels of detail are introduced to ensure practical applicability and efficient patterns based on the data modeler’s needs. BOP opens up a new range of research opportunities in the IEQ domain. Full article
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26 pages, 5270 KiB  
Article
A Foundation Model for Building Digital Twins: A Case Study of a Chiller
by Suliang Li, Qiliang Yang, Jianchun Xing, Wenjie Chen and Rongwei Zou
Buildings 2022, 12(8), 1079; https://doi.org/10.3390/buildings12081079 - 24 Jul 2022
Cited by 3 | Viewed by 2155
Abstract
Due to the high-fidelity mapping of the physical buildings and the intelligent performance shown in their lifecycle, digital twins (DTs) have gained increasing attention in the building sector. Although digital twins based on building information modeling (BIM) have become a hot research topic, [...] Read more.
Due to the high-fidelity mapping of the physical buildings and the intelligent performance shown in their lifecycle, digital twins (DTs) have gained increasing attention in the building sector. Although digital twins based on building information modeling (BIM) have become a hot research topic, existing works emphasize the digitization of building static and dynamic information and lack a unified consideration of the inherent physical mechanisms and interactive behaviors of buildings. To this end, this paper proposes a foundation model for building digital twins which realizes the unification of building static information, physical mechanisms and interaction patterns. The conceptual framework of the model is given first and then formal modeling and verification with time automata theory are performed to demonstrate the plausibility of the model. Finally, a practical digital twin of a chiller is developed based on the proposed foundation model as an example, thus, indicating its effectiveness and credibility. Full article
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Review

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38 pages, 3821 KiB  
Review
Systematic Literature Review of Open Infrastructure BIM
by Antonio Salzano, Mattia Intignano, Carla Mottola, Salvatore Antonio Biancardo, Maurizio Nicolella and Gianluca Dell’Acqua
Buildings 2023, 13(7), 1593; https://doi.org/10.3390/buildings13071593 - 23 Jun 2023
Cited by 2 | Viewed by 2200
Abstract
Representation and modeling using the building information modeling (BIM) methodology of civil works have become the subject of increasing attention in recent years, thanks to the potential offered by Open Infrastructure BIM (I-BIM). However, the complexity of infrastructure works, i.e., the variety of [...] Read more.
Representation and modeling using the building information modeling (BIM) methodology of civil works have become the subject of increasing attention in recent years, thanks to the potential offered by Open Infrastructure BIM (I-BIM). However, the complexity of infrastructure works, i.e., the variety of construction and technological systems, makes Open I-BIM very complex and challenging. The lack of systemic knowledge on the subject is another challenging factor. The aim of the following research work is to provide a synoptic overview of the existing scientific research, accompanied by the most recent studies in the field of computer modeling, its applications, and the main opportunities that Open I-BIM offers to the infrastructure sector. After a thorough review of 198 scientific articles published between 2013 and 2023, this study systematically presents a holistic review and critical reflection on the current status of the use of Open BIM in the infrastructure sector, with a focus on the development of the tools and methods used. The outcome of this work constitutes a systematic review of the literature with a bibliometric analysis on Open I-BIM, which is able to provide a knowledge base for identifying research trends, common problems, and the potential of developed methods. Full article
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23 pages, 2336 KiB  
Review
A Systematic Review of Artificial Intelligence Applied to Facility Management in the Building Information Modeling Context and Future Research Directions
by Rodrigo Pedral Sampaio, António Aguiar Costa and Inês Flores-Colen
Buildings 2022, 12(11), 1939; https://doi.org/10.3390/buildings12111939 - 10 Nov 2022
Cited by 6 | Viewed by 5202
Abstract
Throughout the operation and maintenance (O&M) stage, facility management (FM) teams collect and process data from different sources, often needing to be adequately considered when making future decisions. This data could feed statistical models based on artificial intelligence (AI), thus improving decision-making in [...] Read more.
Throughout the operation and maintenance (O&M) stage, facility management (FM) teams collect and process data from different sources, often needing to be adequately considered when making future decisions. This data could feed statistical models based on artificial intelligence (AI), thus improving decision-making in FM. Building information modeling (BIM) appears in this context, leveraging how data and information are systematized, enabling structured information and its use. This article addresses the state-of-the-art of using AI techniques applied to FM in the BIM context, analyzing articles between 2012 and 2021 related to this area. It is interesting to note that only from 2018 onwards, there is a substantial increase in these publications, from about 8 publications (2012 to 2017) to 24 publications (2018 to 2021) on average. This growth shows the progressive application of the optimization methods mentioned above, which opens new opportunities for the FM profession. This study contributes to the body of knowledge by highlighting the investigated tendency and gaps in critical areas and their relationship with the research topic. Noteworthy future directions are suggested, directing on (i) data and system integration; (ii) predictive models; (iii) automatic as-built/classification; (iv) internet of things; (v) energy management; and (vi) augmented/virtual reality. Full article
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