The hype factor of digital technologies in AEC

Bosch‐Sijtsema, Petra M.; Claeson-Jonsson, Christina; Johansson, Mikael; Roupé, Mattias

doi:10.1108/ci-01-2020-0002

Cited by 68 publications

(44 citation statements)

References 34 publications

(73 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Manufacturing "DT is very realistic models of the current state of the process and their own behavior in interaction with their environment in the real world" [93] Data-Oriented modeling "Coupled model of the real machine that operates in the cloud platform and simulates the health condition with an integrated knowledge from both data driven analytical algorithms as well as other available physical knowledge" [94] Cyber-Physical Systems "Digital Twin, which links the physical system with its virtual equivalent can mitigate these problematic issues" [95] "The Digital Twin (DT) is meant as the virtual and computerized counterpart of a physical system that can be used to simulate it for various purposes, exploiting a realtime synchronization of the sensed data coming from the field" [96] "Digital Twin, requires a cloud-based solution to ensure a near real-time processing" [97,98] Different applications are reported for DT in literature, life prediction [86], supply chain simulation [99], safety and reliability [30], quality control/improve [100], maintenance [101][102][103][104][105], urban administration [106], building lifecycle [107,108], uncertainty management [95], decision science [109], material science [110], cloth industry [111],…”

Section: Definitionmentioning

confidence: 99%

Digital Twin (DT) in Smart Energy Systems - Systematic Literature Review of DT as a growing solution for Energy Internet of the Things (EIoT)

2021

View full text Add to dashboard Cite

In the industry 4.0 era, the Smart Energy System (SES) should be able to address the emerging challenges of digitization and socioeconomic/ecologic transition along with other critical entities of the society. However, because of the complexity of this system, both researchers and practitioners are seeking an agile and smart solution. The main motive of this review is to investigate the applications and implementation of Digital Twin (DT) in the provision of energy services. Research Questions (RQ) of this study include: RQ1: What are the applications of DT in SES and how effective is DT in that use case of EIoT? RQ2: Which issues of an SES can be addressed efficiently by using DT? Through answering the mentioned questions, the current study is heading to following objectives (O), O1: Describe the state of the art of DT in SES. O2: Develop a direction for energy 4.0 management through listing the applications, challenges and important factors of implementing DTs. O3: Provide a list of various approaches in employing DT in the scope of SES. The current study is a systematic literature review (SLR), based on SCOPUS, WOS and IEEE digital libraries. Two keywords (namely “Digital Twin” and “Energy Systems”) have been first used. To achieve the final list of articles, 2 levels of screening have been conducted. The first Screening was based on the relevance of the results concerning research objectives. The second screening was an abstract study. The exclusion/inclusion criteria in the abstract study were based on the research questions. The papers that have the potential of answering one of the research questions have been included. Since the implementation of DT is a rather new topic, both backward snowballing and forward snowballing strategies are implemented to finalize the article selection phase. 60 articles identified by searching through scientific databases and 11 articles have been appended to the list during the snowballing process. The results of the current review provide a managerial guideline for practitioners that are heading to utilize DT, along with an anthology of DT within SES scope to feed possible future studies.

show abstract

Section: Definitionmentioning

confidence: 99%

Digital Twin (DT) in Smart Energy Systems - Systematic Literature Review of DT as a growing solution for Energy Internet of the Things (EIoT)

2021

View full text Add to dashboard Cite

show abstract

“…At the same time, it is possible to determine the maturity of information modeling technologies using the Gartner curve [3] (Fig. 4).…”

Section: Fig3 Maturity Level Diagram Of Information Modeling Technologiesmentioning

confidence: 99%

To the question of the building information modeling technologies transition to a new development level

Shilov

Shilova

2021

E3S Web Conf.

View full text Add to dashboard Cite

The article analyzes the maturity level of information modeling technology based on the Bew-Richards diagram, as well as using the Gartner curve. The analysis of current publications on the keywords BIM and Building information modeling has been carried out. It has been determined that Revit software is currently the most widely used for working with construction objects, but the proposed Bentley products provide more granularity in the information model characteristics. At the same time, none of the presented products can cover the entire life cycle of a construction project without significant modifications. The authors propose to expand the set of building structures elementsэ properties, dividing them into more detailed subgroups, to use this information at further stages of the release of design documentation. Thus, the information in the model should be sufficient to release all subsequent documentation. In this case, in addition of the need to separate them in detail, information about the position of the object in world space, and not in model space, is added to the properties. As a result, it is possible to build an information system containing information sufficient for the release of all project documentation according to the proposed approach, as well as supporting the project at the operational stage. In this case, the documentation issuance is proposed to be done by writing scripts and using databases.

show abstract

“…AI has sparked significant interest in a wide variety of areas, including computer science, mechanical engineering, and civil engineering, attracting the attention of researchers [42,43]. Some reviews on this subject have been published as a result of the rapid growth of AI applications in civil engineering [44][45][46][47]. However, the majority of them only emphasize the importance of AI in a particular subfield, such as structural engineering [48], building information modeling (BIM) [49], automated construction manufacturing [50], computer vision [51], and others.…”

Section: Introductionmentioning

confidence: 99%

Influence of Artificial Intelligence in Civil Engineering toward Sustainable Development—A Systematic Literature Review

Manzoor

Othman

Durdyev

et al. 2021

ASI

View full text Add to dashboard Cite

The widespread use of artificial intelligence (AI) in civil engineering has provided civil engineers with various benefits and opportunities, including a rich data collection, sustainable assessment, and productivity. The trend of construction is diverted toward sustainability with the aid of digital technologies. In this regard, this paper presents a systematic literature review (SLR) in order to explore the influence of AI in civil engineering toward sustainable development. In addition, SLR was carried out by using academic publications from Scopus (i.e., 3478 publications). Furthermore, screening is carried out, and eventually, 105 research publications in the field of AI were selected. Keywords were searched through Boolean operation “Artificial Intelligence” OR “Machine intelligence” OR “Machine Learning” OR “Computational intelligence” OR “Computer vision” OR “Expert systems” OR “Neural networks” AND “Civil Engineering” OR “Construction Engineering” OR “Sustainable Development” OR “Sustainability”. According to the findings, it was revealed that the trend of publications received its high intention of researchers in 2020, the most important contribution of publications on AI toward sustainability by the Automation in Construction, the United States has the major influence among all the other countries, the main features of civil engineering toward sustainability are interconnectivity, functionality, unpredictability, and individuality. This research adds to the body of knowledge in civil engineering by visualizing and comprehending trends and patterns, as well as defining major research goals, journals, and countries. In addition, a theoretical framework has been proposed in light of the results for prospective researchers and scholars.

show abstract

The hype factor of digital technologies in AEC

Cited by 68 publications

References 34 publications

Digital Twin (DT) in Smart Energy Systems - Systematic Literature Review of DT as a growing solution for Energy Internet of the Things (EIoT)

Digital Twin (DT) in Smart Energy Systems - Systematic Literature Review of DT as a growing solution for Energy Internet of the Things (EIoT)

To the question of the building information modeling technologies transition to a new development level

Influence of Artificial Intelligence in Civil Engineering toward Sustainable Development—A Systematic Literature Review

Contact Info

Product

Resources

About