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Cited by 165BIM and Construction IntegrationDigital Transformation in IndustryConstruction Management and Sustainability

An Adapted Model of Cognitive Digital Twins for Building Lifecycle Management

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Yitmen, Ibrahim, Alizadehsalehi, Sepehr, Akıner, İlknur, Akıner, Muhammed Ernur·2021·Applied Sciences
DOI 10.3390/app11094276
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Abstract

In the digital transformation era in the Architecture, Engineering, and Construction (AEC) industry, Cognitive Digital Twins (CDT) are introduced as part of the next level of process automation and control towards Construction 4.0. CDT incorporates cognitive abilities to detect complex and unpredictable actions and reason about dynamic process optimization strategies to support decision-making in building lifecycle management (BLM). Nevertheless, there is a lack of understanding of the real impact of CDT integration, Machine Learning (ML), Cyber-Physical Systems (CPS), Big Data, Artificial Intelligence (AI), and Internet of Things (IoT), all connected to self-learning hybrid models with proactive cognitive capabilities for different phases of the building asset lifecycle. This study investigates the applicability, interoperability, and integrability of an adapted model of CDT for BLM to identify and close this gap. Surveys of industry experts were performed focusing on life cycle-centric applicability, interoperability, and the CDT model’s integration in practice besides decision support capabilities and AEC industry insights. The evaluation of the adapted model of CDT model support approaching the development of CDT for process optimization and decision-making purposes, as well as integrability enablers confirms progression towards Construction 4.0.

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  • Some researchers recently built cognitive digital twins (CDTs) to incorporate cognitive abilities to detect complex and unpredictable actions and reason about dynamic process optimization strategies to support decision making in building lifecycle management (BLM).

    “Some researchers recently brought the DT concept even further [45] by building so-called cognitive digital twins (CDTs) with the purpose of incorporating cognitive abilities to detect complex and unpredictable actions and reason about dynamic process optimization strategies to support decision making in building lifecycle management (BLM).”

    From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [45]

    Section 2.3 describes CDTs as using cognitive abilities to detect anomalies and aid decisions through optimization, and Section 3.1.6 discusses adapting optimization to changing conditions. But Section 3.1 calls this paper’s contribution an adapted conceptual framework for building lifecycle management, not a report that the authors built working CDTs with those abilities. (LLM, conf=0.86)

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  • The study in [45] relied on surveys with industry experts to focus on lifecycle applicability and integration of the CDT model in practice.

    “The study relied on surveys with industry experts to focus on the lifecycle applicability and the integration of the CDT model in practice.”

    From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [45]

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Cited by

Sorted by citations

Authors
Yitmen, I., Alizadehsalehi, S., Akıner, İ., & Akıner, M. E.
Affiliations
  • Department of Construction Engineering and Lighting Science, Jönköping University, 551 11 Jönköping, Sweden
  • Northwestern University (US)
  • Akdeniz University (TR)
ORCID
Venue
Applied Sciences
Publisher
MDPI AG
Published
2021-05-09
Volume
11
Issue
9
Pages
4276
ISSN
2076-3417 (ISSN-L)
DOI
10.3390/app11094276
OpenAlex
W3162999172
Cited by
165
References
1
Citations by year
2026: 24 · 2025: 26 · 2024: 47 · 2023: 35 · 2022: 28 · 2021: 5
FWCI
13.18
Type
journal article
Language
en
Open access
Licence
Locations
  • Applied Sciences (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
  • Physical Sciences › Engineering › Building and Construction › Construction Management and Sustainability
Keywords
cognitive digital twin, building lifecycle management, Construction 4.0, interoperability, integrability, decision support, process optimization, cyber-physical systems, Internet of Things, machine learning, artificial intelligence, big data, AEC industry, expert survey

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