Kor, M; Yitmen, I and Alizadehsalehi, S (2023) An investigation for integration of deep learning and digital twins towards construction 4.0. Smart and Sustainable Built Environment, 12(3), pp. 461-487. ISSN 2046-6099
Abstract
Purpose: The purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an exploratory analysis. Design/methodology/approach: A mixed approach involving qualitative and quantitative analysis was applied to collect data from global industry experts via interviews, focus groups and a questionnaire survey, with an emphasis on the practicality and interoperability of DDT with decision-support capabilities for process optimization. Findings: Based on the analysis of results, a conceptual model of the framework has been developed. The research findings validate that DL integrated DT model facilitating Construction 4.0 will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making. Practical implications: The DL integrated DT model will establish an interoperable functionality and develop typologies of models described for autonomous real-time interpretation and decision-making support of complex building systems development based on cognitive capabilities of DT. Originality/value: The research explores how the technologies work collaboratively to integrate data from different environments in real-time through the interplay of the optimization and simulation during planning and construction. The framework model is a step for the next level of DT involving process automation and control towards Construction 4.0 to be implemented for different phases of the project lifecycle (design–planning–construction).
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial intelligence; construction 4.0; deep learning; digital twins; internet of things; optimization; simulation |
| Index terms: | internet, automation, interoperability, artificial intelligence, building system, investigation, project lifecycle, deep learning, construction 4.0, digital twin, quantitative analysis, integration, methodology, cognitive ability, decision-making, questionnaire, strategy, functionality, survey, reasoning, interview, focus group |
| Subjects: | automation and robotics, management, research methods, systems and processes, organizational analysis, cognitive psychology, decision analysis, engineering systems, computing systems, data collection methods, digital engineering, project completion, artificial intelligence, data analysis and analytics, design features |
| Topics: | Design Practice, Digital Applications, Organizational Design, Business Strategy, Project Management, Research Practice, Engineering Principles, Risk Management |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here