Valinejadshoubi, M; Sacks, R; Valdivieso, F; Corneau-Gauvin, C and Kaptué, A (2025) Digital twin construction in practice: A case study of closed-loop production control integrating BIM, GIS, and IoT sensors. Journal of Construction Engineering and Management, 151(11): 05025014, ISSN 0733-9364
Abstract
Digital twin construction (DTC) integrates digital representation of product design and process planning, automated monitoring on site, intelligent data interpretation, and predictive analytics to provide managers with situational awareness and guide subsequent cycles of production planning and control. This study presents a case study of a DTC system integrating building information modeling (BIM), the Internet of Things (IoT), and GIS for real-time monitoring and process optimization in an industrial silo construction project in Canada. The system consists of four key components: IoT sensors that collect real-time construction data, automated data transmission and storage, BIM-based design and planning models, and interactive dashboards for project monitoring and decision-making. The system enabled just-in-time pull delivery of steel elements, precise placement of components within the slip-formwork, and continuous progress tracking. As a result, construction time was reduced by 28% and material wastage decreased by 15% due to data-driven decision-making and real-time monitoring. The primary contribution of this study is demonstrating a structured approach to integrating DTC technologies into construction workflows, providing a practical framework for bridging digital models with real-time execution. This research highlights how the integration of BIM, IoT, and GIS enhances construction accuracy, efficiency, and automation, addressing challenges related to interoperability, real-time monitoring, and predictive analytics. Despite challenges such as the initial setup costs and specialized staff training requirements, the long-term benefits, including improved resource allocation, cost savings, and enhanced project management capabilities, justify the investment. The findings suggest that adapting advanced DTC systems can significantly enhance construction productivity, accuracy, and sustainability, leading to better-managed and more efficient projects. Future research should explore scalability across different construction sectors and locations to further validate the economic and operational impact of this approach.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | building information modeling; construction progress tracking; data integration; data visualization; GIS; internet of things |
| Index terms: | case study, efficiency, resource allocation, building information modelling, dashboard, Canada, formwork, production control, monitoring, project management, construction time, interoperability, progress tracking, internet, construction productivity, automation, cost saving, construction progress tracking, product design, placement, manager, accuracy, data visualization, production planning, silo construction, just-in-time, integration, decision-making, project monitoring, data-driven decision-making, digital twin, workflow, construction sector |
| Subjects: | management, economics, performance management, project management theory and practice, professional development, project controls, organizational analysis, decision analysis, infrastructure and transport systems, industry analysis, information systems, systems and processes, data collection methods, computing systems, control systems, data science, resource management, project delivery, Geography, automation and robotics, lean logistics, building construction, digital engineering, practitioner, operations management, innovation and technology management |
| Topics: | Research Practice, Information Management, Business Strategy, Cost Management, Construction Technology, Roles and Professions, Human Resources, Digital Applications, Site Management, Organizational Design, Time Control, Project Management, Geographical Context, Engineering Principles, Risk Management, Quality Management, Supply Chain Management |
| Descriptive scope: | 4 PCTE |
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