Journal of Information Technology in Construction
ITcon Vol. 28, pg. 107-137, http://www.itcon.org/2023/6
A tool-based system architecture for a digital twin: a case study in a healthcare facility
DOI: | 10.36680/j.itcon.2023.006 | |
submitted: | August 2022 | |
revised: | January 2023 | |
published: | February 2023 | |
editor(s): | Robert Amor | |
authors: | Ashit Harode, Ph.D. Candidate
Department of Building Construction, Virginia Tech, Blacksburg, VA, USA; ashit02@vt.edu Walid Thabet, Ph.D., CM-BIM W.E. Jamerson Professor, Department of Building Construction, Virginia Tech, Blacksburg, VA, USA thabet@vt.edu Poorvesh Dongre, Ph. D. Student Department of Computer Science, Virginia Tech, Blacksburg, VA, USA poorvesh@vt.edu | |
summary: | Changes in the local and global markets are forcing A/E/C/FM (Architecture, Engineering, Construction, and Facility Management) organizations to deliver more robust and innovative operational BIMs (Building Information Models). It is hypothesized that BIMs will transform from a static 3D model to a Digital Twin providing a truly digital representation of the physical asset or the building it represents. This transformation to a dynamic Digital Twin will allow the A/E/C/FM industry to visualize, monitor, and optimize operational assets and processes to support better inspection and analysis for a more efficient facility operations and maintenance. To support the adoption and implementation of Digital Twin in A/E/C/FM, the authors have defined two clear objectives. First, we discuss requirements for a functionality-based canonical architecture to create a digital twin followed by proposing two tool-based system architecture options for its implementation. Second, we use a case study approach to develop a proof-of-concept Digital Twin of an operating room in a healthcare facility using Power BI Desktop and Azure Services. The prototype aims to monitor room air quality as per INAIL (National Institute for Insurance against Accidents at Work) and ISO (International Organization for Standards) standards. Multiple sensors connected to a Raspberry Pi 4 are used to capture real-time data for various air quality parameters including temperature, humidity, airflow, particulate contamination, and Nitrous Oxide (N2O) gas. Multiple dashboards are also created to visualize, monitor, and analyze the data harnessed from the OR sensors. The implementation addresses critical issues including security, data storage, visualization, processing, data streaming, collection, and analysis. As an initial validation, the Digital Twin prototype was presented and discussed with a healthcare BIM manager. Initial feedback from the industry expert indicated that the prototype could decrease the required time to respond to facility maintenance issues such as decreased air flow due to possible obstructions. | |
keywords: | Levels of Digital Twins, Facility Management, System Architecture, Power BI, Azure Services, IoT Devices, Raspberry Pi 4 | |
full text: | (PDF file, 1.47 MB) | |
citation: | Harode A, Thabet W, Dongre P (2023). A tool-based system architecture for a digital twin: a case study in a healthcare facility, ITcon Vol. 28, pg. 107-137, https://doi.org/10.36680/j.itcon.2023.006 | |
statistics: |