Applicability of BIM-IoT-GIS integrated digital twins for post occupancy evaluations
Author(s): |
Ishan Tripathi
Thomas M. Froese Shauna Mallory-Hill |
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Medium: | journal article |
Language(s): | English |
Published in: | Frontiers in Built Environment, February 2023, v. 9 |
DOI: | 10.3389/fbuil.2023.1103743 |
Abstract: |
Post Occupancy Evaluations (POE) provided a systematic methodology for determining the performance gap between expected and actual performance. Monitoring quality of the indoor environment is essential for understanding building performance in relation to occupant health, wellbeing, and comfort. Because of the global COVID-19 pandemic, researchers faced numerous issues accessing the building for collecting data and making spot measurements of the indoor environment. Technologies such as Building Information Modeling (BIM), Internet of Things (IoT), and Geographical Information Systems (GIS) have the potential to address existing challenges for data collection, analysis, and visualization in post occupancy evaluations. This study aims to explore the applications of a BIM-IoT-GIS-integrated digital twin for post occupancy evaluations. First, high-level use case scenarios are developed to derive system requirements for a digital twin platform. Second, four tests are conducted that provide a step-by-step procedure for BIM-IoT-GIS integration. Third, the integration is validated by geo-reference checks, data transfer checks, and visual checks. Based on the tests, a streamlined workflow is recommended for similar/future projects. The results demonstrate that Revit-ArcGIS Pro integration meets the system requirements for post occupancy evaluations. Moreover, as shown in the graphical abstract (Figure), the spatial-temporal capabilities of ArcGIS Pro enable continuous monitoring and visualization of building performance in 4D. In conclusion, BIM-IoT-GIS integration can provide a solid foundation for developing a centralized digital twin for post occupancy evaluations and enables researcher to collect and analyze the data without being physically present in the building. |
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data sheet - Reference-ID
10732244 - Published on:
13/06/2023 - Last updated on:
13/06/2023