Toward Smart-Building Digital Twins: BIM and IoT Data Integration | IEEE Journals & Magazine | IEEE Xplore

Toward Smart-Building Digital Twins: BIM and IoT Data Integration


Towards Smart-Building Digital Twins: BIM and IoT Data Integration.

Abstract:

Smart-building digital twins aim to virtually replicate the static and dynamic building characteristics through real-time connectivity between the virtual and physical co...Show More

Abstract:

Smart-building digital twins aim to virtually replicate the static and dynamic building characteristics through real-time connectivity between the virtual and physical counterparts. The virtual replica of the building can then be leveraged to monitor the current state, predict the future state, and take proactive measures to ensure optimal operation. Despite its potential, smart-building digital twin research is at an early stage compared to manufacturing and aerospace fields. One of the major impediments to adopting digital twin technology in smart buildings is the lack of interoperability, primarily between Building Information Modeling (BIM) and Internet of Things (IoT) data sources. Consequently, this paper presents a novel multi-layer digital twin architecture for smart buildings called BIM-IoT Data Integration (BIM-IoTDI) to enable semantic interoperability among smart-building digital twin applications. A detailed framework is presented based on the newly developed architecture, introducing an ontology-based query mediation method that provides integrated data access. An experimental evaluation model is developed to characterize the feasibility of the BIM-IoTDI architecture and framework. Furthermore, the performance of the new query mediation method is evaluated and compared to an existing BIM-IoT data integration approach. According to the evaluation results, the BIM-IoTDI architecture and framework are better suited to supporting the envisioned smart-building digital twin capabilities.
Towards Smart-Building Digital Twins: BIM and IoT Data Integration.
Published in: IEEE Access ( Volume: 10)
Page(s): 130487 - 130506
Date of Publication: 15 December 2022
Electronic ISSN: 2169-3536

Funding Agency:


References

References is not available for this document.