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Data Integration for Digital Twins in the Built-Environment: A Hybrid method based on federated data modelling

Lookup NU author(s): Dr Xiang XieORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Improving efficiency of operations is a major challenge in Facility Management given the limitations of outsourcing individual building functions to third-party companies. The status of each building function is isolated in siloes which are controlled by these third-party companies. Companies provide access to aggregated information in the form of reports through web portals, emails or in the worst case scenario, a bureaucratic process. Digital Twins represent an emerging approach to return awareness and control to facility managers by automating all levels of information access (from granular to defined KPIs and reports) and actuation. This paper proposes a method to standardise the integration of data that supports decision making in Facility Management, including construction, operations and maintenance data, and Internet of Things. The method uses federated data models and semantic web ontologies to enable integration and it is implemented within a data lake architecture with connections to siloed data to keep the delegation of responsibilities of data owners. A case study in the Alan Reece building (Cambridge, United Kingdom) demonstrates the approach by enabling Fault-Detection-and-Diagnosis of the Heating Ventilation and Air Conditioning system for facility management.


Publication metadata

Author(s): Merino J, Xie X, Moretti N, Chang J, Parlikad A

Publication type: Article

Publication status: Published

Journal: Smart Infrastructure and Construction (Proceedings of the ICE)

Year: 2023

Volume: 176

Issue: 4

Pages: 194-211

Online publication date: 13/10/2023

Acceptance date: 23/08/2023

Date deposited: 29/08/2023

ISSN (electronic): 2397-8759

Publisher: Institution of Civil Engineers

URL: https://doi.org/10.1680/jsmic.23.00002

DOI: 10.1680/jsmic.23.00002

ePrints DOI: 10.57711/t0mz-7x15


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