This paper explores the potential of a location-enabled “minimal interoperability” framework as a stepping stone for data interoperability and integration in building Digital Twins, where location refers to the position of a feature in relation to a reference system.
Abstract
Digital Twins (DTs) of buildings are becoming increasingly common, with applications including air quality monitoring, reducing energy consumption, increasing human comfort and safety and more. Data is at the heart of these digital twins; however, integration and interoperability challenges are major barriers to adoption. This paper explores the potential of a location-enabled “minimal interoperability” framework as a stepping stone for data interoperability and integration in building Digital Twins, where location refers to the position of a feature in relation to a reference system. To scope the challenge, we first identify twin-centric applications and the data sources used within each. A minimal level of location granularity (the resolution of the data) is then assigned to each data source in order to identify the required geometry components of the framework. We explore the feasibility/time and skills required to implement such a framework for a building, demonstrating the framework within a human comfort-related application. Contributions include the development of a location-enabled minimal interoperability framework that supports the heterogeneous nature of data within building Digital Twins and a `minimum granularity’ approach for the location framework which shows that simple 3D buildings appear sufficient and avoids the need for expensive 3D data capture. Our approach allows implementers of Digital Twins to explore and integrate data without implementing extensive and time-consuming full interoperability.
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