In recent years, the massive development of digital technologies for capturing data from sensors, located both in-side buildings and in the urban environment, made necessary an expansion of the traditional semantic domains of the construction industry with reference to BIM-based information management processes. The integration of data between BIM models and IoT devices enables the creation of Digital Twins (DTs) of built heritage assets, capable of connecting data coming continuously from sensors with digital models of those assets. This enables the management of large masses of data produced at various stages of the building lifecycle, making it possible to experiment with Artificial Intelligence (AI) and data analytics for predictive analysis of building system behavior and performance. This paper presents the results of a research, which aimed to develop a methodological and operational workflow for the creation of Digital Twin of buildings. The interoperability offered by the IFC schema allowed the use of an external platform for linking different semantic fields. Thus, on the one hand, a federated BIM model was created, and on the other hand, real-time acquired data from a system of sensors in-stalled at different locations in the building were recorded and stored in a central server.
BIM and Data Integration: A Workflow for the Implementation of Digital Twins / Biagini Carlo; Bongini Andrea. - ELETTRONICO. - (2023), pp. 821-835. [10.1007/978-3-031-36155-5_53]
BIM and Data Integration: A Workflow for the Implementation of Digital Twins
Biagini Carlo
;Bongini Andrea
2023
Abstract
In recent years, the massive development of digital technologies for capturing data from sensors, located both in-side buildings and in the urban environment, made necessary an expansion of the traditional semantic domains of the construction industry with reference to BIM-based information management processes. The integration of data between BIM models and IoT devices enables the creation of Digital Twins (DTs) of built heritage assets, capable of connecting data coming continuously from sensors with digital models of those assets. This enables the management of large masses of data produced at various stages of the building lifecycle, making it possible to experiment with Artificial Intelligence (AI) and data analytics for predictive analysis of building system behavior and performance. This paper presents the results of a research, which aimed to develop a methodological and operational workflow for the creation of Digital Twin of buildings. The interoperability offered by the IFC schema allowed the use of an external platform for linking different semantic fields. Thus, on the one hand, a federated BIM model was created, and on the other hand, real-time acquired data from a system of sensors in-stalled at different locations in the building were recorded and stored in a central server.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.