An openBIM Approach to IoT Integration with Incomplete As-Built Data
Digital Twins (DT) are powerful tools to support asset managers in the operation and maintenance of cognitive buildings. Building Information Models (BIM) are critical for Asset Management (AM), especially when used in conjunction with Internet of Things (IoT) and other asset data collected througho...
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doaj-e38ae195728a4478bbaa2cdd355a43512020-11-25T04:02:58ZengMDPI AGApplied Sciences2076-34172020-11-01108287828710.3390/app10228287An openBIM Approach to IoT Integration with Incomplete As-Built DataNicola Moretti0Xiang Xie1Jorge Merino2Justas Brazauskas3Ajith Kumar Parlikad4Institute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, UKInstitute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, UKInstitute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, UKThe Computer Laboratory, Department of Computer Science and Technology, University of Cambridge, 15 JJ Thomson Ave, Cambridge CB3 0FD, UKInstitute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, UKDigital Twins (DT) are powerful tools to support asset managers in the operation and maintenance of cognitive buildings. Building Information Models (BIM) are critical for Asset Management (AM), especially when used in conjunction with Internet of Things (IoT) and other asset data collected throughout a building’s lifecycle. However, information contained within BIM models is usually outdated, inaccurate, and incomplete as a result of unclear geometric and semantic data modelling procedures during the building life cycle. The aim of this paper is to develop an openBIM methodology to support dynamic AM applications with limited as-built information availability. The workflow is based on the use of the IfcSharedFacilitiesElements schema for processing the geometric and semantic information of both existing and newly created Industry Foundation Classes (IFC) objects, supporting real-time data integration. The methodology is validated using the West Cambridge DT Research Facility data, demonstrating good potential in supporting an asset anomaly detection application. The proposed workflow increases the automation of the digital AM processes, thanks to the adoption of BIM-IoT integration tools and methods within the context of the development of a building DT.https://www.mdpi.com/2076-3417/10/22/8287BIMopenBIMIFCIoTsensorscognitive buildings |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nicola Moretti Xiang Xie Jorge Merino Justas Brazauskas Ajith Kumar Parlikad |
spellingShingle |
Nicola Moretti Xiang Xie Jorge Merino Justas Brazauskas Ajith Kumar Parlikad An openBIM Approach to IoT Integration with Incomplete As-Built Data Applied Sciences BIM openBIM IFC IoT sensors cognitive buildings |
author_facet |
Nicola Moretti Xiang Xie Jorge Merino Justas Brazauskas Ajith Kumar Parlikad |
author_sort |
Nicola Moretti |
title |
An openBIM Approach to IoT Integration with Incomplete As-Built Data |
title_short |
An openBIM Approach to IoT Integration with Incomplete As-Built Data |
title_full |
An openBIM Approach to IoT Integration with Incomplete As-Built Data |
title_fullStr |
An openBIM Approach to IoT Integration with Incomplete As-Built Data |
title_full_unstemmed |
An openBIM Approach to IoT Integration with Incomplete As-Built Data |
title_sort |
openbim approach to iot integration with incomplete as-built data |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2020-11-01 |
description |
Digital Twins (DT) are powerful tools to support asset managers in the operation and maintenance of cognitive buildings. Building Information Models (BIM) are critical for Asset Management (AM), especially when used in conjunction with Internet of Things (IoT) and other asset data collected throughout a building’s lifecycle. However, information contained within BIM models is usually outdated, inaccurate, and incomplete as a result of unclear geometric and semantic data modelling procedures during the building life cycle. The aim of this paper is to develop an openBIM methodology to support dynamic AM applications with limited as-built information availability. The workflow is based on the use of the IfcSharedFacilitiesElements schema for processing the geometric and semantic information of both existing and newly created Industry Foundation Classes (IFC) objects, supporting real-time data integration. The methodology is validated using the West Cambridge DT Research Facility data, demonstrating good potential in supporting an asset anomaly detection application. The proposed workflow increases the automation of the digital AM processes, thanks to the adoption of BIM-IoT integration tools and methods within the context of the development of a building DT. |
topic |
BIM openBIM IFC IoT sensors cognitive buildings |
url |
https://www.mdpi.com/2076-3417/10/22/8287 |
work_keys_str_mv |
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