An openBIM Approach to IoT Integration with Incomplete As-Built Data

Justas Brazauskas,Nicola Moretti,Jorge Merino,Ajith Kumar Parlikad,Xiang Xie

doi:10.3390/app10228287

Abstract

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 However, information contained within BIM models is usually outdated, inaccurate, and incomplete as a result of unclear geometric and semantic data modelling procedures during the building life cycle.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.

Highlights

Asset Management (AM) is a key organisational area in Architecture, Engineering, Constructions and Operations (AECO), being a recognised and effective driver for better sustainability of the built environment, while improving asset condition and performance [1,2]
The aim of this paper is to present an openBIM methodology to overcome the separation of existing static/dynamic information in supporting AM applications with awareness of inaccurate and incomplete as-built data
The potential of data usually siloed in their own domain can be accessed more supporting the development of AM applications for cognitive buildings

Summary

Introduction

Asset Management (AM) is a key organisational area in Architecture, Engineering, Constructions and Operations (AECO), being a recognised and effective driver for better sustainability of the built environment, while improving asset condition and performance [1,2]. The management of the built environment has entered a new phase characterised by a digital transformation of management processes [3]. This phase concerns the adoption of digital tools that can support the production, storage and update of information during the life cycle of assets [4,5,6].

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