PriSeg: IFC-Supported Primitive Instance Geometry Segmentation with Unsupervised Clustering

Hu, Zhiqi; Brilakis, Ioannis

doi:10.1007/978-3-031-25082-8_13

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Example 1: Condition Monitoring1

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2023

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Cited by 2 publications

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“…By capturing geometric information through different sensors, the current condition of the asset can be visualised and represented by the DT. The geometry of facilities can be monitored by comparing the current condition with previous asset conditions over time, which allows a DT to give maintenance suggestions to the asset holders and managers (Hu et al, 2023).…”

Section: Example 1: Condition Monitoringmentioning

confidence: 99%

Digital Twins and Their Roles in Building Deep Renovation Life Cycle

Pan

Brilakis

2023

Palgrave Studies in Digital Business &Amp; Enabling Technologies

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Digital twins have started to diffuse within architecture, engineering, construction, and operations (AECO), based on their emerging and anticipated benefits to the various stakeholders involved in the building life cycle. However, their applications are still at an early stage, and much effort is still needed to exploit their full potential. This chapter explains some key notions to help understand digital twins in AECO. It exposes the various definitions of digital twins and illustrates the basic steps and relevant methods for creating a digital twin. The chapter also provides an overview of the state-of-the-art deep learning methods for digital twins and discusses some real-life use cases. Finally, the chapter discusses the benefits and challenges associated with the adoption of digital twins.

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Section: Example 1: Condition Monitoringmentioning

confidence: 99%