Real-virtual synchronisation: a review on the state-of-the-art geometric digital twinning of infrastructure

Abstract

In the United Kingdom (UK), recent developments in the construction industry have increased the demand for digitised infrastructure, which facilitates the investigation of the as-is performance of assets. This establishes the need to create and maintain up-todate digital copies of infrastructure assets, often labelled as Digital Twins. Digital twins are obtained by converting the unstructured data formats of the real-world assets, such as point clouds, into high-level digital representations. Yet, only few assets today have usable digital twins because of the high costs of the latter. This counteracts the benefits of the twins and reduces dramatically their true potential. Hence, there is a pressuring need to automate the process of creating digital twins. Geometric digital twin, the most basic form of the twin, contains only the geometry of the physical asset. This paper reviews the work done in computer vision, geometry processing, and civil engineering fields to determine the potential that exists for automatically producing geometric digital twins of infrastructure.

Digital Twins and Enabling Technologies in Museums and Cultural Heritage: An Overview

“…Laser or drone scanning, remote sensing , LiDAR (light detection and ranging), 3D-imaging sensors, close- and midrange terrestrial laser scanning and structured light and multi-beam sensing [ 14 , 24 , 28 , 29 , 38 ] are used for image capturing, area mapping and identifying objects and their properties in five content-centric DTs.…”

“…from an aircraft or satellite [ 4 ] or from drones [ 10 , 15 , 43 ]. It measures emitted or reflected radiation (in agriculture [ 2 ]), realizes inertial localization [ 5 , 19 ] or generates point clouds [ 14 , 28 ]. For 3D reconstruction in content-centric DTs, objects or artwork are scanned in their surroundings using camera [ 1 ], CCD (charge-coupled device) [ 9 ], laser [ 8 , 29 , 42 ], photogrammetry, triangulation in point clouds or other methods [ 9 , 14 , 24 , 38 , 40 ].…”

“…This classification uses the following keywords in the corpus (and specifies the first and following references): Cameras [ 1 ]; Activity recognition [ 2 ]; Sensing in risk-informed DTs to diagnose damage size and location and other failure information [ 3 , 39 ]; Remote sensing [ 4 ], in agriculture [ 2 ] (measuring emitted or reflected radiation by satellite or aircraft); Sensors collect data on temperature, humidity, noise and people’s movement [ 4 , 18 ] to diagnose damage size and location and other failure information [ 4 ]; Satellite sensors gather data for inertial localization [ 5 ], sensing for point clouds [ 14 , 28 ]; Extended reality (XR) smart glasses [ 5 , 6 , 40 ]; 3D interaction techniques: glasses, gloves, hand/body trackers, helmet and external sensors [ 6 ], eye trackers [ 12 , 18 ]; Scanning: Laser [ 8 , 29 , 42 ]; Photogrammetry [ 9 , 14 , 24 , 38 , 40 ], CCD [ 9 ], drone sensing [ 10 , 15 , 43 ]; Embedded IoT-based sensors [ 10 ]; Sensors for ecosystems [ 11 ]; Multimodal sensory perception that handles speech, dialogue flow, gestures, shock, pressure [ 12 ]; Optical sensors [ 13 , 27 ], gloves (with optical sensors) [ …”

“…Based on a reference corpus resulting from a search for scientific publications in books, journals and conference papers on the keywords virtual museums , digital twins , emerging technologies and sensor in leading science databases [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ], we classify DTs according to their application areas, relevant technologies and concepts depending on type, focus and features, sensor technology used and adaptation or innovation power throughout their life cycle. Design, realization, operation and evolution are guided by experts, engineers, customers, curators, software engineers and visitors, all of whom define adequate quality criteria (QC) and metrics (QM) for DTs and ViMs V&VA.…”

“…In this review paper, we examine prominent science databases for occurrences of the terms virtual, museum, digital, twin, emerging, technologies, and sensor in journals, book chapters, conference papers and ePublications. Recent searches in Scopus, IEEEXplore, and Google Scholar with the search string “virtual AND museum AND digital AND twin AND emerging AND technologies AND sensor” yield 43 relevant publications [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ] from the last 13 years, 34 of which were in Scopus, 3 of which were excluded because the keywords were used in other meanings, such as “Siamese twins” (cf. Figure 1 and Figure A1 in the Appendix A ).…”