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Book Chapter

Semi-Automated Visual Quality Control Inspection During Construction or Renovation of Railways Using Deep Learning Techniques and Augmented Reality Visualization

  • Apostolia Gounaridou
  • Evangelia Pantraki
  • Vasileios Dimitriadis
  • Athanasios Tsakiris
  • Dimosthenis Ioannidis
  • Dimitrios Tzovaras

The construction industry stands to greatly benefit from the technological advancements in deep learning and computer vision, which can automate time-consuming tasks such as quality control. In this paper, we introduce a framework that incorporates two advanced tools - the Visual Quality Control (VQC) tool and the Digital Twin visualization with Augmented Reality (DigiTAR) tool - to perform semi-automated visual quality control in the construction site during the execution phase of the project. The VQC tool is a backend service that detects potential defects on images captured on-site using the Mask R-CNN algorithm trained on annotated images of concrete and railway defects. The surveyor, aided by the Augmented Reality (AR) technology through the DigiTAR tool, can in-situ confirm/reject the detected defects and propose remedial actions. All the quality control results are recorded in the relevant BIM model and can be viewed on-site overlaid on the physical construction elements. This solution offers a semi-automated visual inspection that can speed up and simplify the quality control process, especially in case of large linear infrastructures, illustrating the added value of AR-based applications in Digital Twins

  • Keywords:
  • BIM,
  • Augmented Reality,
  • AR in Construction,
  • Deep Learning,
  • Computer Vision,
  • Visual Inspection,
  • Digital Twins,
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Apostolia Gounaridou

Centre for Research and Technology Hellas, Greece - ORCID: 0000-0002-0381-7505

Evangelia Pantraki

Centre for Research and Technology Hellas, Greece - ORCID: 0000-0002-0359-9667

Vasileios Dimitriadis

Centre for Research and Technology Hellas, Greece - ORCID: 0009-0001-8880-119X

Athanasios Tsakiris

Centre for Research and Technology Hellas, Greece - ORCID: 0000-0003-2552-7346

Dimosthenis Ioannidis

Centre for Research and Technology Hellas, Greece - ORCID: 0000-0002-5747-2186

Dimitrios Tzovaras

Centre for Research and Technology Hellas, Greece - ORCID: 0000-0001-6915-6722

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  • Publication Year: 2023
  • Pages: 865-876

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  • Publication Year: 2023

Chapter Information

Chapter Title

Semi-Automated Visual Quality Control Inspection During Construction or Renovation of Railways Using Deep Learning Techniques and Augmented Reality Visualization

Authors

Apostolia Gounaridou, Evangelia Pantraki, Vasileios Dimitriadis, Athanasios Tsakiris, Dimosthenis Ioannidis, Dimitrios Tzovaras

DOI

10.36253/979-12-215-0289-3.86

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

eISBN (pdf)

979-12-215-0289-3

eISBN (xml)

979-12-215-0257-2

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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