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
Centre for Research and Technology Hellas, Greece - ORCID: 0000-0002-0381-7505
Centre for Research and Technology Hellas, Greece - ORCID: 0000-0002-0359-9667
Centre for Research and Technology Hellas, Greece - ORCID: 0009-0001-8880-119X
Centre for Research and Technology Hellas, Greece - ORCID: 0000-0003-2552-7346
Centre for Research and Technology Hellas, Greece - ORCID: 0000-0002-5747-2186
Centre for Research and Technology Hellas, Greece - ORCID: 0000-0001-6915-6722
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
Metadata License
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
Metadata License
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