| Title: |
Chapter Semi-Automated Visual Quality Control Inspection During Construction or Renovation of Railways Using Deep Learning Techniques and Augmented Reality Visualization |
| Authors: |
Gounaridou, Apostolia; Pantraki, Evangelia; Dimitriadis, Vasileios; Tsakiris, Athanasios; Ioannidis, Dimosthenis; Tzovaras, Dimitrios |
| Publisher Information: |
Florence: Firenze University Press, 2024. |
| Publication Year: |
2024 |
| Collection: |
Book chapters; Imported or submitted locally |
| Original Material: |
bf65d21a-78e5-4ba2-983a-dbfa90962870; 137 |
| Subject Terms: |
BIM; Augmented Reality; AR in Construction; Deep Learning; Computer Vision; Visual Inspection; Digital Twins; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTV Virtualization |
| Description: |
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 |
| Document Type: |
chapter |
| File Description: |
application/pdf |
| Language: |
English |
| ISBN: |
979-1-221-50289-3 |
| ISSN: |
2704-5846 |
| Relation: |
Proceedings e report |
| DOI: |
10.36253/979-12-215-0289-3.86 |
| Access URL: |
https://library.oapen.org/handle/20.500.12657/89046 |
| Rights: |
URL: https://creativecommons.org/licenses/by-nc/4.0/legalcode |
| Notes: |
ONIX_20240402_9791221502893_15; ; https://library.oapen.org/handle/20.500.12657/89046; ; https://books.fupress.com/doi/capitoli/979-12-215-0289-3_86 |
| Accession Number: |
edsoap.20.500.12657.89046 |
| Database: |
OAPEN Library |