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Advancements in Remote Sensing and Digital Twins for Bridge Infrastructure

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 26 October 2024 | Viewed by 823

Special Issue Editors


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Guest Editor
Senior Lecturer, Centre for Infrastructure Engineering, Western Sydney University, Kingswood, NSW 2747, Australia
Interests: bridge engineering and asset management; digital twin development; unmanned aerial vehicle (UAV) based photogrammetry; terrestrial laser scanning (TLS); structural health monitoring (SHM), sustainability, and life cycle management.
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Guest Editor
Senior Research Assistant, Centre for Infrastructure Engineering, Western Sydney University, Kingswood, NSW 2747, Australia
Interests: advanced manufacturing; civil/structural engineering; bridge engineering; structural seismic dampers; digital twin development; bridge health monitoring; bridge information model (BrIM)
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Geoscience and Remote Sensing, Delft University of Technology, 2628 CD Delft, The Netherlands
Interests: building information modeling and digital twins
Special Issues, Collections and Topics in MDPI journals

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Co-Guest Editor
Centre for Infrastructure Engineering, Western Sydney University, Kingswood, NSW 2747, Australia
Interests: digital twin; quality evaluation; geometric accuracy; point cloud; UAV photogrammetry; terrestrial laser scanning (TLS); bridge inspection; 3D model extraction; bridge information model (brim); digitization; image matching; UAV map; tie point filtering; image keypoint selection; keypoint filtering; multi-criteria decision making; bundle block adjustment; image orientation

Special Issue Information

Dear Colleagues,

Over the last few years, emerging technologies have generated significant interests in the management of civil infrastructures. Advanced Unmanned Arial Vehicles (UAV) and laser scanning technologies have become appealing alternatives to labour-intensive, expensive and traditional inspection and maintenance methods, and the increased use of these methods is encouraged for bridge infrastructure asset management, especially bridge health monitoring.

This Special Issue invites contributions demonstrating innovative developments in applying remote sensing technologies to bridge health monitoring, as well as case studies highlighting the various applications of remote sensing technologies in 3D modelling, assessment and management of bridges in different phases of fabrication, construction, operation and maintenance.

The potential topics of this Special Issue include, but are not limited to, the following remote sensing applications:

  • 3D model reconstruction process of bridges using UAV photogrammetry and TLS.
  • Quality inspection of bridge elements.
  • Computer vision and image analysis.
  • Advanced structural health monitoring (SHM)
  • Development of bridge information model (BrIM).
  • Decision making and process tracking with UAVs in bridge infrastructure tasks.
  • Bridge Management System (BMS).
  • Bridges Condition Assessment.
  • Artificial intelligent (AI).
  • Virtual Reality (VR) and Augmented Reality (AR).

Dr. Maria Rashidi
Dr. Masoud Mohammadi
Dr. Linh Truong-Hong
Dr. Vahid Mousavi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital twin
  • UAV-based photogrammetry
  • terrestrial laser scanning (TLS)
  • bridge information model (BrIM)
  • 3D reconstruction
  • computer vision
  • bridge inspection
  • structural assessment
  • bridge management
  • virtual reality (VR)
  • augmented reality (AR)

Published Papers (1 paper)

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Review

39 pages, 2825 KiB  
Review
Evolution of Digital Twin Frameworks in Bridge Management: Review and Future Directions
by Vahid Mousavi, Maria Rashidi, Masoud Mohammadi and Bijan Samali
Remote Sens. 2024, 16(11), 1887; https://doi.org/10.3390/rs16111887 - 24 May 2024
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Abstract
Over the last decade, the digital twin (DT) concept has effectively revolutionized conventional bridge monitoring and management. Despite their overall success, current bridge DTs encounter conceptual ambiguities, hindering their inherent potential for practical implementation. Moreover, intelligent decision support models have not been properly [...] Read more.
Over the last decade, the digital twin (DT) concept has effectively revolutionized conventional bridge monitoring and management. Despite their overall success, current bridge DTs encounter conceptual ambiguities, hindering their inherent potential for practical implementation. Moreover, intelligent decision support models have not been properly considered as a component of the bridge DTs framework to enhance the reliability of decisions for asset maintenance. Therefore, this paper conducts a scientometric analysis and a comprehensive state-of-the-art review, exploring current bridge DT research trends and architectures and introducing an enhanced conceptual framework for bridge DTs. To this end, more than 480 research publications have been reviewed, compared, and analyzed. The research result encompasses the redevelopment of a multilayer DT framework, fostering its implementation in the full lifecycle of bridge infrastructure while exploring the potential integration of decision support systems and data fusion from advanced technologies to improve the overall efficiency of implementing DT technology in bridges. Full article
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