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Volume 25
Issue 18
10.3390/s25185708
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Review

Methodologies for Remote Bridge Inspection—Review

by
Diogo Ribeiro
1,2,
Anna M. Rakoczy
3,
Rafael Cabral
2,
Vedhus Hoskere
4,
Yasutaka Narazaki
5,
Ricardo Santos
1,2,
Gledson Tondo
6,
Luis Gonzalez
7,
José Campos Matos
7,
Marcos Massao Futai
8,
Yanlin Guo
9,
Adriana Trias
10,
Joaquim Tinoco
7,
Vanja Samec
11,
Tran Quang Minh
7,
Fernando Moreu
12,
Cosmin Popescu
13,
Ali Mirzazade
14,
Tomás Jorge
1,*,
Jorge Magalhães
1,
Franziska Schmidt
15,
João Ventura
1 and
João Fonseca
1add Show full author list remove Hide full author list
1
iBuilt, School of Engineering, Polytechnic of Porto, 4249-015 Porto, Portugal
2
CONSTRUCT-iRail, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
3
Department of Civil Engineering, Warsaw University of Technology, 00-637 Warsaw, Poland
4
Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77004, USA
5
ZJU-UIUC Institute, Zhejiang University, 718 East Haizhou Road, Haining 314400, China
6
Department of Modelling and Simulation of Structures, Faculty of Civil and Environmental Engineering, Bauhaus-Universität Weimar, 99423 Weimar, Germany
7
ISISE, Department of Civil Engineering, University of Minho, 4800-058 Guimarães, Portugal
8
Department of Structural Engineering and Geotechnics, University of São Paulo, São Paulo 05508-220, Brazil
9
Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80521, USA
10
Civil and Environmental Engineering Department, Rowan University, Glassboro, NJ 08028, USA
11
Bridge and BIM Consultant, Austria
12
Department of Civil, Construction & Environmental Engineering, University of New Mexico, Albuquerque, NM 87106, USA
13
Sintef Narvik AS, 8517 Narvik, Norway
14
Invator AB, 181 22 Lidingö, Sweden
15
MAST-EMGCU, Université Gustave Eiffel, Champs-sur-Marne, 77420 Paris, France
 
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*
Author to whom correspondence should be addressed.
Sensors 2025, 25(18), 5708; https://doi.org/10.3390/s25185708 (registering DOI)
Submission received: 1 July 2025 / Revised: 14 August 2025 / Accepted: 10 September 2025 / Published: 12 September 2025
(This article belongs to the Special Issue Feature Review Papers in Fault Diagnosis & Sensors)
Review Reports Versions Notes

Abstract

This article addresses the state of the art of methodologies for bridge inspection with potential for inclusion in Bridge Management Systems (BMS) and within the scope of the IABSE Task Group 5.9 on Remote Inspection of Bridges. The document covers computer vision approaches, including 3D geometric reconstitution (photogrammetry, LiDAR, and hybrid fusion strategies), damage and component identification (based on heuristics and Artificial Intelligence), and non-contact measurement of key structural parameters (displacements, strains, and modal parameters). Additionally, it addresses techniques for handling the large volumes of data generated by bridge inspections (Big Data), the use of Digital Twins for asset maintenance, and dedicated applications of Augmented Reality based on immersive environments for bridge inspection. These methodologies will contribute to safe, automated, and intelligent assessment and maintenance of bridges, enhancing resilience and lifespan of transportation infrastructure under changing climate.
Keywords: methodologies; remote bridge inspection; computer vision; Big Data; Digital Twins; Augmented Reality methodologies; remote bridge inspection; computer vision; Big Data; Digital Twins; Augmented Reality

Share and Cite

MDPI and ACS Style

Ribeiro, D.; Rakoczy, A.M.; Cabral, R.; Hoskere, V.; Narazaki, Y.; Santos, R.; Tondo, G.; Gonzalez, L.; Matos, J.C.; Massao Futai, M.; et al. Methodologies for Remote Bridge Inspection—Review. Sensors 2025, 25, 5708. https://doi.org/10.3390/s25185708

AMA Style

Ribeiro D, Rakoczy AM, Cabral R, Hoskere V, Narazaki Y, Santos R, Tondo G, Gonzalez L, Matos JC, Massao Futai M, et al. Methodologies for Remote Bridge Inspection—Review. Sensors. 2025; 25(18):5708. https://doi.org/10.3390/s25185708

Chicago/Turabian Style

Ribeiro, Diogo, Anna M. Rakoczy, Rafael Cabral, Vedhus Hoskere, Yasutaka Narazaki, Ricardo Santos, Gledson Tondo, Luis Gonzalez, José Campos Matos, Marcos Massao Futai, and et al. 2025. "Methodologies for Remote Bridge Inspection—Review" Sensors 25, no. 18: 5708. https://doi.org/10.3390/s25185708

APA Style

Ribeiro, D., Rakoczy, A. M., Cabral, R., Hoskere, V., Narazaki, Y., Santos, R., Tondo, G., Gonzalez, L., Matos, J. C., Massao Futai, M., Guo, Y., Trias, A., Tinoco, J., Samec, V., Minh, T. Q., Moreu, F., Popescu, C., Mirzazade, A., Jorge, T., ... Fonseca, J. (2025). Methodologies for Remote Bridge Inspection—Review. Sensors, 25(18), 5708. https://doi.org/10.3390/s25185708

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