Drone-based bridge inspections : Current practices and future directions
(2025) In Automation in Construction 173.- Abstract
As transportation infrastructure networks continue to age, bridges have become critical components requiring monitoring activities to ensure safety and functionality. Inspections and Structural Health Monitoring (SHM) play a vital role in aiding decision-makers in maintaining structural integrity. Drones have gained popularity for bridge inspections because they offer enhanced safety, efficiency, and cost-effectiveness compared to traditional methods. This paper provides a multi-faceted review of existing research on drone-based bridge monitoring, focusing on equipment, inspection procedures, outcomes, the Internet of Drones (IoD), and associated communication technologies, exploring current limitations, future directions and potential... (More)
As transportation infrastructure networks continue to age, bridges have become critical components requiring monitoring activities to ensure safety and functionality. Inspections and Structural Health Monitoring (SHM) play a vital role in aiding decision-makers in maintaining structural integrity. Drones have gained popularity for bridge inspections because they offer enhanced safety, efficiency, and cost-effectiveness compared to traditional methods. This paper provides a multi-faceted review of existing research on drone-based bridge monitoring, focusing on equipment, inspection procedures, outcomes, the Internet of Drones (IoD), and associated communication technologies, exploring current limitations, future directions and potential advancements. In the near future, it is expected that the application of computer vision techniques to drone-captured imagery will expand the possibilities for automated surface damage detection and extraction of dynamic structural features. The main challenges lie in the integration with IoD, and the standardization of the procedures, paving the way for fully automated drone-assisted inspections.
(Less)
- author
- Panigati, Tommaso
; Zini, Mattia
; Striccoli, Domenico
; Giordano, Pier Francesco
; Tonelli, Daniel
; Limongelli, Maria Pina
LU
and Zonta, Daniele
- organization
- publishing date
- 2025-05
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Bridge inspection, Computer vision, Drone, Internet of drones, IoD, Modal identification, SHM, Structural health monitoring, Surface damage detection, UAV, Unmanned aerial vehicle
- in
- Automation in Construction
- volume
- 173
- article number
- 106101
- publisher
- Elsevier
- external identifiers
-
- scopus:85219037369
- ISSN
- 0926-5805
- DOI
- 10.1016/j.autcon.2025.106101
- language
- English
- LU publication?
- yes
- id
- 0c2b3286-7141-4f94-a64d-01c755b95d93
- date added to LUP
- 2025-06-11 14:05:21
- date last changed
- 2025-06-11 14:05:57
@article{0c2b3286-7141-4f94-a64d-01c755b95d93, abstract = {{<p>As transportation infrastructure networks continue to age, bridges have become critical components requiring monitoring activities to ensure safety and functionality. Inspections and Structural Health Monitoring (SHM) play a vital role in aiding decision-makers in maintaining structural integrity. Drones have gained popularity for bridge inspections because they offer enhanced safety, efficiency, and cost-effectiveness compared to traditional methods. This paper provides a multi-faceted review of existing research on drone-based bridge monitoring, focusing on equipment, inspection procedures, outcomes, the Internet of Drones (IoD), and associated communication technologies, exploring current limitations, future directions and potential advancements. In the near future, it is expected that the application of computer vision techniques to drone-captured imagery will expand the possibilities for automated surface damage detection and extraction of dynamic structural features. The main challenges lie in the integration with IoD, and the standardization of the procedures, paving the way for fully automated drone-assisted inspections.</p>}}, author = {{Panigati, Tommaso and Zini, Mattia and Striccoli, Domenico and Giordano, Pier Francesco and Tonelli, Daniel and Limongelli, Maria Pina and Zonta, Daniele}}, issn = {{0926-5805}}, keywords = {{Bridge inspection; Computer vision; Drone; Internet of drones; IoD; Modal identification; SHM; Structural health monitoring; Surface damage detection; UAV; Unmanned aerial vehicle}}, language = {{eng}}, publisher = {{Elsevier}}, series = {{Automation in Construction}}, title = {{Drone-based bridge inspections : Current practices and future directions}}, url = {{http://dx.doi.org/10.1016/j.autcon.2025.106101}}, doi = {{10.1016/j.autcon.2025.106101}}, volume = {{173}}, year = {{2025}}, }