Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91424
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Civil and Environmental Engineering-
dc.creatorHou, Y-
dc.creatorLi, Q-
dc.creatorZhang, C-
dc.creatorLu, G-
dc.creatorYe, Z-
dc.creatorChen, Y-
dc.creatorWang, L-
dc.creatorCao, D-
dc.date.accessioned2021-11-03T06:53:32Z-
dc.date.available2021-11-03T06:53:32Z-
dc.identifier.issn2095-8099-
dc.identifier.urihttp://hdl.handle.net/10397/91424-
dc.language.isoenen_US
dc.publisherGaodeng Jiaoyu Chubansheen_US
dc.rights© 2021 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering andHigher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Hou, Y., Li, Q., Zhang, C., Lu, G., Ye, Z., Chen, Y., ... & Cao, D. (2021). The state-of-the-art review on applications of intrusive sensing, image processing techniques, and machine learning methods in pavement monitoring and analysis. Engineering is available at https://doi.org/10.1016/j.eng.2020.07.030en_US
dc.subjectImage processing techniquesen_US
dc.subjectIntrusive sensingen_US
dc.subjectMachine learning methodsen_US
dc.subjectPavement monitoring and analysisen_US
dc.subjectThe state-of-the-art reviewen_US
dc.titleThe state-of-the-art review on applications of intrusive sensing, image processing techniques, and machine learning methods in pavement monitoring and analysisen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage845-
dc.identifier.epage856-
dc.identifier.volume7-
dc.identifier.issue6-
dc.identifier.doi10.1016/j.eng.2020.07.030-
dcterms.abstractIn modern transportation, pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians. Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users. Therefore, monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance, which in turn ensures public transportation safety. Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions. Advanced technologies can be employed for the collection and analysis of such data, including various intrusive sensing techniques, image processing techniques, and machine learning methods. This review summarizes the state-of-the-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEngineering, June 2021, v. 7, no. 6, p. 845-856-
dcterms.isPartOfEngineering-
dcterms.issued2021-06-
dc.identifier.scopus2-s2.0-85107769598-
dc.identifier.eissn2096-0026-
dc.description.validate202110 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
1-s2.0-S2095809920303799-main.pdf1.2 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

48
Last Week
1
Last month
Citations as of Sep 24, 2023

Downloads

5
Citations as of Sep 24, 2023

SCOPUSTM   
Citations

104
Citations as of Sep 28, 2023

WEB OF SCIENCETM
Citations

100
Citations as of Sep 28, 2023

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.