5G-Based Real-Time Remote Inspection Support

Image analysis has been increasingly used in damage detection, particularly in the inspection of aging bridges. We adopted the image-analysis-based damage detection technology to study the feasibility of remote inspection support aimed at reducing the number of engineers that are dispatched to bridg...

Full description

Saved in:
Bibliographic Details
Published inElectronics (Basel) Vol. 12; no. 5; p. 1082
Main Authors Yoshikura, Mai, Fukuoka, Tomotaka, Suwa, Taiki, Fujiu, Makoto, Ishizuka, Hisayuki, Takezawa, Kousuke, Ikebayashi, Tomoyuki, Takayama, Junichi
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.03.2023
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Image analysis has been increasingly used in damage detection, particularly in the inspection of aging bridges. We adopted the image-analysis-based damage detection technology to study the feasibility of remote inspection support aimed at reducing the number of engineers that are dispatched to bridge sites. The remote inspection support involves uploading bridge images from the bridge site and then issuing directions and instructions to an onsite inspection engineer while a skilled engineer at a remote location verifies the damage detection results in real time. The 5G interface, which can transfer large volumes of data in a short time, was used to upload images, enabling shorter upload times compared with 4G. In addition, by sharing damage conditions in real-time, the engineer at a remote office could ascertain them in detail and make appropriate decisions without going to the bridge site. The damages are complex in aged bridges and their decision requires extensive experience and knowledge of skilled engineers. We determined that 5G-based inspections are highly efficient because directions and instructions can be received from a bridge site in real time in cases where a skilled engineer’s decision is needed.
AbstractList Image analysis has been increasingly used in damage detection, particularly in the inspection of aging bridges. We adopted the image-analysis-based damage detection technology to study the feasibility of remote inspection support aimed at reducing the number of engineers that are dispatched to bridge sites. The remote inspection support involves uploading bridge images from the bridge site and then issuing directions and instructions to an onsite inspection engineer while a skilled engineer at a remote location verifies the damage detection results in real time. The 5G interface, which can transfer large volumes of data in a short time, was used to upload images, enabling shorter upload times compared with 4G. In addition, by sharing damage conditions in real-time, the engineer at a remote office could ascertain them in detail and make appropriate decisions without going to the bridge site. The damages are complex in aged bridges and their decision requires extensive experience and knowledge of skilled engineers. We determined that 5G-based inspections are highly efficient because directions and instructions can be received from a bridge site in real time in cases where a skilled engineer’s decision is needed.
Audience Academic
Author Takayama, Junichi
Yoshikura, Mai
Ikebayashi, Tomoyuki
Suwa, Taiki
Fujiu, Makoto
Takezawa, Kousuke
Ishizuka, Hisayuki
Fukuoka, Tomotaka
Author_xml – sequence: 1
  givenname: Mai
  surname: Yoshikura
  fullname: Yoshikura, Mai
– sequence: 2
  givenname: Tomotaka
  surname: Fukuoka
  fullname: Fukuoka, Tomotaka
– sequence: 3
  givenname: Taiki
  surname: Suwa
  fullname: Suwa, Taiki
– sequence: 4
  givenname: Makoto
  orcidid: 0000-0003-3480-6347
  surname: Fujiu
  fullname: Fujiu, Makoto
– sequence: 5
  givenname: Hisayuki
  surname: Ishizuka
  fullname: Ishizuka, Hisayuki
– sequence: 6
  givenname: Kousuke
  surname: Takezawa
  fullname: Takezawa, Kousuke
– sequence: 7
  givenname: Tomoyuki
  surname: Ikebayashi
  fullname: Ikebayashi, Tomoyuki
– sequence: 8
  givenname: Junichi
  surname: Takayama
  fullname: Takayama, Junichi
BookMark eNptULFOwzAQtVCRKKVfwFKJlZRz7MT2WCpaKlVCgjJHjnNGqRI72OnA32NUBgbuhns6vffu9K7JxHmHhNxSWDKm4AE7NGPwrjWR5lBQkPkFmeYgVKZylU_-4Csyj_EIqRRlksGU3Bfb7FFHbBavqLvs0PaYUO9HXOxcHJJz693i7TQMPow35NLqLuL8d87I--bpsH7O9i_b3Xq1zwyjdMx4jorzAhVFzaWUAo2VtpFcKIPIOOgaEGhRUtnUWqE0lja1gjJ9BLaWbEbuzr5D8J8njGN19Kfg0skqF7KgUpSqTKzlmfWhO6xaZ_0YtEndYN-alJFt034lOBUcoORJwM4CE3yMAW01hLbX4auiUP1EWf0TJfsGwhlpgQ
Cites_doi 10.1109/TPAMI.2016.2644615
10.1016/j.engfailanal.2020.104813
10.1109/TIP.2018.2878966
ContentType Journal Article
Copyright COPYRIGHT 2023 MDPI AG
2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: COPYRIGHT 2023 MDPI AG
– notice: 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID AAYXX
CITATION
7SP
8FD
8FE
8FG
ABUWG
AFKRA
ARAPS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
HCIFZ
L7M
P5Z
P62
PIMPY
PQEST
PQQKQ
PQUKI
PRINS
DOI 10.3390/electronics12051082
DatabaseName CrossRef
Electronics & Communications Abstracts
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Central (Alumni)
ProQuest Central
Advanced Technologies & Aerospace Database‎ (1962 - current)
ProQuest Central Essentials
AUTh Library subscriptions: ProQuest Central
Technology Collection
ProQuest One Community College
ProQuest Central Korea
SciTech Premium Collection (Proquest) (PQ_SDU_P3)
Advanced Technologies Database with Aerospace
ProQuest Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
ProQuest - Publicly Available Content Database
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
DatabaseTitle CrossRef
Publicly Available Content Database
Advanced Technologies & Aerospace Collection
Technology Collection
Technology Research Database
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
Electronics & Communications Abstracts
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Technology Collection
ProQuest SciTech Collection
ProQuest Central China
ProQuest Central
Advanced Technologies & Aerospace Database
ProQuest One Academic UKI Edition
ProQuest Central Korea
ProQuest One Academic
Advanced Technologies Database with Aerospace
DatabaseTitleList CrossRef

Publicly Available Content Database
Database_xml – sequence: 1
  dbid: 8FG
  name: ProQuest Technology Collection
  url: https://search.proquest.com/technologycollection1
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 2079-9292
ExternalDocumentID A741740064
10_3390_electronics12051082
GeographicLocations Japan
GeographicLocations_xml – name: Japan
GroupedDBID 5VS
8FE
8FG
AAYXX
AFKRA
ALMA_UNASSIGNED_HOLDINGS
ARAPS
BENPR
BGLVJ
CCPQU
CITATION
GROUPED_DOAJ
HCIFZ
IAO
ITC
KQ8
MODMG
M~E
OK1
P62
PIMPY
PROAC
7SP
8FD
ABUWG
AZQEC
DWQXO
L7M
PQEST
PQQKQ
PQUKI
PRINS
ID FETCH-LOGICAL-c311t-42e9445e91ea48887ecf8fd8479cee340ab0e015618dba9e8cf1db9068300fb83
IEDL.DBID BENPR
ISSN 2079-9292
IngestDate Fri Sep 13 03:55:02 EDT 2024
Sat Dec 16 00:35:53 EST 2023
Fri Aug 23 02:37:00 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 5
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c311t-42e9445e91ea48887ecf8fd8479cee340ab0e015618dba9e8cf1db9068300fb83
ORCID 0000-0003-3480-6347
OpenAccessLink https://www.proquest.com/docview/2785187696/abstract/?pq-origsite=%requestingapplication%
PQID 2785187696
PQPubID 2032404
ParticipantIDs proquest_journals_2785187696
gale_infotracacademiconefile_A741740064
crossref_primary_10_3390_electronics12051082
PublicationCentury 2000
PublicationDate 2023-03-01
PublicationDateYYYYMMDD 2023-03-01
PublicationDate_xml – month: 03
  year: 2023
  text: 2023-03-01
  day: 01
PublicationDecade 2020
PublicationPlace Basel
PublicationPlace_xml – name: Basel
PublicationTitle Electronics (Basel)
PublicationYear 2023
Publisher MDPI AG
Publisher_xml – name: MDPI AG
References Badrinarayanan (ref_17) 2017; 39
Kimoto (ref_13) 2019; 35
ref_14
ref_12
ref_11
Nakamura (ref_8) 2022; 1
Qin (ref_16) 2019; 28
ref_1
ref_3
ref_2
Saito (ref_9) 2022; 1
Ribeiro (ref_10) 2020; 117
Dang (ref_5) 2020; 1
Kimoto (ref_6) 2022; 1
Izumi (ref_7) 2021; 2
ref_15
ref_4
References_xml – ident: ref_4
– ident: ref_3
– volume: 1
  start-page: 386
  year: 2022
  ident: ref_8
  article-title: Development of automatic detection method of deterioration area aiming at labor saving of concrete bridge inspection
  publication-title: Infrastruct. Maint. Pract.
  contributor:
    fullname: Nakamura
– ident: ref_2
– volume: 2
  start-page: 545
  year: 2021
  ident: ref_7
  article-title: Automatic crack detection by deep learning model using attention mechanism
  publication-title: AI Data Sci.
  contributor:
    fullname: Izumi
– ident: ref_12
– ident: ref_11
– volume: 39
  start-page: 2481
  year: 2017
  ident: ref_17
  article-title: SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
  publication-title: IEEE Trans. Pattern Anal. Mach. Intell.
  doi: 10.1109/TPAMI.2016.2644615
  contributor:
    fullname: Badrinarayanan
– volume: 1
  start-page: 115
  year: 2022
  ident: ref_6
  article-title: Demonstration of bridge inspection robot technology for regional implementation—Eshima Ohashi Bridge Project
  publication-title: Infrastruct. Maint. Pract.
  contributor:
    fullname: Kimoto
– ident: ref_15
– volume: 1
  start-page: 596
  year: 2020
  ident: ref_5
  article-title: A study on deep learning and accuracy improvement methods for automatic damage recognition in UAV images
  publication-title: AI Data Sci.
  contributor:
    fullname: Dang
– volume: 1
  start-page: 372
  year: 2022
  ident: ref_9
  article-title: Proposal of remote Inspection method for labor saving of bridge inspection through adaptation of AI and VR technology to real bridges
  publication-title: Infrastruct. Maint. Pract.
  contributor:
    fullname: Saito
– ident: ref_14
– volume: 117
  start-page: 104813
  year: 2020
  ident: ref_10
  article-title: Remote inspection of RC structures using unmanned aerial vehicles and heuristic image processing
  publication-title: Eng. Fail. Anal.
  doi: 10.1016/j.engfailanal.2020.104813
  contributor:
    fullname: Ribeiro
– volume: 35
  start-page: 53
  year: 2019
  ident: ref_13
  article-title: Verification of digital image resolution and visible crack width of concrete
  publication-title: J. Struct. Mater. Civ. Eng.
  contributor:
    fullname: Kimoto
– ident: ref_1
– volume: 28
  start-page: 1498
  year: 2019
  ident: ref_16
  article-title: DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
  publication-title: IEEE Transactionson Image Process.
  doi: 10.1109/TIP.2018.2878966
  contributor:
    fullname: Qin
SSID ssj0000913830
Score 2.2887678
Snippet Image analysis has been increasingly used in damage detection, particularly in the inspection of aging bridges. We adopted the image-analysis-based damage...
SourceID proquest
gale
crossref
SourceType Aggregation Database
StartPage 1082
SubjectTerms Accuracy
Bridge inspection
Bridges
Cameras
Communication
Damage detection
Engineers
Experiments
Feasibility studies
Image analysis
Inspection
Real time
Reinforced concrete
Safety and security measures
Structural analysis (Engineering)
Unmanned aerial vehicles
Title 5G-Based Real-Time Remote Inspection Support
URI https://www.proquest.com/docview/2785187696/abstract/
Volume 12
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LT8MwDLaAXeCAeIrBmHpA4kK0pknb5IQG2hhImxACiVuV57HjMa78dmza8ZAQt1Y9VLFj-4tj-wM44V6JKINk0pSRyTJzzLrMsChikUaMSIWn1MB0Vkwe5M1j_rgCk2UvDJVVLn3ip6P2c0c58kFGLPJouroYGEtZALcYnD89M-KPonvWlkxjFToZl3Rh27kYzW7vvvItNP9SibQZPCTwpD_45pl55RntTZX9Ck5_u-jPuDPegs0WMCbDRsPbsBLqHdj4MUZwF87yK3aB0cgndwj7GHV14BPqICTXddNKOa8T4u9ErL0HD-PR_eWEtSwIzAnOF0xmQUuZB82DQWtTZXBRRY9RRWOAEzI1Ng3UEM2Vt0YH5SL3VqcFrjaNVol9WKvndTiAxGlhtNA2GuNl5NLaUri89Dwgzsps3oWz5fKrp2bYRYWHBJJW9Ye0unBKIqrIFEghpq3ox5_RUKlqiGillAR6utBbSrFqbeS1-tbo4f-fj2CdSN6byq8erC1e3sIxQoGF7cOqGl_1W13j2_R99AFYz7cK
link.rule.ids 315,786,790,12792,21416,27957,27958,33408,33779,43635,43840,74392,74659
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV07T8MwELagDMCAeIpCgQxILLUax87DEyqIPqDtgFqpW-TnmJa2_H_umpSChNgiZYh857vv88V3HyH3zGbcCyeoUKmnIo0M1SZS1HOfhB4QKbFYGhiOkt5EvE7jaVVwW1bXKjc5cZ2o7cxgjbwVoYo8hK5MHucfFFWj8O9qJaGxS_YEB-jETvFO97vGgjMvMx6Ww4Y4nO5bW22ZJYtwP2bRL0D6Oy2vsaZzTI4qkhi0S6-ekB1XnJLDH6MDz0gz7tInQCAbvAPVo9jJAU9gdxf0i7J9clYEqNkJ_PqcTDov4-cerZQPqOGMraiInBQidpI5BRGWpc74zFtAEgmgxkWodOiwCZplVivpMuOZ1TJMYLWh1xm_ILViVrhLEhjJleRSe6Ws8ExonXITp5Y54FaRjuukuVl-Pi8HXORwMEBr5X9Yq04e0EQ5bv_VQhlV3eKHj-EgqbwNDCUVSHTqpLGxYl7FxTLfevHq_9d3ZL83Hg7yQX_0dk0OUOS9vPnVILXV4tPdABVY6du1v78AfGOywA
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LTwIxEG4UEqMH4zOiqHsw8ULDdtt99GRAQfBBCJGE26bP44KA_98pW0QT4m2TPWw605nva3dmPoTuiM6oZYZhJlKLWRopLFUksKU2CS0gUqLd1cD7IOmN2csknvj6p4Uvq1znxFWi1lPl7sibkVORh9DlSdP6sojhU_dh9omdgpT70-rlNHZRNWVJDDu82u4MhqOfGxc3ATOjYTl6iMJZv7lRmlmQyO3OLPoDT9uT9Ap5ukfo0FPGoFX6-BjtmOIEHfwaJHiKGvEzbgMe6WAExA-7vg54Ai-YoF-UzZTTInAKnsC2z9C42_l47GGvg4AVJWSJWWQ4Y7HhxAiItyw1ymZWA65wgDjKQiFD41qiSaal4CZTlmjJwwRWG1qZ0XNUKaaFuUCB4lRwyqUVQjNLmJQpVXGqiQGmFcm4hhrr5eezctxFDscEZ618i7Vq6N6ZKHfBsJwLJXxNP3zMjZXKW8BXUuZoTw3V11bMfZQs8o1PL_9_fYv2wNn5W3_weoX2neJ7WQZWR5Xl_MtcAy9Yyhvv8G_IPrhj
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=5G-Based+Real-Time+Remote+Inspection+Support&rft.jtitle=Electronics+%28Basel%29&rft.au=Yoshikura%2C+Mai&rft.au=Fukuoka%2C+Tomotaka&rft.au=Suwa%2C+Taiki&rft.au=Fujiu%2C+Makoto&rft.date=2023-03-01&rft.issn=2079-9292&rft.eissn=2079-9292&rft.volume=12&rft.issue=5&rft.spage=1082&rft_id=info:doi/10.3390%2Felectronics12051082&rft.externalDBID=n%2Fa&rft.externalDocID=10_3390_electronics12051082
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2079-9292&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2079-9292&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2079-9292&client=summon