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      KCI등재 SCIE SCOPUS

      UAV-RFID Integration for Construction Resource Localization

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      https://www.riss.kr/link?id=A106832102

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      다국어 초록 (Multilingual Abstract)

      Location data of construction resources are important in understanding on the context of a construction site, yet most sites still rely on people’s observations to localize their resources. Among then various localization technologies, radio frequen...

      Location data of construction resources are important in understanding on the context of a construction site, yet most sites still rely on people’s observations to localize their resources. Among then various localization technologies, radio frequency identification (RFID) is considered as a good solution. However, RFID either provides limited location data when fixed receivers are used, or it requires considerable manpower for scanning the tagged resources when hand-held receivers are used. These requirements result in inefficiency and impractical demands on time and cost, particularly in the case of complex or large-scale sites. This study attempted to overcome the limitations by proposing an integrated unmanned aerial vehicle-RFID (UAV-RFID) platform to replace the considerable manpower with the UAV and to enable identifying tags on a site. It applies deep learning algorithms to localize an RFID tag position within an acceptable range of accuracy, thereby demonstrating the feasibility of the integrated platform for construction resource localization.

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      참고문헌 (Reference)

      1 Caldas CH, "Using global positioning system to improve materials-locating processes on industrial projects" 132 (132): 741-749, 2006

      2 Zhao Y, "Saliency detection and deep learning-based wildfire identification in UAV imagery" 18 (18): 712-, 2018

      3 Buffi A, "SARFID on drone: Drone-based UHF-RFID tag localization" 2017

      4 Chai J, "Reference tag supported RFID tracking using robust support vector regression and Kalman filter" 32 : 1-10, 2017

      5 Hildreth J, "Reduction of short-interval GPS data for construction operations analysis" 131 (131): 920-927, 2005

      6 Li H, "Real-time locating systems applications in construction" 63 : 37-47, 2016

      7 He T, "Range-free localization schemes for large scale sensor networks" 2003

      8 Almuzaini KK, "Range-based localization in wireless networks using density-based outlier detection" 2 (2): 807-814, 2010

      9 Montaser A, "RFID indoor location identification for construction projects" 39 (39): 167-179, 2014

      10 Omni-ID, "Power 400/415 datasheet"

      1 Caldas CH, "Using global positioning system to improve materials-locating processes on industrial projects" 132 (132): 741-749, 2006

      2 Zhao Y, "Saliency detection and deep learning-based wildfire identification in UAV imagery" 18 (18): 712-, 2018

      3 Buffi A, "SARFID on drone: Drone-based UHF-RFID tag localization" 2017

      4 Chai J, "Reference tag supported RFID tracking using robust support vector regression and Kalman filter" 32 : 1-10, 2017

      5 Hildreth J, "Reduction of short-interval GPS data for construction operations analysis" 131 (131): 920-927, 2005

      6 Li H, "Real-time locating systems applications in construction" 63 : 37-47, 2016

      7 He T, "Range-free localization schemes for large scale sensor networks" 2003

      8 Almuzaini KK, "Range-based localization in wireless networks using density-based outlier detection" 2 (2): 807-814, 2010

      9 Montaser A, "RFID indoor location identification for construction projects" 39 (39): 167-179, 2014

      10 Omni-ID, "Power 400/415 datasheet"

      11 Cheng T, "Performance evaluation of ultra wideband technology for construction resource location tracking in harsh environments" 20 (20): 1173-1184, 2011

      12 Jung S, "Perception, guidance, and navigation for indoor autonomous drone racing using deep learning" 3 (3): 2539-2544, 2018

      13 Haque IT, "On the impact of node placement and profile point selection on indoor localization" 308 : 220-231, 2009

      14 Torrent DG, "Methodology for automating the identification and localization of construction components on industrial projects" 23 (23): 3-13, 2009

      15 Senta Y, "Machine learning approach to self-localization of mobile robots using RFID tag" 2007

      16 Sak H, "Long short-term memory recurrent neural network architectures for large scale acoustic modeling" Singapore 2014

      17 Hochreiter S, "Long short-term memory" 9 (9): 1735-1780, 1997

      18 Rojas EM, "Labor productivity drivers and opportunities in the construction industry" 19 (19): 78-82, 2003

      19 Valero E, "Integration of RFID with other technologies in construction" 94 : 614-620, 2016

      20 El-Omari S, "Integrating automated data acquisition technologies for progress reporting of construction projects" 20 (20): 699-705, 2011

      21 Jaselskis EJ, "Implementing radio frequency identification in the construction process" 129 (129): 680-688, 2003

      22 Claire S, "Gammon steel tracks modular components for buildings"

      23 Soltani MM, "Enhancing Cluster-based RFID Tag Localization using artificial neural networks and virtual reference tags" 2013

      24 Ma Y, "Drone relays for battery-free networks" 2017

      25 Fumio H, "Development of digital photo system using RFID technology in plant construction management" 2009

      26 Torrent DG, "Development of a methodology for automating the identification and localization of engineered components and assessment of its impact on construction craft productivity" University of Texas at Austin 2008

      27 Shahi A, "Deterioration of UWB positioning during construction" 24 : 72-80, 2012

      28 Ammour N, "Deep learning approach for car detection in UAV imagery" 9 (9): 312-, 2017

      29 Claire S, "DPR construction uses RFID Journal"

      30 Singhvi V, "Context-aware information system for construction site applications" 2003

      31 Thomas HR, "Construction site management and labor productivity improvement: How to improve the bottom line and shorten the project schedule" ASCE Press 2017

      32 Won D, "Construction resource localization based on UAV-RFID platform using machine learning algorithm" 2018

      33 Fang Y, "Case study of BIM and cloud–enabled real-time RFID indoor localization for constructionmanagement applications" 142 (142): 05016003-, 2016

      34 Sacks R, "Building project model support for automated labor monitoring" 17 (17): 19-27, 2003

      35 Song J, "Automating the task of tracking the delivery and receipt of fabricated pipe spools in industrial projects" 15 (15): 166-177, 2006

      36 Pradhananga N, "Automatic spatio-temporal analysis of construction site equipment operations using GPS data" 29 : 107-122, 2013

      37 Claire S, "Australian oil refinery construction site tries out RFID"

      38 Claire S, "At construction sites, RFID tracks arrivals, departures"

      39 Soleimanifar M, "Applying received signal strength based methods for indoor positioning and tracking in construction applications" 41 (41): 703-716, 2014

      40 Krishnan P, "A system for LEASE: Location estimation assisted by stationary emitters for indoor RF wireless networks" 2004

      41 Soleimanifar M, "A robust positioning architecture for construction resources localization using wireless sensor networks" 2011

      42 Yang J, "A performance evaluation of vision and radio frequency tracking methods for interacting workforce" 25 (25): 736-747, 2011

      43 Kim Y-S, "A model for automation of infrastructure maintenance using representational forms" 10 (10): 57-68, 2000

      44 Dionisio-Ortega S, "A deep learning approach towards autonomous flight in forest environments" 2018

      45 Mok E, "A case study on the feasibility and performance of an UWB-AoA real time location system for resources management of civil construction projects" 4 (4): 23-32, 2010

      46 Cai H, "A boundary condition based algorithm for locating construction site objects using RFID and GPS" 28 (28): 455-468, 2014

      47 Du JC, "3D laser scanning and GPS technology for landslide earthwork volume estimation" 16 (16): 657-663, 2007

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2005-05-27 학술지명변경 한글명 : 대한토목학회 영문논문집 -> KSCE Journal of Civil Engineering KCI등재
      2005-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2004-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2002-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.59 0.12 0.49
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.42 0.39 0.286 0.06
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