TwinPort: 5G drone-assisted data collection with digital twin for smart seaports

Yagmur Yigit, Long D. Nguyen, Mehmet Ozdem, Omer Kemal Kinaci, Trang Hoang, Berk Canberk, Trung Q. Duong*

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

26 Atıf (Scopus)

Özet

Numerous ports worldwide are adopting automation to boost productivity and modernize their operations. At this point, smart ports become a more important paradigm for handling increasing cargo volumes and increasing operational efficiency. In fact, as ports become more congested and cargo volumes increase, the need for accurate navigation through seaports is more pronounced to avoid collisions and the resulting consequences. To this end, digital twin (DT) technology in the fifth-generation (5G) networks and drone-assisted data collection can be combined to provide precise ship maneuvering. In this paper, we propose a DT model using drone-assisted data collection architecture, called TwinPort, to offer a comprehensive port management system for smart seaports. We also present a recommendation engine to ensure accurate ship navigation within a smart port during the docking process. The experimental results reveal that our solution improves the trajectory performance by approaching the desired shortest path. Moreover, our solution supports significantly reducing financial costs and protecting the environment by reducing fuel consumption.

Orijinal dilİngilizce
Makale numarası12310
DergiScientific Reports
Hacim13
Basın numarası1
DOI'lar
Yayın durumuYayınlandı - Ara 2023

Bibliyografik not

Publisher Copyright:
© 2023, The Author(s).

Finansman

Yagmur Yigit would like to thank the ITU-Turkcell and ITU-BTS Graduate Research Scholarship Programme for their support. The work of Trang Hoang is funded by Vietnam National University HoChiMinh City (VNU-HCM) under grant number: DS2023-20-03. The work of Trung Q. Duong was funded by U.K. Engineering and Physical Sciences Research Council under Grant EP/P019374/1. The work was supported by U.K. Engineering and Physical Sciences Research Council under Grant EP/P019374/1 and in part by the UKRI in the UKRI-Horizon Europe program with the UKRI reference number 10061165 under MISO project “Autonomous Multi-Format In-Situ Observation Platform for Atmospheric Carbon Dioxide and Methane Monitoring in Permafrost & Wetlands.

FinansörlerFinansör numarası
ITU-BTS
ITU-Turkcell
Vietnam National University HoChiMinh CityDS2023-20-03
UK Research and Innovation10061165
Engineering and Physical Sciences Research CouncilEP/P019374/1

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