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Abstrakty
The Internet of things (IoT) ecosystem provides a platform for the connectivity of interrelated smart devices to automate manual processes and reduce labor costs. IoT has brought significant benefits to all industries, including maritime, as various objects (e.g., ports, ships, agents, etc.) are connected to gather and share information within the maritime ecosystem. The innovative technological aspects of IoT are promoting the effective collaboration between the research community and the maritime industry, for enhancing the performance of maritime transportation systems. Therefore, this study discusses recent advances delivered by the IoT and other emerging technologies, like machine learning and computer vision, for smart maritime transportation systems (SMTSs). In particular, the authors present two specific use cases of SMTSs, namely, predictive maintenance and container damage/seal inspection. Moreover, the key benefits of integrating IoT with machine learning and computer vision are highlighted for the above-mentioned use cases. Finally, a discussion is presented to highlight key opportunities along with foreseeable future challenges in adopting these new technologies by the maritime industry.
Rocznik
Tom
Strony
855--858
Opis fizyczny
Bibliogr. 20 poz., fot.
Twórcy
autor
- Cyprus University of Technology, Limassol 3036, Cyprus
autor
- Cyprus University of Technology, Limassol 3036, Cyprus
autor
- Prodevelop S.L, 46001 VALENCIA, Spain
autor
- Prodevelop S.L, 46001 VALENCIA, Spain
autor
- Prodevelop S.L, 46001 VALENCIA, Spain
autor
- Eurogate Container Terminal, Limassol, Cyprus
autor
- Eurogate Container Terminal, Limassol, Cyprus
autor
- Eurogate Container Terminal, Limassol, Cyprus
autor
- Cyprus University of Technology, Limassol 3036, Cyprus
Bibliografia
- 1. S.-J. Chang, G.-Y. Hsu, J.-A. Yang, K.-N. Chen, Y.-F. Chiu, and F.-T. Chang, “Vessel Traffic Analysis for Maritime Intelligent Transportation System,” in Proc. of the 71st Vehicular Technology Conference. IEEE, 2010, pp. 1–4.
- 2. A. Bahnasse, A. Badri, M. Talea, F. E. Louhab, A. Al-Harbi, A. Khiat, and S. Broumi, “WIMAX Technology for Maritime Intelligent Transport Systems Communication,” in Proc. of the 2nd Intl. Conf. on Future Networks and Distributed Systems. ACM, 2018, p. 10.
- 3. S. Aslam, M. P. Michaelides, and H. Herodotou, “Internet of ships: A survey on architectures, emerging applications, and challenges,” IEEE Internet Things J, vol. 7, no. 10, pp. 9714–9727, 2020.
- 4. Y. Yang, M. Zhong, H. Yao, F. Yu, X. Fu, and O. Postolache, “Internet of Things for Smart Ports: Technologies and Challenges,” IEEE Instrumentation & Measurement Magazine, vol. 21, no. 1, pp. 34–43, 2018.
- 5. “World First 5G Container Port in XIAMEN to Explore Driverless Tech,” November 2019, https://www.yicaiglobal.com.
- 6. M. Lind, M. Michaelides, R. Ward, and R. T. Watson, Maritime informatics. Springer, 2021.
- 7. M. Ozturk, M. Jaber, and M. A. Imran, “Energy-Aware Smart Connectivity for IoT Networks: Enabling Smart Ports,” Wireless Communications and Mobile Computing, 2018.
- 8. M. P. Michaelides, H. Herodotou, M. Lind, and R. T. Watson, “Port-2-port communication enhancing short sea shipping performance: The case study of cyprus and the eastern mediterranean,” Sustainability, vol. 11, no. 7, p. 1912, 2019.
- 9. H. S. Bedi and K. Arora, “Monitoring and controlling of industrial crane using programmable logic controllers,” Ind. J. of EEI (IJEEi), vol. 3, no. 2, pp. 115–118, 2015.
- 10. I. Zaman, K. Pazouki, R. Norman, S. Younessi, and S. Coleman, “Challenges and opportunities of big data analytics for upcoming regulations and future transformation of the shipping industry,” Procedia Eng, vol. 194, pp. 537–544, 2017.
- 11. P. Zhang, Y. Wang, G. S. Aujla, A. Jindal, and Y. D. Al-Otaibi, “A blockchain-based authentication scheme and secure architecture for iotenabled maritime transportation systems,” IEEE trans Intell Transp Syst, 2022.
- 12. P. Kumar, G. P. Gupta, R. Tripathi, S. Garg, and M. M. Hassan, “Dltif: Deep learning-driven cyber threat intelligence modeling and identification framework in iot-enabled maritime transportation systems,” IEEE trans Intell Transp Syst, 2021.
- 13. “MarineTraffic – A day in numbers,” March 2020, https://www.marinetraffic.com/blog/a-day-in-numbers/.
- 14. S. Aslam, M. P. Michaelides, and H. Herodotou, “Berth allocation considering multiple quays: A practical approach using cuckoo search optimization,” J Mar Sci Eng, vol. 11, no. 7, p. 1280, 2023.
- 15. I. Lytra, M.-E. Vidal, F. Orlandi, and J. Attard, “A big data architecture for managing oceans of data and maritime applications,” in Intl. Conf. on Engineering, Technology and Innovation. IEEE, 2017, pp. 1216–1226.
- 16. D. Yang, Y. Zhou, W. Huang, and X. Zhou, “5g mobile communication convergence protocol architecture and key technologies in satellite internet of things system,” Alexandria Eng J, vol. 60, no. 1, pp. 465–476, 2021.
- 17. A. Kamolov and S. Park, “An iot-based ship berthing method using a set of ultrasonic sensors,” Sensors, vol. 19, no. 23, p. 5181, 2019.
- 18. M. A. Ben Farah, E. Ukwandu, H. Hindy, D. Brosset, M. Bures, I. Andonovic, and X. Bellekens, “Cyber security in the maritime industry: A systematic survey of recent advances and future trends,” Information, vol. 13, no. 1, p. 22, 2022.
- 19. A. H. S. Mufti, “Quay container crane productivity effectiveness analysis: Case study pt jakarta international container terminal,” Int J Innov Sci Res Technol, vol. 7, no. 8, August 2022.
- 20. F. K. Konstantinidis, S. G. Mouroutsos, and A. Gasteratos, “The role of machine vision in industry 4.0: an automotive manufacturing perspective,” in Intl. Conf. on Imaging Systems and Techniques (IST). IEEE, 2021, pp. 1–6.
Uwagi
1. Thematic Tracks Short Papers
2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d935c2c3-632d-4f1f-b72b-0e49888a155e