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Selected Papers from 2nd International Conference on Maritime IT Convergence...
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Selected Papers from 2nd International Conference on Maritime IT Convergence (ICMIC)

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (15 November 2023) | Viewed by 9631

Special Issue Editor

Prof. Dr. Wooyeol Choi

E-Mail Website
Guest Editor
Department of Computer Engineering, Chosun University, Gwangju 61452, Republic of Korea
Interests: PHY/MAC cross-layer protocols; machine learning-based resource allocation; SDR-based performance verification for wireless networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The International Conference on Maritime IT Convergence (ICMIC) will be inaugurated in 2023 with the aim to promote convergence activities of maritime and terrestrial communications, as well as related wireless communications. As maritime communications usually involve ship-to-ship and ship-to-shore communication, maritime ICT technologies will facilitate the maturation and evolution of terrestrial wired/wireless communication technologies for use in future smart maritime communications. More specifically, this Special Issue will focus on addressing the challenges in maritime communications with ICT convergence or advanced wireless communications over various sectors, include the industrial, academic and practical engineering sectors. This Special Issue will be composed of selected papers from the ICMIC 2023 Conference, extended and reviewed to meet the high standard of publication in Electronics. Potential topics in this Special Issue include the following keywords but are not limited to these presented topics.

Prof. Dr. Wooyeol Choi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • maritime wireless communications
  • maritime artificial intelligence and machine learning
  • 6G, 5G and LTE-advanced networks
  • autonomous driving
  • remote control
  • unmanned aerial vehicle
  • underwater wireless communications
  • machine-to-machine and D2D communications
  • military communication technologies
  • satellite communications
  • Internet of Things
  • mobile cloud computing
  • mobile S/W and data science
  • Bbg data and smart computing
  • deep-learning-based object recognition
  • behavior pattern awareness
  • VR and AR
  • metaverse applications
  • indoor positioning and navigation systems
  • smart factory
  • u-healthcare systems, bio-informatics and their applications
  • smart cities
  • vehicular information and communication technologies
  • intelligent transportation systems
  • encryption and security for ICT convergence
  • block chain

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Published Papers (4 papers)

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Research

27 pages, 1509 KiB  
Article
Zero-Trust Marine Cyberdefense for IoT-Based Communications: An Explainable Approach
by Ebuka Chinaechetam Nkoro, Judith Nkechinyere Njoku, Cosmas Ifeanyi Nwakanma, Jae-Min Lee and Dong-Seong Kim
Electronics 2024, 13(2), 276; https://doi.org/10.3390/electronics13020276 - 8 Jan 2024
Cited by 5 | Viewed by 3222
Abstract
Integrating Explainable Artificial Intelligence (XAI) into marine cyberdefense systems can address the lack of trustworthiness and low interpretability inherent in complex black-box Network Intrusion Detection Systems (NIDS) models. XAI has emerged as a pivotal focus in achieving a zero-trust cybersecurity strategy within marine [...] Read more.
Integrating Explainable Artificial Intelligence (XAI) into marine cyberdefense systems can address the lack of trustworthiness and low interpretability inherent in complex black-box Network Intrusion Detection Systems (NIDS) models. XAI has emerged as a pivotal focus in achieving a zero-trust cybersecurity strategy within marine communication networks. This article presents the development of a zero-trust NIDS framework designed to detect contemporary marine cyberattacks, utilizing two modern datasets (2023 Edge-IIoTset and 2023 CICIoT). The zero-trust NIDS model achieves an optimal Matthews Correlation Coefficient (MCC) score of 97.33% and an F1-score of 99% in a multi-class experiment. The XAI approach leverages visual and quantitative XAI methods, specifically SHapley Additive exPlanations (SHAP) and the Local Interpretable Model-agnostic Explanations (LIME) algorithms, to enhance explainability and interpretability. The research results indicate that current black-box NIDS models deployed for marine cyberdefense can be made more reliable and interpretable, thereby improving the overall cybersecurity posture of marine organizations. Full article
(This article belongs to the Special Issue Selected Papers from 2nd International Conference on Maritime IT Convergence (ICMIC))
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22 pages, 8852 KiB  
Article
Ship Classification Based on AIS Data and Machine Learning Methods
by I-Lun Huang, Man-Chun Lee, Chung-Yuan Nieh and Juan-Chen Huang
Electronics 2024, 13(1), 98; https://doi.org/10.3390/electronics13010098 - 25 Dec 2023
Cited by 3 | Viewed by 2636
Abstract
AIS ship-type code categorizes ships into broad classes, such as fishing, passenger, and cargo, yet struggles with finer distinctions among cargo ships, such as bulk carriers and containers. Different ship types significantly impact acceleration, steering performance, and stopping distance, thus making precise identification [...] Read more.
AIS ship-type code categorizes ships into broad classes, such as fishing, passenger, and cargo, yet struggles with finer distinctions among cargo ships, such as bulk carriers and containers. Different ship types significantly impact acceleration, steering performance, and stopping distance, thus making precise identification of unfamiliar ship types crucial for maritime monitoring. This study introduces an original classification study based on AIS data for cargo ships, presenting a classifier tailored for bulk carriers, containers, general cargo, and vehicle carriers. The model’s efficacy was tested within the Changhua Wind Farm Channel using eight classification algorithms across tree-structure-based, proximity-based, and regression-based categories and employing standard metrics (Accuracy, Precision, Recall, F1-score) to assess the performance. The results show that tree-structure-based algorithms, particularly XGBoost and Random Forest, demonstrated superior performance. This study also implemented a feature selection strategy with five methods, revealing that a model trained with only four features (three ship-geometric features and one trajectory behavior feature) can achieve high accuracy. Conclusively, the classifier effectively overcame the challenges of limited AIS data labels, achieving a classification accuracy of 97% for ships in the Changhua Wind Farm Channel. These results are pivotal in identifying abnormal ship behavior, highlighting the classifier’s potential for maritime monitoring applications. Full article
(This article belongs to the Special Issue Selected Papers from 2nd International Conference on Maritime IT Convergence (ICMIC))
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26 pages, 7167 KiB  
Article
Enhancing Security and Accountability in Autonomous Vehicles through Robust Speaker Identification and Blockchain-Based Event Recording
by Judith Nkechinyere Njoku, Cosmas Ifeanyi Nwakanma, Jae-Min Lee and Dong-Seong Kim
Electronics 2023, 12(24), 4998; https://doi.org/10.3390/electronics12244998 - 13 Dec 2023
Cited by 2 | Viewed by 1874
Abstract
As the deployment of Autonomous Vehicles (AVs) gains momentum, ensuring both security and accountability becomes paramount. This paper proposes a comprehensive approach to address these concerns. With the increasing importance of speaker identification, our first contribution lies in implementing a robust mechanism for [...] Read more.
As the deployment of Autonomous Vehicles (AVs) gains momentum, ensuring both security and accountability becomes paramount. This paper proposes a comprehensive approach to address these concerns. With the increasing importance of speaker identification, our first contribution lies in implementing a robust mechanism for identifying authorized users within AVs, enhancing security. To counter the threat of voice spoofing, an ensemble-based approach leveraging speaker verification techniques is presented, ensuring the authenticity of user commands. Furthermore, in scenarios of accidents involving AVs, the need for accurate accountability and liability allocation arises. To address this, we introduce a novel application of blockchain technology, enabling an event recording system that ensures transparent and tamper-proof records. The proposed system enhances AV security and establishes a framework for reliable accident investigation using speakers’ records. In addition, this paper presents an innovative concept where vehicles act as impartial judges during accidents, utilizing location-based identification. Results show the viability of the proposed solution for accident investigation and analysis. Full article
(This article belongs to the Special Issue Selected Papers from 2nd International Conference on Maritime IT Convergence (ICMIC))
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12 pages, 5827 KiB  
Article
Automatic Verticality Monitoring and Securing System for Large Circular Steel Pipes
by Sungmin Koo, Haeyong Park, Myounghak Oh and Seungjae Baek
Electronics 2023, 12(24), 4989; https://doi.org/10.3390/electronics12244989 - 13 Dec 2023
Viewed by 1008
Abstract
Securing the verticality of foundations is a crucial factor for ensuring safety in offshore construction. The repeated intrusion-pulling method is generally used to ensure verticality in suction bucket foundation construction processes. However, it relies heavily on the experience and skills of field workers [...] Read more.
Securing the verticality of foundations is a crucial factor for ensuring safety in offshore construction. The repeated intrusion-pulling method is generally used to ensure verticality in suction bucket foundation construction processes. However, it relies heavily on the experience and skills of field workers and is relatively time-consuming. To address this problem, we propose an automatic verticality securing system for large circular steel pipes based on a verticality monitoring system. This system adjusts cables at locations where verticality correction is required without changing the existing suction pile–penetration–construction process. It includes a monitoring component that provides real-time data on pipe alignment and an automatic lifting cable control system that maintains perpendicularity using data acquired from the monitoring system. The monitoring system comprises a sensor, an embedded controller, and a display program that displays the vertical information of circular steel pipes. The automatic lifting cable control system includes a controller with an algorithm for adjusting the length of the actuator. We showed that the system operates satisfactorily and secures the verticality of less than 0.2° in the suction bucket-based model experiment. Furthermore, the testbed experimental results show that our monitoring system can efficiently measure verticality information in real time. Full article
(This article belongs to the Special Issue Selected Papers from 2nd International Conference on Maritime IT Convergence (ICMIC))
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