Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review
<i>Background:</i> Autonomous ships have the potential to increase operational efficiency and reduce carbon footprints through technology and innovation. However, there is no comprehensive literature review of all the different types of papers related to autonomous ships, especially with...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-02-01
|
| Series: | Logistics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2305-6290/8/1/23 |
| _version_ | 1797240248775737344 |
|---|---|
| author | Enna Hirata Annette Skovsted Hansen |
| author_facet | Enna Hirata Annette Skovsted Hansen |
| author_sort | Enna Hirata |
| collection | DOAJ |
| description | <i>Background:</i> Autonomous ships have the potential to increase operational efficiency and reduce carbon footprints through technology and innovation. However, there is no comprehensive literature review of all the different types of papers related to autonomous ships, especially with regard to their integration with ports. This paper takes a systematic review approach to extract and summarize the main topics related to autonomous ships in the fields of container shipping and port management. <i>Methods:</i> A machine learning method is used to extract the main topics from more than 2000 journal publications indexed in WoS and Scopus. <i>Results:</i> The research findings highlight key issues related to technology, cybersecurity, data governance, regulations, and legal frameworks, providing a different perspective compared to human manual reviews of papers. <i>Conclusions:</i> Our search results confirm several recommendations. First, from a technological perspective, it is advised to increase support for the research and development of autonomous underwater vehicles and unmanned aerial vehicles, establish safety standards, mandate testing of wave model evaluation systems, and promote international standardization. Second, from a cyber–physical systems perspective, efforts should be made to strengthen logistics and supply chains for autonomous ships, establish data governance protocols, enforce strict control over IoT device data, and strengthen cybersecurity measures. Third, from an environmental perspective, measures should be implemented to address the environmental impact of autonomous ships. This can be achieved by promoting international agreements from a global societal standpoint and clarifying the legal framework regarding liability in the event of accidents. |
| first_indexed | 2024-04-24T18:04:25Z |
| format | Article |
| id | doaj.art-0d0f7a1974444b1a90b44fbcb0ce3aad |
| institution | Directory Open Access Journal |
| issn | 2305-6290 |
| language | English |
| last_indexed | 2024-04-24T18:04:25Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Logistics |
| spelling | doaj.art-0d0f7a1974444b1a90b44fbcb0ce3aad2024-03-27T13:51:37ZengMDPI AGLogistics2305-62902024-02-01812310.3390/logistics8010023Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature ReviewEnna Hirata0Annette Skovsted Hansen1Graduate School of Maritime Sciences, Center for Mathematical and Data Sciences, Kobe University, Higashinada-ku, Kobe 658-0022, JapanSchool of Culture and Society, Aarhus University, 8000 Aarhus, Denmark<i>Background:</i> Autonomous ships have the potential to increase operational efficiency and reduce carbon footprints through technology and innovation. However, there is no comprehensive literature review of all the different types of papers related to autonomous ships, especially with regard to their integration with ports. This paper takes a systematic review approach to extract and summarize the main topics related to autonomous ships in the fields of container shipping and port management. <i>Methods:</i> A machine learning method is used to extract the main topics from more than 2000 journal publications indexed in WoS and Scopus. <i>Results:</i> The research findings highlight key issues related to technology, cybersecurity, data governance, regulations, and legal frameworks, providing a different perspective compared to human manual reviews of papers. <i>Conclusions:</i> Our search results confirm several recommendations. First, from a technological perspective, it is advised to increase support for the research and development of autonomous underwater vehicles and unmanned aerial vehicles, establish safety standards, mandate testing of wave model evaluation systems, and promote international standardization. Second, from a cyber–physical systems perspective, efforts should be made to strengthen logistics and supply chains for autonomous ships, establish data governance protocols, enforce strict control over IoT device data, and strengthen cybersecurity measures. Third, from an environmental perspective, measures should be implemented to address the environmental impact of autonomous ships. This can be achieved by promoting international agreements from a global societal standpoint and clarifying the legal framework regarding liability in the event of accidents.https://www.mdpi.com/2305-6290/8/1/23autonomous shipcontainer porttopic modelbertopicmachine learningnatural language processing |
| spellingShingle | Enna Hirata Annette Skovsted Hansen Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review Logistics autonomous ship container port topic model bertopic machine learning natural language processing |
| title | Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review |
| title_full | Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review |
| title_fullStr | Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review |
| title_full_unstemmed | Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review |
| title_short | Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review |
| title_sort | identifying key issues in integration of autonomous ships in container ports a machine learning based systematic literature review |
| topic | autonomous ship container port topic model bertopic machine learning natural language processing |
| url | https://www.mdpi.com/2305-6290/8/1/23 |
| work_keys_str_mv | AT ennahirata identifyingkeyissuesinintegrationofautonomousshipsincontainerportsamachinelearningbasedsystematicliteraturereview AT annetteskovstedhansen identifyingkeyissuesinintegrationofautonomousshipsincontainerportsamachinelearningbasedsystematicliteraturereview |