The Application of Artificial Intelligence Technology in Shipping: A Bibliometric Review

Author:

Xiao Guangnian1ORCID,Yang Daoqi1,Xu Lang2,Li Jinpei3,Jiang Ziran4ORCID

Affiliation:

1. School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China

2. College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China

3. School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China

4. School of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China

Abstract

Artificial intelligence (AI) technologies are increasingly being applied to the shipping industry to advance its development. In this study, 476 articles published in the Science Citation Index Expanded (SCI-EXPANDED) and the Social Sciences Citation Index (SSCI) of the Web of Science Core Collection from 2001 to 2022 were collected, and bibliometric methods were applied to conduct a systematic literature of the field of AI technology applications in the shipping industry. The review commences with an annual publication trend analysis, which shows that research in the field has been growing rapidly in recent years. This is followed by a statistical analysis of journals and a collaborative network analysis to identify the most productive journals, countries, institutions, and authors. The keyword “co-occurrence analysis” is then utilized to identify major research clusters, as well as hot research directions in the field, providing directions for future research in the field. Finally, based on the results of the keyword co-occurrence analysis and the content analysis of the papers published in recent years, the research gaps in AIS data applications, ship trajectory, and anomaly detection, as well as the possible future research directions, are discussed. The findings indicate that AIS data in the future research direction are mainly reflected in the analysis of ship behavior and AIS data repair. Ship trajectory in the future research direction is mainly reflected in the deep learning-based method research and the discussion of ship trajectory classification. Anomaly detection in the future research direction is mainly reflected in the application of deep learning technology in ship anomaly detection and improving the efficiency of ship anomaly detection. These insights offer guidance for researchers’ future investigations in this area. In addition, we discuss the implications of research in the field of shipping AI from both theoretical and practical perspectives. Overall, this review can help researchers understand the status and development trend of the application field of AI technology in shipping, correctly grasp the research direction and methodology, and promote the further development of the field.

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

The Youth Foundation of Humanities and Social Science Research of the Ministry of Education

Publisher

MDPI AG

Reference72 articles.

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2. Study on artificial intelligence: The state of the art and future prospects;Zhang;J. Ind. Inf. Integr.,2021

3. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, august 31, 1955;McCarthy;AI Mag.,2006

4. Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey;Ding;Inf. Sci.,2022

5. Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI;Bennetot;Inf. Fusion,2020

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