Technology evolution in maritime autonomous systems: A patent-based analysis

Belabyad, M, Pyne, R, Paraskevadakis, D, Chang, C-H and Kontovas, C (2025) Technology evolution in maritime autonomous systems: A patent-based analysis. Ocean & Coastal Management, 267. ISSN 0964-5691

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Abstract

Technology evolution in maritime autonomous systems is moving rapidly, yet the understanding of how different technologies integrate and mature remains limited. This study maps the technological landscape through patent analysis of 5987 patents from 2010 to 2024. The framework combines the following: a) bibliometric analysis, (b) Latent Dirichlet Allocation (LDA) topic modelling for the identification of key topics, c) topic-topic network analysis examining knowledge flows, and d) technology lifecycle analysis and forecasting using comparative growth curve modelling (Bass, Gompertz, and Logistic models). The analysis identifies 20 technological domains organised into seven clusters, with network analysis showing ‘Sensor Integration’ as the most influential technology through centrality metrics. The technology lifecycle assessment shows distinct maturity patterns: 65 % of domains are in growth phase, with safety technologies best predicted by Bass models and complex infrastructural technologies by Gompertz models. Key findings include predicted technology inflection points during 2025–2030, strong interdependencies between domains and emerging cognitive technologies showing high growth potential despite low current maturity. This research offers evidence-based insights for future research studies, research and development (R&D) prioritisation, and investment timing in the development of autonomous shipping. It also demonstrates the effectiveness of integrated patent analytics for technology forecasting, which has potential applications in several areas.

Item Type:	Article
Uncontrolled Keywords:	04 Earth Sciences; 05 Environmental Sciences; 16 Studies in Human Society; Fisheries; 37 Earth sciences; 41 Environmental sciences; 44 Human society
Subjects:	Q Science > QA Mathematics > QA76 Computer software V Naval Science > V Naval Science (General)
Divisions:	Engineering
Publisher:	Elsevier BV
Date of acceptance:	9 May 2025
Date of first compliant Open Access:	22 May 2025
Date Deposited:	22 May 2025 15:32
Last Modified:	22 May 2025 16:00
DOI or ID number:	10.1016/j.ocecoaman.2025.107744
URI:	https://researchonline.ljmu.ac.uk/id/eprint/26401

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