Scientometric insights into the trends and evolution of the underwater sensing technologies and their applications

Par Conseil national de recherches du Canada

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DOI	Trouver le DOI : https://doi.org/10.5530/jscires.13.2.44
Auteur	Rechercher : Ebadi, Ashkan¹Identifiant ORCID : https://orcid.org/0000-0002-4542-9105; Rechercher : Auger, Alain; Rechercher : Gauthier, Yvan¹
Affiliation	Conseil national de recherches du Canada. Technologies numériques
Format	Texte, Article
Sujet	technology trends; research topic evolution; underwater sensing; machine learning; topic modeling.
Résumé	Underwater sensing has a wide range of applications including the location and monitoring of subsurface infrastructures such as cables and pipelines, mapping undersea terrain, the study of marine life, pollution and salinity monitoring and detection of seismic activities. Underwater sensing technologies are also essential to maritime surveillance, detection and tracking of submarines and other underwater objects. Using natural language processing and machine learning, we mined scientific publications to gain insight into underwater sensing research evolution during the 21st century, in terms of technology development and applications. This study offers a comprehensive analysis of the underwater sensing research landscape as well as the temporal evolution of its main research topics. We identified 18 key research topics that offer comprehensive and logical coverage of the research field. Nearly half of them are on a decreasing trend, despite an overall increase in the number of scientific publications. These findings and the extracted patterns can provide researchers and decision-makers with new insights into the field, its characteristics and its development. Our proposed algorithmic approach can also be applied to other areas for technologies of a disruptive nature.
Date de publication	2024-08-19
Maison d’édition	EManuscript Technologies Phcog.Net
Licence	Creative Commons Attribution - Pas d'utilisation commerciale 4.0 International (CC BY-NC 4.0) https://creativecommons.org/licenses/by-nc/4.0/deed.fr
Dans	Journal of Scientometric Research 13, nº 2 (19 août 2024) : 562–574.
Langue	anglais
Publications évaluées par des pairs	Oui
Exporter la notice	Exporter en format RIS
Signaler une correction	Signaler une correction (s'ouvre dans un nouvel onglet)
Identificateur de l’enregistrement	ca53a183-cd99-45be-a5f2-2f63cc963752
Enregistrement créé	2024-08-27
Enregistrement modifié	2024-08-27

Date de modification :: 2024-12-01