Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113959
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dc.contributorFaculty of Business-
dc.creatorChen, M-
dc.creatorQi, C-
dc.creatorWu, X-
dc.date.accessioned2025-07-04T08:34:18Z-
dc.date.available2025-07-04T08:34:18Z-
dc.identifier.isbn979-8-3503-5409-6-
dc.identifier.urihttp://hdl.handle.net/10397/113959-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication M. Chen, C. Qi and X. Wu, "Applications of Artificial Intelligence in Oceanic Nuclear Contamination Management," 2024 IEEE Conference on Artificial Intelligence (CAI), Singapore, Singapore, 2024, pp. 210-215 is available at https://doi.org/10.1109/CAI59869.2024.00046.en_US
dc.subjectArtificial Intelligenceen_US
dc.subjectOceanic Nuclear Contaminationen_US
dc.titleApplications of artificial intelligence in oceanic nuclear contamination managementen_US
dc.typeConference Paperen_US
dc.identifier.spage210-
dc.identifier.epage215-
dc.identifier.doi10.1109/CAI59869.2024.00046-
dcterms.abstractRecently, nuclear pollution in the ocean has become a hot debate. The unprecedented advancement of Artificial Intelligence (AI) has engendered practical applications for addressing environmental issues such as nuclear contamination in oceans. AI algorithms and applications have been widely studied in multiple scientific fields, however, the research on marine science, especially oceanic nuclear contamination is limited. To fill in the gap in the related field, this paper introduces four major categories of AI technologies in oceanic nuclear contamination management, explores their applications in six companies/institutions across three leading countries, and compares the similarity and differences among them. It is found that UK, Japan, and China mainly use robots or drones for nuclear contamination management, and rely heavily on state fundings and the scientific output from research institutions. On the other hand, different countries have various objectives and motivations to drive AI in this area. What is more, we found that although most traditional big IT companies have not clearly stated the usage of AI in marine pollution, the need to diminish the impacts of nuclear pollution in oceans will inevitably urge new applications of AI in oceanic nuclear contamination.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings : 2024 IEEE Conference on Artificial Intelligence CAI 2024 : 25-27 June 2024, Marina Bay Sands, Singapore, p. 210-215-
dcterms.issued2024-
dc.identifier.scopus2-s2.0-85201186248-
dc.relation.conferenceIEEE Conference on Artificial Intelligence [CAI]-
dc.description.validate202506 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera3807aen_US
dc.identifier.SubFormID51163en_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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