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Cited 11 time in webofscience Cited 24 time in scopus
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Enabling Ambient Intelligence of Things (AIoT) healthcare system architectures

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dc.contributor.authorPise, Anil-
dc.contributor.authorYoon, Byungun-
dc.contributor.authorSingh, Saurabh-
dc.date.accessioned2024-08-08T09:31:53Z-
dc.date.available2024-08-08T09:31:53Z-
dc.date.issued2023-01-
dc.identifier.issn0140-3664-
dc.identifier.issn1873-703X-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/20949-
dc.description.abstractDuring the last decade, significant research has been conducted in the fields of healthcare and the administration of cutting-edge ambient intelligence (AmI) technology. Healthcare experts explored smart gadgets and other medical technologies, as well as ambient intelligence using Internet of Things (IoT) (AIoT). The potential for linking the two regions and improving care for individuals living in rural and distant areas is apparent. The healthcare industry has seen tremendous advances in efficiency, affordability, and usefulness as a result of new growth possibilities and drastic cost reductions. This includes a how-to guide on how medical advancements may be both helpful and detrimental as a result of (AIoT-based) technology. The AIoTH application is anticipated to be covered in the last section since it has the ability to assist with current and varied technologies, and relevant approaches for solving healthcare problems are examined. Furthermore, many potential problems and inconsistencies with the AIoT-H method are often identified. Current and future academics interested in the subject will be able to examine a wide range of possible AIoT-H implementations in order to get a better understanding of the effect and influence on any of the many AIoT applications.-
dc.format.extent9-
dc.language영어-
dc.language.isoENG-
dc.publisherELSEVIER-
dc.titleEnabling Ambient Intelligence of Things (AIoT) healthcare system architectures-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.comcom.2022.10.029-
dc.identifier.scopusid2-s2.0-85143759849-
dc.identifier.wosid001026631600001-
dc.identifier.bibliographicCitationComputer Communications, v.198, pp 186 - 194-
dc.citation.titleComputer Communications-
dc.citation.volume198-
dc.citation.startPage186-
dc.citation.endPage194-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.subject.keywordPlusINTERNET-
dc.subject.keywordPlusIOT-
dc.subject.keywordPlusTECHNOLOGIES-
dc.subject.keywordPlusCHALLENGES-
dc.subject.keywordPlusFRAMEWORK-
dc.subject.keywordPlusSCHEME-
dc.subject.keywordAuthorArtificial intelligence-
dc.subject.keywordAuthorAmbient intelligence-
dc.subject.keywordAuthorHealthcare analytics-
dc.subject.keywordAuthorPredictive analytics-
dc.subject.keywordAuthorHealthcare informatics-
dc.subject.keywordAuthorDisease detection-
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