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Cited 7 time in webofscience Cited 7 time in scopus
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IoT-Aided Fingerprint Indoor Positioning Using Support Vector Classification

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dc.contributor.authorWei, Yiqiao-
dc.contributor.authorHwang, Seung-Hoon-
dc.contributor.authorLee, Sang-Moon-
dc.date.accessioned2023-04-28T10:41:20Z-
dc.date.available2023-04-28T10:41:20Z-
dc.date.issued2018-11-16-
dc.identifier.issn2162-1233-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/10008-
dc.description.abstractWi-Fi based fingerprint indoor positioning technology is known as one of the most popular indoor positioning technologies. In this work, an internet of things (IoT) aided fingerprint indoor positioning system using support vector machine classifier has been proposed. The support vector classification with kernel tricks is introduced to accomplish multi-classes classification problem in fingerprint indoor positioning. Three kinds of kernel functions are investigated and compared based on results of the experiment performed in a real indoor environment. The results show support vector classifier with Gaussian RBF kernel function has highest positioning accuracy.-
dc.format.extent3-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE-
dc.titleIoT-Aided Fingerprint Indoor Positioning Using Support Vector Classification-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1109/ICTC.2018.8539594-
dc.identifier.scopusid2-s2.0-85059463994-
dc.identifier.wosid000517984800213-
dc.identifier.bibliographicCitation2018 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC), pp 973 - 975-
dc.citation.title2018 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC)-
dc.citation.startPage973-
dc.citation.endPage975-
dc.type.docTypeProceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordAuthorIndoor positioning-
dc.subject.keywordAuthorReceived Signal Strength-
dc.subject.keywordAuthorFingerprint-
dc.subject.keywordAuthorSupport vector machine-
dc.subject.keywordAuthorIoT-
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