Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/7121
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dc.contributor.authorChieh, K.S.en_US
dc.contributor.authorKeong, N.Y.en_US
dc.contributor.authorBurhan, M.F.en_US
dc.contributor.authorBalasubramaniam, N.en_US
dc.contributor.authorDin, N.M.en_US
dc.date.accessioned2018-01-11T09:10:41Z-
dc.date.available2018-01-11T09:10:41Z-
dc.date.issued2015-
dc.description.abstractIndoor localization system has become popular and widely deployed in ftracking the position and movement of objects and humans within an enclosed structure. This work proposes development of indoor localization system using ZigBee. K-Nearest Neighbor algorithm is adapted to predict the location of a user in an indoor environment. The accuracy of the indoor location sensing is investigated. Emphasis is placed on RSS sample vector fluctuation correction to further increase the prediction accuracy. © 2014 IEEE.
dc.language.isoenen_US
dc.titleZigBee environment for indoor localizationen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/ICE2T.2014.7006237-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.openairetypeConference Paper-
Appears in Collections:COGS Scholarly Publication
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