Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105538
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dc.contributorDepartment of Computing-
dc.creatorHo, YHen_US
dc.creatorChan, HCBen_US
dc.date.accessioned2024-04-15T07:34:55Z-
dc.date.available2024-04-15T07:34:55Z-
dc.identifier.issn0140-3664en_US
dc.identifier.urihttp://hdl.handle.net/10397/105538-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights©2020 Elsevier B. V. All rights reserved.en_US
dc.rights©2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Ho, Y. H., & Chan, H. C. (2020). Decentralized adaptive indoor positioning protocol using Bluetooth Low Energy. Computer Communications, 159, 231-244. is available at https://doi.org/10.1016/j.comcom.2020.04.041.en_US
dc.subjectBluetooth Low Energyen_US
dc.subjectIndoor positioningen_US
dc.titleDecentralized adaptive indoor positioning protocol using Bluetooth Low Energyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage231en_US
dc.identifier.epage244en_US
dc.identifier.volume159en_US
dc.identifier.doi10.1016/j.comcom.2020.04.041en_US
dcterms.abstractPrevious indoor positioning research has mainly been focused on using Wi-Fi and RFID. In recent years, researchers began to study using Bluetooth 4.0 and Bluetooth Low Energy (BLE) for indoor positioning purposes. In general, positioning techniques based on received signal strength indicator (RSSI), such as signal propagation and fingerprint, are commonly used in wireless/mobile networks. These techniques have certain limitations and tradeoff in terms of accuracy, ease of implementation and practical application/deployment. For example, both methods require a training process before deployment. In this paper, we present a decentralized BLE-based positioning protocol that does not require training before deployment. The training process can automatically be done on the fly by the anchor nodes. While the anchor nodes are broadcasting, they also scan for signals emitted by other anchors. This collaborative communication process exchanges location information and signal strength measurements between each anchor. This process builds a signal-to-distance reference list for the target node to estimate physical distance in a more accurate way. Experimentation in a real indoor environment shows that the proposed collaborative positioning method can achieve an error of 1.5 meters on average. This is generally applicable for most indoor positioning applications for locating people. Furthermore, its implementation is simple and practical, because it does not require training before positioning estimation and is adaptive to environmental changes.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationComputer communications, 1 June 2020, v. 159, p. 231-244en_US
dcterms.isPartOfComputer communicationsen_US
dcterms.issued2020-06-01-
dc.identifier.scopus2-s2.0-85085218373-
dc.identifier.eissn1873-703Xen_US
dc.description.validate202402 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCOMP-0322-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextPolyUen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS25648622-
dc.description.oaCategoryGreen (AAM)en_US
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