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Comparative Study of Supervised Learning and Metaheuristic Algorithms for the Development of Bluetooth-Based Indoor Localization Mechanisms

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dc.contributor.authorLovón Melgarejo, Jesús
dc.contributor.authorHuarcaya Canal, Oscar
dc.contributor.authorOrozco Barbosa, Luis
dc.contributor.authorGarcía Varea, Ismael
dc.contributor.authorCastillo Cara, José Manuel
dc.date.accessioned2024-05-20T11:42:26Z
dc.date.available2024-05-20T11:42:26Z
dc.date.issued2019-02-15
dc.description.abstractThe development of the Internet of Things (IoT) benefits from 1) the connections between devices equipped with multiple sensors; 2) wireless networks and; 3) processing and analysis of the gathered data. The growing interest in the use of IoT technologies has led to the development of numerous diverse applications, many of which are based on the knowledge of the end user's location and profile. This paper investigates the characterization of Bluetooth signals behavior using 12 different supervised learning algorithms as a first step toward the development of fingerprint-based localization mechanisms. We then explore the use of metaheuristics to determine the best radio power transmission setting evaluated in terms of accuracy and mean error of the localization mechanism. We further tune-up the supervised algorithm hyperparameters. A comparative evaluation of the 12 supervised learning and two metaheuristics algorithms under two different system parameter settings provide valuable insights into the use and capabilities of the various algorithms on the development of indoor localization mechanisms.en
dc.description.versionversión publicada
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2019.2899736
dc.identifier.issn2169-3536
dc.identifier.urihttps://hdl.handle.net/20.500.14468/12446
dc.journal.titleIEEE Access
dc.journal.volume7
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentInteligencia Artificial
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subject.keywordsIndoor positioning
dc.subject.keywordsfingerprinting
dc.subject.keywordsBluetooth
dc.subject.keywordsclassification model
dc.subject.keywordssignal processing
dc.subject.keywordsreceived signal strength indication
dc.subject.keywordsmultipath fading
dc.subject.keywordstransmission power
dc.subject.keywordsbenchmark
dc.subject.keywordsmetaheuristic optimization algorithms
dc.titleComparative Study of Supervised Learning and Metaheuristic Algorithms for the Development of Bluetooth-Based Indoor Localization Mechanismses
dc.typejournal articleen
dc.typeartículoes
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoveryc0e39bd2-c0d8-4743-953d-488baf6b977e
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