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dc.contributor.authorPapakyriakopoulos, Dimitrios-
dc.contributor.authorBardaki, Cleopatra-
dc.contributor.authorStavrou, Vasilis-
dc.contributor.authorPramatari, Katerina-
dc.date.accessioned2024-04-19T09:50:00Z-
dc.date.available2024-04-19T09:50:00Z-
dc.date.issued2019-10-02-
dc.identifierscopus-85073656463-
dc.identifier.issn1424-8220-
dc.identifier.other85073656463-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2153-
dc.description.abstractThis paper has developed and deployed a Bluetooth Low Energy (BLE) beacon-based indoor positioning system in a two-floor retail store. The ultimate purpose of this study was to compare the different indoor positioning techniques towards achieving efficient position determination of moving customers in the retail store. The innovation of this research lies in its context (the retail store) and the fact that this is not a laboratory, controlled experiment. Retail stores are challenging environments with multiple sources of noise (e.g., shoppers’ moving) that impede indoor localization. To the best of the authors’ knowledge, this is the first work concerning indoor localization of consumers in a real retail store. This study proposes an ensemble filter with lower absolute mean and root mean squared errors than the random forest. Moreover, the localization error is approximately 2 m, while for the random forest, it is 2.5 m. In retail environments, even a 0.5 m deviation is significant because consumers may be positioned in front of different store shelves and, thus, different product categories. The more accurate the consumer localization, the more accurate and rich insights on the customers’ shopping behavior. Consequently, retailers can offer more effective customer location-based services (e.g., personalized offers) and, overall, better consumer localization can improve decision making in retailing.en_US
dc.language.isoenen_US
dc.relation.ispartofSensorsen_US
dc.subjectBLE Beaconsen_US
dc.subjectBluetooth low energyen_US
dc.subjectEnsemble filteren_US
dc.subjectFingerprintingen_US
dc.subjectIndoor positioningen_US
dc.subjectRetail storeen_US
dc.titleAn ensemble filter for indoor positioning in a retail store using bluetooth low energy beaconsen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/s19204550en_US
dc.identifier.scopus2-s2.0-85073656463-
dcterms.accessRights1en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume19en_US
dc.relation.issue20en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0001-7033-1890-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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