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Improving bluetooth beacon-based indoor location and fingerprinting

dc.contributor.authorMartins, Pedro
dc.contributor.authorAbbasi, Maryam
dc.contributor.authorSá, Filipe
dc.contributor.authorCecílio, José
dc.contributor.authorMorgado, Francisco
dc.contributor.authorCaldeira, Filipe
dc.date.accessioned2023-07-04T12:51:05Z
dc.date.available2023-07-04T12:51:05Z
dc.date.issued2019-12-10
dc.date.updated2023-06-14T15:29:10Z
dc.description.abstractThe complex way radio waves propagate indoors, leads to the derivation of location using fngerprinting techniques. In this cases, location is computed relying on WiFi signals strength mapping. Recent Bluetooth low energy (BLE) provides new opportunities to explore positioning. In this work is studied how BLE beacons radio signals can be used for indoor location scenarios, as well as their precision. Additionally, this paper also introduces a method for beacon-based positioning, based on signal strength measurements at key distances for each beacon. This method allows to use diferent beacon types, brands, and location conditions/constraints. Depending on each situation (i.e., hardware and location) it is possible to adapt the distance measuring curve to minimize errors and support higher distances, while at the same time keeping good precision. Moreover, this paper also presents a comparison with traditional positioning method, using formulas for distance estimation, and the position triangulation. The proposed study is performed inside the campus of Viseu Polytechnic Institute, and tested using a group of students, each with his smart-phone, as proof of concept. Experimental results show that BLE allows having < 1.5 m error approximately 90% of the times, and the experimental results using the proposed location detection method show that the proposed position technique has 13.2% better precision than triangulation, for distances up to 10 m.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/s12652-019-01626-2pt_PT
dc.identifier.eid2-s2.0-85076607532
dc.identifier.issn1868-5137
dc.identifier.issn1868-5145
dc.identifier.slugcv-prod-878100
dc.identifier.urihttp://hdl.handle.net/10400.19/7862
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationCENTRO-01-0145-FEDER-023797pt_PT
dc.subjectBeaconpt_PT
dc.subjectWirelesspt_PT
dc.subjectGPSpt_PT
dc.subjectIndoor locationpt_PT
dc.subjectBlock-chainpt_PT
dc.subjectCrowd learningpt_PT
dc.subjectBluetoothpt_PT
dc.subjectBLEpt_PT
dc.subjectWiFipt_PT
dc.titleImproving bluetooth beacon-based indoor location and fingerprintingpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage3919pt_PT
oaire.citation.issue10pt_PT
oaire.citation.startPage3907pt_PT
oaire.citation.titleJournal of Ambient Intelligence and Humanized Computingpt_PT
oaire.citation.volume11pt_PT
person.familyName
person.familyNameCaldeira
person.givenNameFilipe
person.givenNameFilipe
person.identifierR-00H-E4X
person.identifierlXPmBvYAAAAJ
person.identifier.ciencia-id791E-0243-634F
person.identifier.ciencia-idCB11-8109-AB1D
person.identifier.orcid0000-0002-7846-8397
person.identifier.orcid0000-0001-7558-2330
person.identifier.scopus-author-id8447524700
person.identifier.scopus-author-id36023210300
rcaap.cv.cienciaidCB11-8109-AB1D | Filipe Caldeira
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication9fb8350d-65a7-4170-b28f-cc60c70c0bb2
relation.isAuthorOfPublicatione845705e-5b0b-4f70-9c53-c472ffd768d1
relation.isAuthorOfPublication.latestForDiscoverye845705e-5b0b-4f70-9c53-c472ffd768d1

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