Publicação
Improving bluetooth beacon-based indoor location and fingerprinting
| Resumo: | The 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. |
|---|---|
| Autores principais: | Martins, Pedro |
| Outros Autores: | Abbasi, Maryam; Sá, Filipe; Cecílio, José; Morgado, Francisco; Caldeira, Filipe |
| Assunto: | Beacon Wireless GPS Indoor location Block-chain Crowd learning Bluetooth BLE WiFi |
| Ano: | 2019 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Viseu |
| Idioma: | inglês |
| Origem: | Repositório Científico do Instituto Politécnico de Viseu |
| _version_ | 1863854343577403392 |
|---|---|
| author | Martins, Pedro |
| author2 | Abbasi, Maryam Sá, Filipe Cecílio, José Morgado, Francisco Caldeira, Filipe |
| author2_role | author author author author author |
| author_facet | Martins, Pedro Abbasi, Maryam Sá, Filipe Cecílio, José Morgado, Francisco Caldeira, Filipe |
| author_role | author |
| contributor_name_str_mv | Instituto Politécnico de Viseu |
| country_str | PT |
| creators_json_str | [{\"Person.name\":\"Martins, Pedro\"},{\"Person.name\":\"Abbasi, Maryam\"},{\"Person.name\":\"Sá, Filipe\",\"Person.identifier.orcid\":\"0000-0002-7846-8397\"},{\"Person.name\":\"Cecílio, José\"},{\"Person.name\":\"Morgado, Francisco\"},{\"Person.name\":\"Caldeira, Filipe\",\"Person.identifier.orcid\":\"0000-0001-7558-2330\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Instituto Politécnico de Viseu |
| datacite.creators.creator.creatorName.fl_str_mv | Martins, Pedro Abbasi, Maryam Sá, Filipe Cecílio, José Morgado, Francisco Caldeira, Filipe |
| datacite.date.Accepted.fl_str_mv | 2019-12-10T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-07-04T12:51:05Z |
| datacite.date.embargoed.fl_str_mv | 2023-07-04T12:51:05Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Beacon Wireless GPS Indoor location Block-chain Crowd learning Bluetooth BLE WiFi |
| datacite.titles.title.fl_str_mv | Improving bluetooth beacon-based indoor location and fingerprinting |
| dc.contributor.none.fl_str_mv | Instituto Politécnico de Viseu |
| dc.creator.none.fl_str_mv | Martins, Pedro Abbasi, Maryam Sá, Filipe Cecílio, José Morgado, Francisco Caldeira, Filipe |
| dc.date.Accepted.fl_str_mv | 2019-12-10T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-07-04T12:51:05Z |
| dc.date.embargoed.fl_str_mv | 2023-07-04T12:51:05Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.19/7862 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Beacon Wireless GPS Indoor location Block-chain Crowd learning Bluetooth BLE WiFi |
| dc.title.fl_str_mv | Improving bluetooth beacon-based indoor location and fingerprinting |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | The 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. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://repositorio.ipv.pt/bitstreams/c0ca68d7-ef05-491e-a936-01e540fea68a/download |
| id | ripv_5f4e5d227d2aaf3f7089f2dc69fe2949 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.19/7862 |
| instacron_str | ripv |
| institution | Instituto Politécnico de Viseu |
| instname_str | Instituto Politécnico de Viseu |
| language | eng |
| network_acronym_str | ripv |
| network_name_str | Repositório Científico do Instituto Politécnico de Viseu |
| oai_identifier_str | oai:repositorio.ipv.pt:10400.19/7862 |
| organization_str_mv | urn:organizationAcronym:ripv |
| person_str_mv | Martins, Pedro Abbasi, Maryam Sá, Filipe Sá, Filipe https://www.ciencia-id.pt/791E-0243-634F 791E-0243-634F http://orcid.org/0000-0002-7846-8397 0000-0002-7846-8397 Cecílio, José Morgado, Francisco Caldeira, Filipe Caldeira, Filipe https://www.ciencia-id.pt/CB11-8109-AB1D CB11-8109-AB1D http://orcid.org/0000-0001-7558-2330 0000-0001-7558-2330 |
| publishDate | 2019 |
| reponame_str | Repositório Científico do Instituto Politécnico de Viseu |
| repository_id_str | urn:repositoryAcronym:ripv |
| service_str_mv | urn:repositoryAcronym:ripv |
| spelling | engpt_PTThe 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.application/pdfpt_PTImproving bluetooth beacon-based indoor location and fingerprintingMartins, PedroAbbasi, MaryamPersonalSá, FilipeDSpacehttp://dspace.org/items/9fb8350d-65a7-4170-b28f-cc60c70c0bb2DSpacehttp://dspace.org/items/9fb8350d-65a7-4170-b28f-cc60c70c0bb2SáFilipeCiência IDhttps://www.ciencia-id.pt791E-0243-634FORCIDhttp://orcid.org0000-0002-7846-8397Scopus Author IDhttps://www.scopus.com8447524700Cecílio, JoséMorgado, FranciscoPersonalCaldeira, FilipeDSpacehttp://dspace.org/items/e845705e-5b0b-4f70-9c53-c472ffd768d1DSpacehttp://dspace.org/items/e845705e-5b0b-4f70-9c53-c472ffd768d1CaldeiraFilipeCiência IDhttps://www.ciencia-id.ptCB11-8109-AB1DORCIDhttp://orcid.org0000-0001-7558-2330Scopus Author IDhttps://www.scopus.com36023210300HostingInstitutionOrganizationalInstituto Politécnico de Viseue-mailmailto:repositorio@sc.ipv.ptrepositorio@sc.ipv.ptISSNIsPartOf1868-5137ISSNIsPartOf1868-5145DOIIsPartOf10.1007/s12652-019-01626-22023-07-04T12:51:05Z2019-12-102023-06-14T15:29:10Z2019-12-10T00:00:00ZHandlehttp://hdl.handle.net/10400.19/7862http://purl.org/coar/access_right/c_abf2open accessBeaconWirelessGPSIndoor locationBlock-chainCrowd learningBluetoothBLEWiFi3115884 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ipv.pt/bitstreams/c0ca68d7-ef05-491e-a936-01e540fea68a/downloadJournal of Ambient Intelligence and Humanized Computing111039073919 |
| spellingShingle | Improving bluetooth beacon-based indoor location and fingerprinting Martins, Pedro Beacon Wireless GPS Indoor location Block-chain Crowd learning Bluetooth BLE WiFi |
| subject.fl_str_mv | Beacon Wireless GPS Indoor location Block-chain Crowd learning Bluetooth BLE WiFi |
| title | Improving bluetooth beacon-based indoor location and fingerprinting |
| title_full | Improving bluetooth beacon-based indoor location and fingerprinting |
| title_fullStr | Improving bluetooth beacon-based indoor location and fingerprinting |
| title_full_unstemmed | Improving bluetooth beacon-based indoor location and fingerprinting |
| title_short | Improving bluetooth beacon-based indoor location and fingerprinting |
| title_sort | Improving bluetooth beacon-based indoor location and fingerprinting |
| topic | Beacon Wireless GPS Indoor location Block-chain Crowd learning Bluetooth BLE WiFi |
| topic_facet | Beacon Wireless GPS Indoor location Block-chain Crowd learning Bluetooth BLE WiFi |
| url | http://hdl.handle.net/10400.19/7862 |
| visible | 1 |