L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/86713 |
Resumo: | The demand for indoor location-based services and the wide availability of mobile devices have triggered research into new positioning systems able to provide accurate indoor positions using smartphones. However, accurate solutions require a complex implementation and long-term maintenance of their infrastructure. Collaborative systems may help to alleviate these drawbacks. In this paper, we propose a smartphone-based collaborative architecture using neural networks and received signal strength, which exploits the built-in wireless communication technologies in smartphones and the collaboration between devices to improve traditional positioning systems without additional deployment. Experiments are carried out in two real-world scenarios, demonstrating that our proposed architecture enhances the position accuracy of traditional indoor positioning systems. |
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L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprintingCalibrationCollaborationCollaborative Indoor PositioningComputer architectureFingerprint recognitionFingerprintingLaterationNeural NetworksReceived Signal StrengthSensorsSmart phonesWireless fidelityEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaThe demand for indoor location-based services and the wide availability of mobile devices have triggered research into new positioning systems able to provide accurate indoor positions using smartphones. However, accurate solutions require a complex implementation and long-term maintenance of their infrastructure. Collaborative systems may help to alleviate these drawbacks. In this paper, we propose a smartphone-based collaborative architecture using neural networks and received signal strength, which exploits the built-in wireless communication technologies in smartphones and the collaboration between devices to improve traditional positioning systems without additional deployment. Experiments are carried out in two real-world scenarios, demonstrating that our proposed architecture enhances the position accuracy of traditional indoor positioning systems.The authors gratefully acknowledge funding from European Union’s Horizon 2020 RIA programme under the Marie Skłodowska Curie grant agreement No. 813278 (A-WEAR: A network for dynamic wearable applications with privacy constraints) and No. 101023072 (ORIENTATE: Low-cost Reliable Indoor Positioning in Smart Factories). The associate editor coordinating the review of this article and approving it for publication was Prof. Name Surname (Corresponding authors: J. Torres-Sospedra and S. Casteleyn).IEEEUniversidade do MinhoPascacio, PavelTorres-Sospedra, JoaquínCasteleyn, SvenLohan, Elena SimonaNurmi, Jari20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/86713engPascacio, P., Torres-Sospedra, J., Casteleyn, S., Lohan, E. S., & Nurmi, J. (2023). L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting. IEEE Sensors Journal. Institute of Electrical and Electronics Engineers (IEEE). http://doi.org/10.1109/jsen.2023.33081471530-437X10.1109/JSEN.2023.3308147https://ieeexplore.ieee.org/document/10234220/info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-02T01:20:48Zoai:repositorium.sdum.uminho.pt:1822/86713Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:35:32.160465Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting |
title |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting |
spellingShingle |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting Pascacio, Pavel Calibration Collaboration Collaborative Indoor Positioning Computer architecture Fingerprint recognition Fingerprinting Lateration Neural Networks Received Signal Strength Sensors Smart phones Wireless fidelity Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
title_short |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting |
title_full |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting |
title_fullStr |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting |
title_full_unstemmed |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting |
title_sort |
L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting |
author |
Pascacio, Pavel |
author_facet |
Pascacio, Pavel Torres-Sospedra, Joaquín Casteleyn, Sven Lohan, Elena Simona Nurmi, Jari |
author_role |
author |
author2 |
Torres-Sospedra, Joaquín Casteleyn, Sven Lohan, Elena Simona Nurmi, Jari |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Pascacio, Pavel Torres-Sospedra, Joaquín Casteleyn, Sven Lohan, Elena Simona Nurmi, Jari |
dc.subject.por.fl_str_mv |
Calibration Collaboration Collaborative Indoor Positioning Computer architecture Fingerprint recognition Fingerprinting Lateration Neural Networks Received Signal Strength Sensors Smart phones Wireless fidelity Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
topic |
Calibration Collaboration Collaborative Indoor Positioning Computer architecture Fingerprint recognition Fingerprinting Lateration Neural Networks Received Signal Strength Sensors Smart phones Wireless fidelity Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
description |
The demand for indoor location-based services and the wide availability of mobile devices have triggered research into new positioning systems able to provide accurate indoor positions using smartphones. However, accurate solutions require a complex implementation and long-term maintenance of their infrastructure. Collaborative systems may help to alleviate these drawbacks. In this paper, we propose a smartphone-based collaborative architecture using neural networks and received signal strength, which exploits the built-in wireless communication technologies in smartphones and the collaboration between devices to improve traditional positioning systems without additional deployment. Experiments are carried out in two real-world scenarios, demonstrating that our proposed architecture enhances the position accuracy of traditional indoor positioning systems. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023 2023-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/86713 |
url |
https://hdl.handle.net/1822/86713 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Pascacio, P., Torres-Sospedra, J., Casteleyn, S., Lohan, E. S., & Nurmi, J. (2023). L/F-CIPS: Collaborative indoor positioning for smartphones with lateration and fingerprinting. IEEE Sensors Journal. Institute of Electrical and Electronics Engineers (IEEE). http://doi.org/10.1109/jsen.2023.3308147 1530-437X 10.1109/JSEN.2023.3308147 https://ieeexplore.ieee.org/document/10234220/ |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
IEEE |
publisher.none.fl_str_mv |
IEEE |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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