Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing

Detalhes bibliográficos
Autor(a) principal: Santos, Ricardo
Data de Publicação: 2019
Outros Autores: Barandas, Marília, Leonardo, Ricardo, Gamboa, Hugo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: https://doi.org/10.3390/s19040919
Resumo: This research was supported by North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026.
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spelling Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcingcrowdsourcingfingerprintingfloor plan constructionindoor localisationindoor mappingpedestrian dead reckoningtime series similaritiesunsupervised machine learningCrowdsourcingTime series similaritiesIndoor localisationPedestrian dead reckoningUnsupervised machine learningFingerprintingFloor plan constructionIndoor mappingAnalytical ChemistryInstrumentationAtomic and Molecular Physics, and OpticsElectrical and Electronic EngineeringBiochemistryThis research was supported by North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026.The demand for easily deployable indoor localisation solutions has been growing. Although several systems have been proposed, their limitations regarding the high implementation costs hinder most of them to be widely used. Fingerprinting-based IPS (Indoor Positioning Systems) depend on characteristics pervasively available in buildings. However, such systems require indoor floor plans, which might not be available, as well as environmental fingerprints, that need to be collected through human resources intensive processes. To overcome these limitations, this paper proposes an algorithm for the automatic construction of indoor maps and fingerprints, solely depending on non-annotated crowdsourced data from smartphones. Our system relies on multiple gait-model based filtering techniques for accurate movement quantification in combination with opportunistic sensing observations. After the reconstruction of users' movement with PDR (Pedestrian Dead Reckoning) techniques, Wi-Fi measurements are clustered to partition the trajectories into segments. Similar segments, which belong to the same cluster, are identified using an adaptive approach based on a geomagnetic field distance. Finally, the floor plans are obtained through a data fusion process. Merging the acquired environmental data using the obtained floor plan, fingerprints are aligned to physical locations. Experimental results show that the proposed solution achieved comparable floor plans and fingerprints to those acquired manually, allowing the conclusion that is possible to automate the setup process of infrastructure-free IPS.DF – Departamento de FísicaLIBPhys-UNLRUNSantos, RicardoBarandas, MaríliaLeonardo, RicardoGamboa, Hugo2019-09-04T22:40:48Z2019-02-022019-02-02T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.3390/s19040919eng1424-8220PURE: 12925555http://www.scopus.com/inward/record.url?scp=85062432992&partnerID=8YFLogxKhttps://doi.org/10.3390/s19040919info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:40:44Zoai:run.unl.pt:10362/80180Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:12:02.192154Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
title Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
spellingShingle Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
Santos, Ricardo
crowdsourcing
fingerprinting
floor plan construction
indoor localisation
indoor mapping
pedestrian dead reckoning
time series similarities
unsupervised machine learning
Crowdsourcing
Time series similarities
Indoor localisation
Pedestrian dead reckoning
Unsupervised machine learning
Fingerprinting
Floor plan construction
Indoor mapping
Analytical Chemistry
Instrumentation
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Biochemistry
title_short Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
title_full Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
title_fullStr Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
title_full_unstemmed Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
title_sort Fingerprints and Floor Plans Construction for Indoor Localisation Based on Crowdsourcing
author Santos, Ricardo
author_facet Santos, Ricardo
Barandas, Marília
Leonardo, Ricardo
Gamboa, Hugo
author_role author
author2 Barandas, Marília
Leonardo, Ricardo
Gamboa, Hugo
author2_role author
author
author
dc.contributor.none.fl_str_mv DF – Departamento de Física
LIBPhys-UNL
RUN
dc.contributor.author.fl_str_mv Santos, Ricardo
Barandas, Marília
Leonardo, Ricardo
Gamboa, Hugo
dc.subject.por.fl_str_mv crowdsourcing
fingerprinting
floor plan construction
indoor localisation
indoor mapping
pedestrian dead reckoning
time series similarities
unsupervised machine learning
Crowdsourcing
Time series similarities
Indoor localisation
Pedestrian dead reckoning
Unsupervised machine learning
Fingerprinting
Floor plan construction
Indoor mapping
Analytical Chemistry
Instrumentation
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Biochemistry
topic crowdsourcing
fingerprinting
floor plan construction
indoor localisation
indoor mapping
pedestrian dead reckoning
time series similarities
unsupervised machine learning
Crowdsourcing
Time series similarities
Indoor localisation
Pedestrian dead reckoning
Unsupervised machine learning
Fingerprinting
Floor plan construction
Indoor mapping
Analytical Chemistry
Instrumentation
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Biochemistry
description This research was supported by North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-04T22:40:48Z
2019-02-02
2019-02-02T00:00:00Z
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://doi.org/10.3390/s19040919
url https://doi.org/10.3390/s19040919
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1424-8220
PURE: 12925555
http://www.scopus.com/inward/record.url?scp=85062432992&partnerID=8YFLogxK
https://doi.org/10.3390/s19040919
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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