Evaluating Wi-Fi indoor positioning approaches in a real world environment
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/19782 |
Resumo: | Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics |
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Evaluating Wi-Fi indoor positioning approaches in a real world environmentWi-FiWorldIndoor positioning systemRSSIFingerprintRetail analyticsPredictive modelingData scienceInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsGlobal positioning system(GPS) does not provide generally a good positioning performance in an indoor location because of many reasons (Henniges, 2012). On the other hand, other alternatives such as the WI-FI technology has become recently in a popular use to provide indoor localization. And that is due to many reasons, such as the wide spread of WI-FI infrastructure in the indoor environments and the low cost of this technology. This study attempts to evaluate different WI-FI indoor positioning approaches in a real world environment. In particular, in retail stores and shopping malls. The pros and cons of each one of these approaches are pointed out. The main purpose of this study from the company perspective is to explore the state of the art methods and the cutting edge technologies of the WI-FI IPS and to come up with an improvement of their indoor localization system. This system forms the core of the company`s retail-analytics product that uses a Wi-Fi positioning technology to provide indoor location based services for the customers and helps retailers to better understanding their businesses.Vanneschi, LeonardoBrosig, FabianMüller, AlexanderRUNHantoush, Raafat2017-01-16T10:31:47Z2016-01-132016-01-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/19782TID:201357992enginfo: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:RCAAP2024-03-11T04:01:56Zoai:run.unl.pt:10362/19782Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:25:41.647755Repositório 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 |
Evaluating Wi-Fi indoor positioning approaches in a real world environment |
title |
Evaluating Wi-Fi indoor positioning approaches in a real world environment |
spellingShingle |
Evaluating Wi-Fi indoor positioning approaches in a real world environment Hantoush, Raafat Wi-Fi World Indoor positioning system RSSI Fingerprint Retail analytics Predictive modeling Data science |
title_short |
Evaluating Wi-Fi indoor positioning approaches in a real world environment |
title_full |
Evaluating Wi-Fi indoor positioning approaches in a real world environment |
title_fullStr |
Evaluating Wi-Fi indoor positioning approaches in a real world environment |
title_full_unstemmed |
Evaluating Wi-Fi indoor positioning approaches in a real world environment |
title_sort |
Evaluating Wi-Fi indoor positioning approaches in a real world environment |
author |
Hantoush, Raafat |
author_facet |
Hantoush, Raafat |
author_role |
author |
dc.contributor.none.fl_str_mv |
Vanneschi, Leonardo Brosig, Fabian Müller, Alexander RUN |
dc.contributor.author.fl_str_mv |
Hantoush, Raafat |
dc.subject.por.fl_str_mv |
Wi-Fi World Indoor positioning system RSSI Fingerprint Retail analytics Predictive modeling Data science |
topic |
Wi-Fi World Indoor positioning system RSSI Fingerprint Retail analytics Predictive modeling Data science |
description |
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-13 2016-01-13T00:00:00Z 2017-01-16T10:31:47Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/19782 TID:201357992 |
url |
http://hdl.handle.net/10362/19782 |
identifier_str_mv |
TID:201357992 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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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) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137888039862273 |