Data Fusion in Internet of Things

Detalhes bibliográficos
Autor(a) principal: Mendes, Tiago Nobre de Albuquerque
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.6/10222
Resumo: This dissertation reviews Internet of Things concepts and implementations, state-of-the-art technology with practical examples, as well as data fusion methods applied in different problems. The purpose of this study is to review different data fusion methods and develop a system to provide recognition of human activity that can be applied in day care homes and in hospitals to monitor patients. The system’s objective is to study human activity recognition based on the data recovered by sensors like accelerometers and gyroscopes. In order to transform this data to useful information and practical results to monitoring patients with accuracy and high performance, two different neural networks were implemented. To conclude, the results from the two different neural networks are compared to each other and compared with systems from other authors. It is hoped this study will inform other authors and developers about the performance of neural networks when managing human activity recognition systems.
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spelling Data Fusion in Internet of ThingsData FusionDeep LearningHealth-CareHuman Activity RecognitionInternet of ThingsNeural NetworksSmart HomeDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaThis dissertation reviews Internet of Things concepts and implementations, state-of-the-art technology with practical examples, as well as data fusion methods applied in different problems. The purpose of this study is to review different data fusion methods and develop a system to provide recognition of human activity that can be applied in day care homes and in hospitals to monitor patients. The system’s objective is to study human activity recognition based on the data recovered by sensors like accelerometers and gyroscopes. In order to transform this data to useful information and practical results to monitoring patients with accuracy and high performance, two different neural networks were implemented. To conclude, the results from the two different neural networks are compared to each other and compared with systems from other authors. It is hoped this study will inform other authors and developers about the performance of neural networks when managing human activity recognition systems.Pombo, Nuno Gonçalo Coelho CostaSantos, Nuno Manuel Garcia dosMerilampi, SariuBibliorumMendes, Tiago Nobre de Albuquerque2020-03-25T14:33:35Z2019-07-302019-06-242019-07-30T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.6/10222TID:202365255enginfo: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:RCAAP2023-12-15T09:51:40Zoai:ubibliorum.ubi.pt:10400.6/10222Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:50:14.271797Repositório 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 Data Fusion in Internet of Things
title Data Fusion in Internet of Things
spellingShingle Data Fusion in Internet of Things
Mendes, Tiago Nobre de Albuquerque
Data Fusion
Deep Learning
Health-Care
Human Activity Recognition
Internet of Things
Neural Networks
Smart Home
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
title_short Data Fusion in Internet of Things
title_full Data Fusion in Internet of Things
title_fullStr Data Fusion in Internet of Things
title_full_unstemmed Data Fusion in Internet of Things
title_sort Data Fusion in Internet of Things
author Mendes, Tiago Nobre de Albuquerque
author_facet Mendes, Tiago Nobre de Albuquerque
author_role author
dc.contributor.none.fl_str_mv Pombo, Nuno Gonçalo Coelho Costa
Santos, Nuno Manuel Garcia dos
Merilampi, Sari
uBibliorum
dc.contributor.author.fl_str_mv Mendes, Tiago Nobre de Albuquerque
dc.subject.por.fl_str_mv Data Fusion
Deep Learning
Health-Care
Human Activity Recognition
Internet of Things
Neural Networks
Smart Home
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
topic Data Fusion
Deep Learning
Health-Care
Human Activity Recognition
Internet of Things
Neural Networks
Smart Home
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
description This dissertation reviews Internet of Things concepts and implementations, state-of-the-art technology with practical examples, as well as data fusion methods applied in different problems. The purpose of this study is to review different data fusion methods and develop a system to provide recognition of human activity that can be applied in day care homes and in hospitals to monitor patients. The system’s objective is to study human activity recognition based on the data recovered by sensors like accelerometers and gyroscopes. In order to transform this data to useful information and practical results to monitoring patients with accuracy and high performance, two different neural networks were implemented. To conclude, the results from the two different neural networks are compared to each other and compared with systems from other authors. It is hoped this study will inform other authors and developers about the performance of neural networks when managing human activity recognition systems.
publishDate 2019
dc.date.none.fl_str_mv 2019-07-30
2019-06-24
2019-07-30T00:00:00Z
2020-03-25T14:33:35Z
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format masterThesis
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.6/10222
TID:202365255
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identifier_str_mv TID:202365255
dc.language.iso.fl_str_mv eng
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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