Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory

Detalhes bibliográficos
Autor(a) principal: Silva, Katia Cilene Neles
Data de Publicação: 2017
Outros Autores: Bressan, Graça
Tipo de documento: Artigo
Idioma: eng
Título da fonte: INFOCOMP: Jornal de Ciência da Computação
Texto Completo: https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/554
Resumo: This paper describes the authors’ observations about the uncertainties associated with monitoring based on sensors, through the Dempster-Shafer Evidence Theory.  It presents the results of an experiment which is part of an ongoing research about dealing with uncertain contextual information in the human health monitoring system based on sensors. The experiment employs evidence theory on reasoning over context. Recommendations to improve the systems to monitor the human health within a framework that addresses uncertainty are also provided.
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spelling Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence TheoryThis paper describes the authors’ observations about the uncertainties associated with monitoring based on sensors, through the Dempster-Shafer Evidence Theory.  It presents the results of an experiment which is part of an ongoing research about dealing with uncertain contextual information in the human health monitoring system based on sensors. The experiment employs evidence theory on reasoning over context. Recommendations to improve the systems to monitor the human health within a framework that addresses uncertainty are also provided.Editora da UFLA2017-12-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/554INFOCOMP Journal of Computer Science; Vol. 16 No. 1-2 (2017): June-December 2017; 46-541982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/554/496Silva, Katia Cilene NelesBressan, Graçainfo:eu-repo/semantics/openAccess2017-12-05T03:02:55Zoai:infocomp.dcc.ufla.br:article/554Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:42.858740INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
title Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
spellingShingle Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
Silva, Katia Cilene Neles
title_short Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
title_full Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
title_fullStr Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
title_full_unstemmed Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
title_sort Human Health Monitoring by Sensors: Analysis of Contextual Uncertainties through Dempster-Shafer Evidence Theory
author Silva, Katia Cilene Neles
author_facet Silva, Katia Cilene Neles
Bressan, Graça
author_role author
author2 Bressan, Graça
author2_role author
dc.contributor.author.fl_str_mv Silva, Katia Cilene Neles
Bressan, Graça
description This paper describes the authors’ observations about the uncertainties associated with monitoring based on sensors, through the Dempster-Shafer Evidence Theory.  It presents the results of an experiment which is part of an ongoing research about dealing with uncertain contextual information in the human health monitoring system based on sensors. The experiment employs evidence theory on reasoning over context. Recommendations to improve the systems to monitor the human health within a framework that addresses uncertainty are also provided.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/554
url https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/554
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/554/496
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.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv INFOCOMP Journal of Computer Science; Vol. 16 No. 1-2 (2017): June-December 2017; 46-54
1982-3363
1807-4545
reponame:INFOCOMP: Jornal de Ciência da Computação
instname:Universidade Federal de Lavras (UFLA)
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instname_str Universidade Federal de Lavras (UFLA)
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institution UFLA
reponame_str INFOCOMP: Jornal de Ciência da Computação
collection INFOCOMP: Jornal de Ciência da Computação
repository.name.fl_str_mv INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv infocomp@dcc.ufla.br||apfreire@dcc.ufla.br
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