Publicação
A Methodology for Trustworthy IoT in Healthcare-Related Environments
| Resumo: | The transition to the so-called retirement years comes with the freedom to pursue old passions and hobbies that were not possible to do in the past busy life. Unfortunately, that freedom does not come alone, as the previous young years are gone, and the body starts to feel the time that passed. The necessity to adapt elder way of living grows as they become more prone to health problems. Often, the solution for the attention required by the elders is nursing homes, or similar, that take away their so cherished independence. IoT has the great potential to help elder citizens stay healthier at home, since it has the possibility to connect and create non-intrusive systems capable of interpreting data and act accordingly. With that capability, comes the responsibility to ensure that the collected data is reliable and trustworthy, as human wellbeing may rely on it. Addressing this uncertainty is the motivation for the presented work. The proposed methodology to reduce this uncertainty and increase confidence relies on a data fusion and a redundancy approach, using a sensor set. Since the scope of wellbeing environment is wide, this paper focuses its proof of concept on the detection of falls inside home environments. The experimental results demonstrate that the solution implemented has more than 80% of reliable performance and can provide trustworthy results. |
|---|---|
| Autores principais: | Pereira Michel, Lisa |
| Outros Autores: | Lopes, Carlos; Agostinho, Carlos; Melo de Almeida, Raquel |
| Assunto: | Confidence metric data fusion healthcare General Computer Science SDG 3 - Good Health and Well-being |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868983114698588160 |
|---|---|
| author | Pereira Michel, Lisa |
| author2 | Lopes, Carlos Agostinho, Carlos Melo de Almeida, Raquel |
| author2_role | author author author |
| author_facet | Pereira Michel, Lisa Lopes, Carlos Agostinho, Carlos Melo de Almeida, Raquel |
| author_role | author |
| contributor_name_str_mv | DEE - Departamento de Engenharia Electrotécnica e de Computadores UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias CTS - Centro de Tecnologia e Sistemas Universidada de Los Lagos RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Pereira Michel, Lisa\"},{\"Person.name\":\"Lopes, Carlos\"},{\"Person.name\":\"Agostinho, Carlos\"},{\"Person.name\":\"Melo de Almeida, Raquel\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | DEE - Departamento de Engenharia Electrotécnica e de Computadores UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias CTS - Centro de Tecnologia e Sistemas Universidada de Los Lagos RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Pereira Michel, Lisa Lopes, Carlos Agostinho, Carlos Melo de Almeida, Raquel |
| datacite.date.Accepted.fl_str_mv | 2022-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2026-01-14T10:50:22Z |
| datacite.date.embargoed.fl_str_mv | 2026-01-14T10:50:22Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Confidence metric data fusion healthcare General Computer Science SDG 3 - Good Health and Well-being |
| datacite.titles.title.fl_str_mv | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| dc.contributor.none.fl_str_mv | DEE - Departamento de Engenharia Electrotécnica e de Computadores UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias CTS - Centro de Tecnologia e Sistemas Universidada de Los Lagos RUN |
| dc.creator.none.fl_str_mv | Pereira Michel, Lisa Lopes, Carlos Agostinho, Carlos Melo de Almeida, Raquel |
| dc.date.Accepted.fl_str_mv | 2022-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2026-01-14T10:50:22Z |
| dc.date.embargoed.fl_str_mv | 2026-01-14T10:50:22Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/198796 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Confidence metric data fusion healthcare General Computer Science SDG 3 - Good Health and Well-being |
| dc.title.fl_str_mv | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | The transition to the so-called retirement years comes with the freedom to pursue old passions and hobbies that were not possible to do in the past busy life. Unfortunately, that freedom does not come alone, as the previous young years are gone, and the body starts to feel the time that passed. The necessity to adapt elder way of living grows as they become more prone to health problems. Often, the solution for the attention required by the elders is nursing homes, or similar, that take away their so cherished independence. IoT has the great potential to help elder citizens stay healthier at home, since it has the possibility to connect and create non-intrusive systems capable of interpreting data and act accordingly. With that capability, comes the responsibility to ensure that the collected data is reliable and trustworthy, as human wellbeing may rely on it. Addressing this uncertainty is the motivation for the presented work. The proposed methodology to reduce this uncertainty and increase confidence relies on a data fusion and a redundancy approach, using a sensor set. Since the scope of wellbeing environment is wide, this paper focuses its proof of concept on the detection of falls inside home environments. The experimental results demonstrate that the solution implemented has more than 80% of reliable performance and can provide trustworthy results. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://run.unl.pt/bitstreams/c997debd-c4c5-405f-b79f-59143d360473/download |
| id | run_fc7e21dcf7eceb087bca6ab6cafd2de9 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10362/198796 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
| instacron_str | unl |
| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
| network_acronym_str | run |
| network_name_str | Repositório Institucional da UNL |
| oai_identifier_str | oai:run.unl.pt:10362/198796 |
| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Pereira Michel, Lisa Lopes, Carlos Agostinho, Carlos Melo de Almeida, Raquel |
| publishDate | 2022 |
| repo_facet_str | urn:repositoryAcronym:run{{{_:::_}}}Repositório Institucional da UNL |
| reponame_str | Repositório Institucional da UNL |
| repository_id_str | urn:repositoryAcronym:run |
| service_str_mv | urn:repositoryAcronym:run |
| spelling | engenThe transition to the so-called retirement years comes with the freedom to pursue old passions and hobbies that were not possible to do in the past busy life. Unfortunately, that freedom does not come alone, as the previous young years are gone, and the body starts to feel the time that passed. The necessity to adapt elder way of living grows as they become more prone to health problems. Often, the solution for the attention required by the elders is nursing homes, or similar, that take away their so cherished independence. IoT has the great potential to help elder citizens stay healthier at home, since it has the possibility to connect and create non-intrusive systems capable of interpreting data and act accordingly. With that capability, comes the responsibility to ensure that the collected data is reliable and trustworthy, as human wellbeing may rely on it. Addressing this uncertainty is the motivation for the presented work. The proposed methodology to reduce this uncertainty and increase confidence relies on a data fusion and a redundancy approach, using a sensor set. Since the scope of wellbeing environment is wide, this paper focuses its proof of concept on the detection of falls inside home environments. The experimental results demonstrate that the solution implemented has more than 80% of reliable performance and can provide trustworthy results.application/pdfenA Methodology for Trustworthy IoT in Healthcare-Related EnvironmentsPereira Michel, LisaLopes, CarlosAgostinho, CarlosMelo de Almeida, RaquelDEE - Departamento de Engenharia Electrotécnica e de ComputadoresUNINOVA-Instituto de Desenvolvimento de Novas TecnologiasCTS - Centro de Tecnologia e SistemasUniversidada de Los LagosHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptISSNIsPartOf1613-0073URNIsPartOfPURE: 54045740URNIsPartOfPURE UUID: a3f62452-fff0-4fbc-9901-96df37192abaURNIsPartOfScopus: 851386755242026-01-14T10:50:22Z20222022-01-01T00:00:00ZHandlehttp://hdl.handle.net/10362/198796http://purl.org/coar/access_right/c_abf2open accessConfidence metricdata fusionhealthcareGeneral Computer ScienceSDG 3 - Good Health and Well-being790733 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/c997debd-c4c5-405f-b79f-59143d360473/download |
| spellingShingle | A Methodology for Trustworthy IoT in Healthcare-Related Environments Pereira Michel, Lisa Confidence metric data fusion healthcare General Computer Science SDG 3 - Good Health and Well-being |
| status | SINGLETON |
| subject.fl_str_mv | Confidence metric data fusion healthcare General Computer Science SDG 3 - Good Health and Well-being |
| title | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| title_full | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| title_fullStr | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| title_full_unstemmed | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| title_short | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| title_sort | A Methodology for Trustworthy IoT in Healthcare-Related Environments |
| topic | Confidence metric data fusion healthcare General Computer Science SDG 3 - Good Health and Well-being |
| topic_facet | Confidence metric data fusion healthcare General Computer Science SDG 3 - Good Health and Well-being |
| url | http://hdl.handle.net/10362/198796 |
| visible | 1 |