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A Methodology for Trustworthy IoT in Healthcare-Related Environments

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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

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