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 thesis focuses its proof of concept on the detection of falls inside home environments, through an android app using an accelerometer sensor and a micro- phone. The experimental results demonstrates that the implemented system has more than 80% of reliable performance and can provide trustworthy results. Currently the app is being tested also in the frame of the European Union projects Smart4Health and Smart Bear. |
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| Autores principais: | Michel, Lisa Pereira |
| Assunto: | Internet of Things Data Fusion Redundancy Wearable Device Well Being Healthcare |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| 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 thesis focuses its proof of concept on the detection of falls inside home environments, through an android app using an accelerometer sensor and a micro- phone. The experimental results demonstrates that the implemented system has more than 80% of reliable performance and can provide trustworthy results. Currently the app is being tested also in the frame of the European Union projects Smart4Health and Smart Bear. |
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