A Survey of Approaches to Unobtrusive Sensing of Humans
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/100009 https://doi.org/10.1145/3491208 |
Resumo: | The increasing amount of human-related and/or human-originated data in current systems is both an opportunity and a challenge. Nevertheless, despite relying on the processing of large amounts of data, most of the so-called smart systems that we have nowadays merely consider humans as sources of data, not as system beneficiaries or even active "components."For truly smart systems, we need to create systems that are able to understand human actions and emotions, and take them into account when deciding on the system behavior. Naturally, in order to achieve this, we first have to empower systems with human sensing capabilities, possibly in ways that are as inconspicuous as possible. In this context, in this article we survey existing approaches to unobtrusive monitorization of human beings, namely, of their activity, vital signs, and emotional states. After setting a taxonomy for human sensing, we proceed to present and analyze existing solutions for unobtrusive sensing. Subsequently, we identify and discuss open issues and challenges in this area. Although there are surveys that address some of the concerned fields of research, such as healthcare, human monitorization, or even the use-specific techniques like channel state information or image recognition, as far as we know this is the first comprehensive survey on unobtrusive sensing of human beings. © 2022 Association for Computing Machinery. |
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A Survey of Approaches to Unobtrusive Sensing of Humansdata processingHiTLIoTsignal processingUnobtrusive sensingThe increasing amount of human-related and/or human-originated data in current systems is both an opportunity and a challenge. Nevertheless, despite relying on the processing of large amounts of data, most of the so-called smart systems that we have nowadays merely consider humans as sources of data, not as system beneficiaries or even active "components."For truly smart systems, we need to create systems that are able to understand human actions and emotions, and take them into account when deciding on the system behavior. Naturally, in order to achieve this, we first have to empower systems with human sensing capabilities, possibly in ways that are as inconspicuous as possible. In this context, in this article we survey existing approaches to unobtrusive monitorization of human beings, namely, of their activity, vital signs, and emotional states. After setting a taxonomy for human sensing, we proceed to present and analyze existing solutions for unobtrusive sensing. Subsequently, we identify and discuss open issues and challenges in this area. Although there are surveys that address some of the concerned fields of research, such as healthcare, human monitorization, or even the use-specific techniques like channel state information or image recognition, as far as we know this is the first comprehensive survey on unobtrusive sensing of human beings. © 2022 Association for Computing Machinery.This work is funded by national funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the project CISUC – UID/CEC/00326/2020 and by the European Social Fund, through the Regional Operational Program Centro 2020. Also, the research presented in this article was carried out in the scope of the EEA Grants Portugal 2014– 2021–Bilateral Initiative number 63 “PrivacyCoLab” and the project iFriend – Supervisión inteligente del estado de salud en personas mayores con insuficiencia renal mediante dispositivos inalámbricos” supported by Fundación CSIC, Interreg Portugal-Espanha. José Marcelo Fernandes wishes to acknowledge the Portuguese funding institution FCT – Foundation for Science and Technology for supporting his research under the Ph.D. grant SFRH/BD/147371/2019ACM2022-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/100009http://hdl.handle.net/10316/100009https://doi.org/10.1145/3491208eng0360-03001557-7341Fernandes, José MarceloSilva, Jorge SáRodrigues, AndréBoavida, Fernandoinfo: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:RCAAP2022-06-29T17:36:17ZPortal AgregadorONG |
dc.title.none.fl_str_mv |
A Survey of Approaches to Unobtrusive Sensing of Humans |
title |
A Survey of Approaches to Unobtrusive Sensing of Humans |
spellingShingle |
A Survey of Approaches to Unobtrusive Sensing of Humans Fernandes, José Marcelo data processing HiTL IoT signal processing Unobtrusive sensing |
title_short |
A Survey of Approaches to Unobtrusive Sensing of Humans |
title_full |
A Survey of Approaches to Unobtrusive Sensing of Humans |
title_fullStr |
A Survey of Approaches to Unobtrusive Sensing of Humans |
title_full_unstemmed |
A Survey of Approaches to Unobtrusive Sensing of Humans |
title_sort |
A Survey of Approaches to Unobtrusive Sensing of Humans |
author |
Fernandes, José Marcelo |
author_facet |
Fernandes, José Marcelo Silva, Jorge Sá Rodrigues, André Boavida, Fernando |
author_role |
author |
author2 |
Silva, Jorge Sá Rodrigues, André Boavida, Fernando |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Fernandes, José Marcelo Silva, Jorge Sá Rodrigues, André Boavida, Fernando |
dc.subject.por.fl_str_mv |
data processing HiTL IoT signal processing Unobtrusive sensing |
topic |
data processing HiTL IoT signal processing Unobtrusive sensing |
description |
The increasing amount of human-related and/or human-originated data in current systems is both an opportunity and a challenge. Nevertheless, despite relying on the processing of large amounts of data, most of the so-called smart systems that we have nowadays merely consider humans as sources of data, not as system beneficiaries or even active "components."For truly smart systems, we need to create systems that are able to understand human actions and emotions, and take them into account when deciding on the system behavior. Naturally, in order to achieve this, we first have to empower systems with human sensing capabilities, possibly in ways that are as inconspicuous as possible. In this context, in this article we survey existing approaches to unobtrusive monitorization of human beings, namely, of their activity, vital signs, and emotional states. After setting a taxonomy for human sensing, we proceed to present and analyze existing solutions for unobtrusive sensing. Subsequently, we identify and discuss open issues and challenges in this area. Although there are surveys that address some of the concerned fields of research, such as healthcare, human monitorization, or even the use-specific techniques like channel state information or image recognition, as far as we know this is the first comprehensive survey on unobtrusive sensing of human beings. © 2022 Association for Computing Machinery. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/100009 http://hdl.handle.net/10316/100009 https://doi.org/10.1145/3491208 |
url |
http://hdl.handle.net/10316/100009 https://doi.org/10.1145/3491208 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0360-0300 1557-7341 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
ACM |
publisher.none.fl_str_mv |
ACM |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) 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 |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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_version_ |
1777302791899840512 |