Integration of mobile devices in home automation with use of machine learning for object recognition
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/22749 |
Resumo: | The number of smart homes is increasingly expanding, with even more connected devices and available control options. Mobile devices have unfortunately been up to now generally regarded as mere remote controls in these environments. This paper addresses this shortcoming, by presenting a novel integration architecture and prototype where the potential of mobile devices sensors can be better explored in home automation platforms, in particular by detecting objects in the information collected by their cameras that subsequently allow for users to interact with them in an intuitive way. The detection is performed at the mobile side, using a lightweight machine learning solution. The obtained accuracy and processing time are comparable to that obtained at server side. But the advantage here is that the interactive experience of users can be dramatically improved, with the absence of round-trip time required if server processing would be used. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Integration of mobile devices in home automation with use of machine learning for object recognitionThe number of smart homes is increasingly expanding, with even more connected devices and available control options. Mobile devices have unfortunately been up to now generally regarded as mere remote controls in these environments. This paper addresses this shortcoming, by presenting a novel integration architecture and prototype where the potential of mobile devices sensors can be better explored in home automation platforms, in particular by detecting objects in the information collected by their cameras that subsequently allow for users to interact with them in an intuitive way. The detection is performed at the mobile side, using a lightweight machine learning solution. The obtained accuracy and processing time are comparable to that obtained at server side. But the advantage here is that the interactive experience of users can be dramatically improved, with the absence of round-trip time required if server processing would be used.Association for Computing Machinery2021-06-17T09:33:54Z2020-01-01T00:00:00Z20202021-06-17T10:32:52Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10071/22749eng978-1-4503-7711-9Passinhas, R.Marinheiro, R. N.Nunes, P.info: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:RCAAP2024-07-07T02:50:55Zoai:repositorio.iscte-iul.pt:10071/22749Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T02:50:55Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Integration of mobile devices in home automation with use of machine learning for object recognition |
title |
Integration of mobile devices in home automation with use of machine learning for object recognition |
spellingShingle |
Integration of mobile devices in home automation with use of machine learning for object recognition Passinhas, R. |
title_short |
Integration of mobile devices in home automation with use of machine learning for object recognition |
title_full |
Integration of mobile devices in home automation with use of machine learning for object recognition |
title_fullStr |
Integration of mobile devices in home automation with use of machine learning for object recognition |
title_full_unstemmed |
Integration of mobile devices in home automation with use of machine learning for object recognition |
title_sort |
Integration of mobile devices in home automation with use of machine learning for object recognition |
author |
Passinhas, R. |
author_facet |
Passinhas, R. Marinheiro, R. N. Nunes, P. |
author_role |
author |
author2 |
Marinheiro, R. N. Nunes, P. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Passinhas, R. Marinheiro, R. N. Nunes, P. |
description |
The number of smart homes is increasingly expanding, with even more connected devices and available control options. Mobile devices have unfortunately been up to now generally regarded as mere remote controls in these environments. This paper addresses this shortcoming, by presenting a novel integration architecture and prototype where the potential of mobile devices sensors can be better explored in home automation platforms, in particular by detecting objects in the information collected by their cameras that subsequently allow for users to interact with them in an intuitive way. The detection is performed at the mobile side, using a lightweight machine learning solution. The obtained accuracy and processing time are comparable to that obtained at server side. But the advantage here is that the interactive experience of users can be dramatically improved, with the absence of round-trip time required if server processing would be used. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01T00:00:00Z 2020 2021-06-17T09:33:54Z 2021-06-17T10:32:52Z |
dc.type.driver.fl_str_mv |
conference object |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/22749 |
url |
http://hdl.handle.net/10071/22749 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
978-1-4503-7711-9 |
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 |
Association for Computing Machinery |
publisher.none.fl_str_mv |
Association for Computing Machinery |
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 |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
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1817546337141391360 |