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: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/20251 |
Resumo: | The concept of smart homes is increasingly expanding and the number of objects we have at home that are connected grows exponentially. The so-called internet of things is increasingly englobing more home devices and the need to control them is also growing. However, there are numerous platforms that integrate numerous protocols and devices in many ways, many of them being unintuitive. Something that we always carry with us is our mobile devices and with the evolution of technology, they have become increasingly powerful and equipped with lots of sensors. One of the bridges to the real world in these devices is the camera and its many potentials. The amount of information gathered can be used in a variety of ways and one topic that has also gathered tremendous relevance is Artificial Intelligence and Machine Learning algorithms. Thus, with the correct processing, data collected by the sensors could be used intuitively to interact with such devices present at home. This dissertation presents the prototype of a system that integrates mobile devices in home automation platforms by detecting objects in the information collected by their cameras, consequently allowing the user to interact with them in an intuitive way. The main contribution of the work developed is the non-explored until then integration, in the home automation context, of cutting-edge algorithms capable of easily outperforming humans into analyzing and processing data acquired by our mobile devices. Throughout the dissertation the referred concepts are explored as well as the potentiality of this integration and the results obtained. |
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Integration of mobile devices in home automation with use of machine learning for object recognitionInternet of thingsSmart homesComputer visionMachine learningMobile devicesInternet das coisasCasas inteligentesComputação visualAprendizagem máquinaDispositivos móveisThe concept of smart homes is increasingly expanding and the number of objects we have at home that are connected grows exponentially. The so-called internet of things is increasingly englobing more home devices and the need to control them is also growing. However, there are numerous platforms that integrate numerous protocols and devices in many ways, many of them being unintuitive. Something that we always carry with us is our mobile devices and with the evolution of technology, they have become increasingly powerful and equipped with lots of sensors. One of the bridges to the real world in these devices is the camera and its many potentials. The amount of information gathered can be used in a variety of ways and one topic that has also gathered tremendous relevance is Artificial Intelligence and Machine Learning algorithms. Thus, with the correct processing, data collected by the sensors could be used intuitively to interact with such devices present at home. This dissertation presents the prototype of a system that integrates mobile devices in home automation platforms by detecting objects in the information collected by their cameras, consequently allowing the user to interact with them in an intuitive way. The main contribution of the work developed is the non-explored until then integration, in the home automation context, of cutting-edge algorithms capable of easily outperforming humans into analyzing and processing data acquired by our mobile devices. Throughout the dissertation the referred concepts are explored as well as the potentiality of this integration and the results obtained.O conceito de casas inteligentes está cada vez mais em constante expansão e o número de objetos que temos em casa que estão conectados cresce exponencialmente. A tão chamada internet das coisas abrange cada vez mais dispositivos domésticos crescendo também a necessidade de os controlar. No entanto existem inúmeras plataformas que integram inúmeros protocolos e dispositivos, de inúmeras maneiras, muitas delas pouco intuitivas. Algo que transportamos sempre connosco são os nossos dispositivos móveis e com a evolução da tecnologia, estes vieram-se tornando cada vez mais potentes e munidos de variados sensores. Uma das portas para o mundo real nestes dispositivos é a câmara e as suas inúmeras potencialidades. Uma temática que tem vindo também a ganhar enorme relevância é a Inteligência Artificial e os algoritmos de Aprendizagem Máquina. Assim, com o processamento correto os dados recolhidos pelos sensores poderiam ser utilizados de maneira intuitiva para interagir com os tais dispositivos presentes em casa. Nesta dissertação é apresentado o protótipo de um sistema que integra os dispositivos móveis nas plataformas de automação de casas através da deteção de objetos na informação recolhida pela câmara dos mesmos, permitindo assim ao utilizador interagir com eles de forma intuitiva. A principal contribuição do trabalho desenvolvido é a integração não explorada até então, no contexto da automação de casas, de algoritmos de ponta capazes de superar facilmente os seres humanos na análise e processamento de dados adquiridos pelos nossos dispositivos móveis. Ao longo da dissertação são explorados os conceitos referidos, bem como a potencialidade dessa integração e os resultados obtidos.2020-03-27T14:57:06Z2019-12-10T00:00:00Z2019-12-102019-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/20251TID:202459900engPassinhas, Rui Jorge Silvainfo: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:RCAAP2023-11-09T17:57:15Zoai:repositorio.iscte-iul.pt:10071/20251Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:29:30.586615Repositório 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, Rui Jorge Silva Internet of things Smart homes Computer vision Machine learning Mobile devices Internet das coisas Casas inteligentes Computação visual Aprendizagem máquina Dispositivos móveis |
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, Rui Jorge Silva |
author_facet |
Passinhas, Rui Jorge Silva |
author_role |
author |
dc.contributor.author.fl_str_mv |
Passinhas, Rui Jorge Silva |
dc.subject.por.fl_str_mv |
Internet of things Smart homes Computer vision Machine learning Mobile devices Internet das coisas Casas inteligentes Computação visual Aprendizagem máquina Dispositivos móveis |
topic |
Internet of things Smart homes Computer vision Machine learning Mobile devices Internet das coisas Casas inteligentes Computação visual Aprendizagem máquina Dispositivos móveis |
description |
The concept of smart homes is increasingly expanding and the number of objects we have at home that are connected grows exponentially. The so-called internet of things is increasingly englobing more home devices and the need to control them is also growing. However, there are numerous platforms that integrate numerous protocols and devices in many ways, many of them being unintuitive. Something that we always carry with us is our mobile devices and with the evolution of technology, they have become increasingly powerful and equipped with lots of sensors. One of the bridges to the real world in these devices is the camera and its many potentials. The amount of information gathered can be used in a variety of ways and one topic that has also gathered tremendous relevance is Artificial Intelligence and Machine Learning algorithms. Thus, with the correct processing, data collected by the sensors could be used intuitively to interact with such devices present at home. This dissertation presents the prototype of a system that integrates mobile devices in home automation platforms by detecting objects in the information collected by their cameras, consequently allowing the user to interact with them in an intuitive way. The main contribution of the work developed is the non-explored until then integration, in the home automation context, of cutting-edge algorithms capable of easily outperforming humans into analyzing and processing data acquired by our mobile devices. Throughout the dissertation the referred concepts are explored as well as the potentiality of this integration and the results obtained. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-10T00:00:00Z 2019-12-10 2019-10 2020-03-27T14:57:06Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/20251 TID:202459900 |
url |
http://hdl.handle.net/10071/20251 |
identifier_str_mv |
TID:202459900 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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.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 |
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1799134856884518912 |