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Data Fusion in Internet of Things

datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.contributor.advisorPombo, Nuno Gonçalo Coelho Costa
dc.contributor.advisorSantos, Nuno Manuel Garcia dos
dc.contributor.advisorMerilampi, Sari
dc.contributor.authorMendes, Tiago Nobre de Albuquerque
dc.date.accessioned2020-03-25T14:33:35Z
dc.date.available2020-03-25T14:33:35Z
dc.date.issued2019-07-30
dc.date.submitted2019-06-24
dc.description.abstractThis dissertation reviews Internet of Things concepts and implementations, state-of-the-art technology with practical examples, as well as data fusion methods applied in different problems. The purpose of this study is to review different data fusion methods and develop a system to provide recognition of human activity that can be applied in day care homes and in hospitals to monitor patients. The system’s objective is to study human activity recognition based on the data recovered by sensors like accelerometers and gyroscopes. In order to transform this data to useful information and practical results to monitoring patients with accuracy and high performance, two different neural networks were implemented. To conclude, the results from the two different neural networks are compared to each other and compared with systems from other authors. It is hoped this study will inform other authors and developers about the performance of neural networks when managing human activity recognition systems.eng
dc.identifier.tid202365255
dc.identifier.urihttp://hdl.handle.net/10400.6/10222
dc.language.isoengpor
dc.subjectData Fusionpor
dc.subjectDeep Learningpor
dc.subjectHealth-Carepor
dc.subjectHuman Activity Recognitionpor
dc.subjectInternet of Thingspor
dc.subjectNeural Networkspor
dc.subjectSmart Homepor
dc.titleData Fusion in Internet of Thingspor
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspor
rcaap.typemasterThesispor
thesis.degree.name2º Ciclo em Engenharia Informáticapor

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