Smart monitoring of electrical circuits for distinction of connected devices through current pattern analysis using machine learning algorithms

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<dc:creator>Oliveira Lima, Jean Phelipe de </dc:creator>
<dc:creator>Seródio Figueiredo, Carlos Maurício </dc:creator>
<dc:date>2020-12-01</dc:date>
<dc:description xml:lang="es">Artículo en portugués</dc:description>
<dc:description xml:lang="es">Sumario: Energy Monitoring is a crucial activity in Energy Eciency, which involves the study of techniques to supervise the energy consumption in a power grid, regarding the main purpose is to assure a good level of detail, to achieve consumption quotas for each connected device, for a low infrastructure cost. This paper presents the evaluation of dierent Machine Learning models to classify electric current patterns to identify and monitor electric charges present in circuits with a single sensing device. The models were trained and validated by a database created from signal samples of 4 electrical devices: Notebook Charger, Refrigerator, Blender and Fan. The models that presented the best metrics achieved, respectively, 97% and 100% Accuracy and 98% and 100% F1-Score, surpassing results obtained in related researches.</dc:description>
<dc:format xml:lang="en">application/pdf</dc:format>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/record.do?id=173800</dc:identifier>
<dc:language>por</dc:language>
<dc:rights xml:lang="es">In Copyright (InC) - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Inteligencia artificial</dc:subject>
<dc:subject xml:lang="es">Machine learning</dc:subject>
<dc:subject xml:lang="es">Eficiencia energética</dc:subject>
<dc:subject xml:lang="es">Consumo energético</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Smart monitoring of electrical circuits for distinction of connected devices through current pattern analysis using machine learning algorithms</dc:title>
<dc:relation xml:lang="es">En: Revista Iberoamericana de Inteligencia Artificial. - IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018- = ISSN 1988-3064. - 31/12/2020 Volumen 23 Número 66 - diciembre 2020 , p. 36-50</dc:relation>
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