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Smart monitoring of electrical circuits for distinction of connected devices through current pattern analysis using machine learning algorithms
Smart monitoring of electrical circuits for distinction of connected devices through current pattern analysis using machine learning algorithms
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MAP20200037262
Oliveira Lima, Jean Phelipe de
Smart monitoring of electrical circuits for distinction of connected devices through current pattern analysis using machine learning algorithms / Jean Phelipe de Oliveira Lima, Carlos Maurício Seródio Figueiredo
Artículo en portugués
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
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
1. Inteligencia artificial . 2. Machine learning . 3. Eficiencia energética . 4. Consumo energético . I. Seródio Figueiredo, Carlos Maurício . II. Título.