Non-Intrusive Load Monitoring of Household Devices Using a Hybrid Deep Learning Model through Convex Hull-Based Data Selection

The availability of smart meters and IoT technology has opened new opportunities, ranging from monitoring electrical energy to extracting various types of information related to household occupancy, and with the frequency of usage of different appliances. Non-intrusive load monitoring (NILM) allows...

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Detalhes bibliográficos
Autor principal: Laouali, Inoussa (author)
Outros Autores: Ruano, Antonio (author), Ruano, Maria da Graça (author), Bennani, Saad Dosse (author), Fadili, Hakim El (author)
Formato: article
Idioma:eng
Publicado em: 2022
Assuntos:
non-intrusive load monitoring
energy disaggregation
low frequency power data
convex hull
bidirectional long short time memory
convolutional neural networks
Texto completo:http://hdl.handle.net/10316/103236
País:Portugal
Oai:oai:estudogeral.sib.uc.pt:10316/103236

Texto Completo

http://hdl.handle.net/10316/103236

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