Identificação de assinaturas de carga de eletrodomésticos residenciais em Smart Meters usando Inteligência Artificial e IoT: Implementação e testbed

Autores

  • Thiago C. Sousa Universidade Federal do Piauí (UFPI)
  • Artur Felipe da Silva Veloso Faculdade Estacio (CEUT), PI
  • Regenildo G. Oliveira Faculdade Estacio (CEUT), PI
  • Antonio A Rodrigues Faculdade FAETE, PI
  • Davi L. Oliveira Universidade Federal do Piauí (UFPI), PI
  • Altamir J Gallas Faculdade Maurício de Nassau, PI
  • José V. V. Sobral Instituto de Telecomunicações, Universidade da Beira Interior

DOI:

https://doi.org/10.13037/ria.vol14n1.221

Resumo

A identificação de eletrodomésticos individualmente na rede elétrica residencial, prover um melhor controle do consumo e detecção de anomalias presentes em alguns desses eletrodomésticos. Essa identificação só é possível se cada eletrodoméstico tiver uma assinatura de cargas. A geração da assinatura de carga, se da através de aplicações como o medidor inteligente que fornece informações necessárias para este fim. O trabalho proposto permite a leitura e detecção de eletrodomésticos residenciais presentes na rede, através da assinatura de carga individual, utilizando medidores inteligentes juntamente com Inteligência Artificial. Alguns parâmetros elétricos importantes serão analisados e detectados de forma individual. Com auxílio do algoritmo Naive Bayes, os dados da criação de assinatura de cargas são armazenados em um banco de dados e treinados para que a identificação seja possível. Contudo, é fornecido ao consumidor uma aplicação que permite identificar e classificar qualquer equipamento existente na residência quando estiver ativo, assim como anomalias e alterações presentes na rede residencial.

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Biografia do Autor

Artur Felipe da Silva Veloso, Faculdade Estacio (CEUT), PI

Trabalha desde 2013 com a plataforma de prototipagem Arduino. Formado em 2017.1 em CIência da computação na Estácio CEUT, em Teresina Piauí. Poussi trabalhos de pesquisa na área de Internet of Things, Advanced Metering Infrastructure, Smart Meter, Communication e Desenvolvimento de sistemas. Atualmente trabalha como professor de IoT no Senac Piauí e como Maker Gerente na empresa Gado Azul, onde gerencia uma equipe maker que desenvolve soluções IoT para automação de fazendas.

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Publicado

2020-05-31

Como Citar

Sousa, T. C., Veloso, A. F. da S., Oliveira, R. G., Rodrigues, A. A., Oliveira, D. L., Gallas, A. J., & Sobral, J. V. V. (2020). Identificação de assinaturas de carga de eletrodomésticos residenciais em Smart Meters usando Inteligência Artificial e IoT: Implementação e testbed. Revista De Informática Aplicada, 14(1). https://doi.org/10.13037/ria.vol14n1.221

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