Discrete Wavelet Transform and Classifiers for Appliances Recognition

  • El Bouazzaoui Cherraqi
  • Nadia Oukrich
  • Soufiane El Moumni
  • Abdelilah Maach
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 37)


Recognition of appliances’ signatures is an important task in energy disaggregation applications. To save and manage energy, load signatures provided by appliances can be used to detect which appliance is used. In this study, we use a low frequency database to identify appliances based on discrete wavelet transform for features extraction and data dimensionality reduction. Further that, the accuracy of several classifiers is investigated. This paper aims to prove the effectiveness of DWT in load signatures recognition. Then, the best classifier for this studied task is selected.


Classifiers Discrete Wavelet Transform (DWT) Appliances recognition 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Mohammadia School of EngineeringMohammed V University in RabatRabatMorocco
  2. 2.Laboratory of Information ProcessingHassan II-University of CasablancaCasablancaMorocco

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