Today, the increase of computing capacity and the increasing complexity of problems
cause the steady spread of soft computing methods used in information systems. One
promising topic in the building automation ﬁeld is the identiﬁcation of electrical equipments
based on their power consumption parameters. Electrical devices identiﬁed this way can be
monitored,the given power consumptionhabits andpossiblemalfunction canbe discovered.
The thesis aims to achieve a working recognition system implemented in MATLAB
environment, with suﬃcient accuracy for identiﬁcation of consumers. Future embedded
implementation should be taken account – in the design phase the reduced computing
capacity, and accuracy available in embedded systems, particularly.
Previous research results and application possibilities of the topic are reviewed, we touch
their suitability questions. The results of these papers served as a basis, we use some of
the methods used in these articles.
The diﬃculties of creating feature-vectors, particularly the problem of high-dimensional
data representation are described. We investigate two widely used solutions – they are the
principal component analysis (PCA) and linear discriminant analysis (LDA). We discuss
non-hierarchical clustering methods are discussed in those categories that are relevant to
resolv our problem - these are the k-means, kernel k-means and Gaussian Mixture Model
We overview classiﬁcation techniques, focusing on their applicability to our problem –
especially the high computational requirements and recognition accuracy. The considered
classiﬁers are the neural network, the KNN method and some other distance-based classi-
The problems of detection eﬃciency, and also the suitable the analysis methods of these
techniques are presented. The presented techniques are the confusion matrix and ROC
The system is tested on real data samples in cross-validated manner. The implemented
identiﬁcation algorythm works with suﬃcient precision, but we also present some recom-
mendations to increase the accuracy of the system.