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dc.contributor.authorRosdi, N.A.M.en_US
dc.contributor.authorNordin, F.H.en_US
dc.contributor.authorRamasamy, A.K.en_US
dc.contributor.authorMustafa, N.B.A.en_US
dc.description.abstractMany researches have proven that power lines and electrical appliances do emit electromagnetic fields and can be harmful to human's health. However, research on the effect of the magnetic fields on human's health is not yet conclusive. Instead of letting the magnetic fields emit by the electrical appliances be wasted, this paper aims to use the magnetic fields to classify or identify the electrical appliances being used. Table fans, blenders and hairdryers are the electrical appliances used for this purpose where they are divided into three different categories of usage i.e. (i) used less than 1year (ii) used between 1 to 5 years and (iii) used more than 5 years. The magnetic fields are measured from all the nine appliances. Then, the features of the magnetic fields are extracted and trained offline using the Probabilistic Neural Network (PNN). From the results, it is shown that the PNN is able to identify the type of electrical appliance being used regardless of the appliances years of usage using magnetic fields emitted by the appliances. © 2014 IEEE.
dc.titleClassification of electrical appliances using magnetic field and probabilistic neural networken_US
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