Classification of electrical appliances using magnetic field and probabilistic neural network

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Many 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.

Original languageEnglish
Title of host publicationProceedings - 2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages268-273
Number of pages6
ISBN (Electronic)9781479956920
DOIs
Publication statusPublished - 01 Jan 2014
Event2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014 - Shah Alam, Malaysia
Duration: 11 Aug 201412 Aug 2014

Other

Other2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014
CountryMalaysia
CityShah Alam
Period11/08/1412/08/14

Fingerprint

Magnetic fields
Neural networks
Health
Electromagnetic fields
Fans

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Rosdi, N. A. M., Nordin, F. H., Ramasamy, A., & Ahmad Mustafa, N. B. (2014). Classification of electrical appliances using magnetic field and probabilistic neural network. In Proceedings - 2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014 (pp. 268-273). [6908735] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSGRC.2014.6908735
Rosdi, Nurul Aishah Mohd ; Nordin, Farah Hani ; Ramasamy, Agileswari ; Ahmad Mustafa, Nur Badariah. / Classification of electrical appliances using magnetic field and probabilistic neural network. Proceedings - 2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 268-273
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Rosdi, NAM, Nordin, FH, Ramasamy, A & Ahmad Mustafa, NB 2014, Classification of electrical appliances using magnetic field and probabilistic neural network. in Proceedings - 2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014., 6908735, Institute of Electrical and Electronics Engineers Inc., pp. 268-273, 2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014, Shah Alam, Malaysia, 11/08/14. https://doi.org/10.1109/ICSGRC.2014.6908735

Classification of electrical appliances using magnetic field and probabilistic neural network. / Rosdi, Nurul Aishah Mohd; Nordin, Farah Hani; Ramasamy, Agileswari; Ahmad Mustafa, Nur Badariah.

Proceedings - 2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 268-273 6908735.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Many 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.

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Rosdi NAM, Nordin FH, Ramasamy A, Ahmad Mustafa NB. Classification of electrical appliances using magnetic field and probabilistic neural network. In Proceedings - 2014 5th IEEE Control and System Graduate Research Colloquium, ICSGRC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 268-273. 6908735 https://doi.org/10.1109/ICSGRC.2014.6908735