APPLICATION OF MACHINE LEARNING FOR REMOTE ELECTRONICS EXPERIMENTS AS THE MEAN OF INDENTIFICATION

Authors

  • Antoni Kozic Vilniaus kolegija/University of Applied Sciences
  • Andzej Lucun Vilniaus kolegija/University of Applied Sciences
  • Mindaugas Vingelis LUMO Advanced Lighting Company Expert
  • Eugenijus Macerauskas Vilniaus kolegija/University of Applied Sciences
  • Andrius Narmontas Vilniaus kolegija/University of Applied Sciences

DOI:

https://doi.org/10.17770/sie2021vol5.6371

Keywords:

machine learning, LabVIEW, remote laboratory

Abstract

We are increasingly faced with automated solutions that create a dynamic and constantly evolving scientific and technical environment, with new challenges in finding more accurate and efficient solutions for identification. This article introduces a machine learning application that allows you to automatically recognize and identify learners in a distance learning experiment without being explicitly programmed. Experimental methods and components have been transferred to a distance learning laboratory environment. A conceptual model of an electronics laboratory has been developed for remote experiments using identification methods. This article focuses on machine learning using the LabVIEW package, which can access data and use it for self-study. The article presents the application of machine learning software LabVIEW National Instruments and NI ELVIS hardware simulators for electronic laboratory remote experiments and perspectives in the educational process.

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Author Biographies

  • Antoni Kozic, Vilniaus kolegija/University of Applied Sciences
    Vilniaus kolegija/University of Applied Sciences,The Faculty of Electronics and Informatics,Electronics Department: Head of the Department: assoc. prof. dr. Antoni Kozič
  • Andzej Lucun, Vilniaus kolegija/University of Applied Sciences
    Vilniaus kolegija/University of Applied Sciences,The Faculty of Electronics and Informatics.Electronics Department: assoc. prof. dr.
  • Mindaugas Vingelis, LUMO Advanced Lighting Company Expert
    JSC Company: LUMO Advanced Lighting Company Exper
  • Eugenijus Macerauskas, Vilniaus kolegija/University of Applied Sciences
    Vilniaus kolegija/University of Applied Sciences,The Faculty of Electronics and InformaticsElectronics Department: assoc. prof. dr.
  • Andrius Narmontas, Vilniaus kolegija/University of Applied Sciences
    Vilniaus kolegija/University of Applied Sciences,The Faculty of Electronics and Informatics,Electronics Department,Electronic engineering study program student

References

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Published

2021-05-28

How to Cite

Kozic, A., Lucun, A., Vingelis, M., Macerauskas, E., & Narmontas, A. (2021). APPLICATION OF MACHINE LEARNING FOR REMOTE ELECTRONICS EXPERIMENTS AS THE MEAN OF INDENTIFICATION. SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference, 5, 371-378. https://doi.org/10.17770/sie2021vol5.6371