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Decreasing Influence of the Error Due to Acquired Inhomogeneity of Sensors by the Means of Artificial Intelligence

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Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 140))

Abstract

Sensors usually have the biggest error among all components in a measuring system. The paper considers the application of the methods of artificial intelligence, in particular, neural networks and data science applications for sensor data processing. The main attention is focused on improvement of measurement accuracy when using inaccurate sensors. The abovementioned methods illustrated on the example of improvement of measurement accuracy of the most widely used temperature sensor—the thermocouple. Neural networks and other methods of artificial intelligence ensure the improvement of accuracy of temperature measurements by an order of magnitude. However, they require considerable complication in both hardware and software.

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Author information

Authors and Affiliations

  1. University of Library Studies and Information Technologies, 69A, Ship. Prohod Blvd., 1574, Sofia, Bulgaria

    Vladimir Jotsov

  2. Department of Information-Measuring Engineering, Lviv Polytechnic National University, Bandera Str., 12, Lviv, 79013, Ukraine

    Orest Kochan

  3. School of Computer Science, Hubei University of Technology, Wuhan, China

    Su Jun

Authors
  1. Vladimir Jotsov
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  2. Orest Kochan
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  3. Su Jun
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Corresponding author

Correspondence to Vladimir Jotsov .

Editor information

Editors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Vassil Sgurev

  2. University of Library Studies and Information Technologies, Sofia, Bulgaria

    Vladimir Jotsov

  3. Department of Computer Science, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Jotsov, V., Kochan, O., Jun, S. (2018). Decreasing Influence of the Error Due to Acquired Inhomogeneity of Sensors by the Means of Artificial Intelligence. In: Sgurev, V., Jotsov, V., Kacprzyk, J. (eds) Practical Issues of Intelligent Innovations. Studies in Systems, Decision and Control, vol 140. Springer, Cham. https://doi.org/10.1007/978-3-319-78437-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-78437-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78436-6

  • Online ISBN: 978-3-319-78437-3

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