Sensors and wrong values

Authors

  • Zoltán Pödör Dr

DOI:

https://doi.org/10.14738/tnc.94.10539

Keywords:

sensors, sensor data, missing data

Abstract

In the world of IoT and BigData, sensor based data collection is a really important domain. Using these tools it is possible to stow large amounts of data collection sensors in a factory or in nature in harsh environments. However, in order to obtain valuable information from these tools, it is important that potentially wrong data is discovered and handled. Automated exploration of wrong data is not a trivial task, even if similar measurements are performed in parallel with spatial differences. We present the difficulties of revealing defected data and suggest easy-to-implement procedures for detecting and handing them. We also draw attention to the potential disadvantages of these methods based on the given results.

References

Gludovátz A., Bacsárdi L., Industry 4.0 projects' background: Experiences at the wood industrial manufactories, SEFBIS JOURNAL XI/2018, 34-41.

Bencsik G., Random Correlation Methodology as a Tool for Analyzing Random Factor of Scientific Results, SEFBIS JOURNAL XII./2018, 11-20.

Jeffrey S. S. (1998), Smoothing Methods in Statistics (Springer Series in Statistics), Springer

Rice A. J. (2010), Mathematical Statistics and Data Analysis, Third edition, Kindle Edition

https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/

Downloads

Published

2021-07-30

How to Cite

Pödör, Z. (2021). Sensors and wrong values. Transactions on Networks and Communications, 9(4), 23–28. https://doi.org/10.14738/tnc.94.10539