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In this article, a new low-cost measurement system for measuring the electric component of the electromagnetic
field is presented. For the initial calibration of the new measurement system, a reference meter was used, based on
its readings, calibration was carried out using a machine learning model. Initial calibration was carried out in a
GTEM 1000 with a Teseq ITS 6006 generator connected. Five models were compared, among which the K-Nearest
Neighbors (KNN) model had the highest accuracy. The model was tested on 5 types of aircrafts, and its readings
were compared with a reference sensor. Test measurements were carried out in five types of aircrafts: Cessna
C172, Aero AT-3 R100, Tecnam P2006T, PZL M28 Bryza and the Mi -8 helicopter with the developed new
measurement system and a reference meter (NHT3DL) with 01E probe. The new measurement system is small in
size and fits anywhere in the aircraft cockpit. To compare the models, the following metrics were used: the
coefficient of determination, mean absolute error, mean square error and root mean square error. The Two-sample
Kolmogorov-Smirnov tests were used for analysis, and Bag of Words and Bag of Patterns methods were applied.
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