Panalysis of the Efficiency of the VRS Algorithm in the Transmission of Weather Data

Abstract

In the first part of this paper a Variable rate sampling, algorithm for prediction has been described. Variable rate sampling systems were used for reducing power demand, by reducing the number of sent samples. In the second part is performed an experiment where is tested algorithm for prediction of data for transmission and transmitted data. For the purpose of this analyze transmission and predictions are performed for temperatures, air pressure, wind speed, and visibility. Prediction on the side of the transmission is performed using three different extrapolations (mam, mab, and ng). At the receiving side reconstruction of the received signal is performed applying Linear, Cubic, Makima, and Spline extrapolations, built into Matlab. A simple reconstruction is also performed, using the last known value for prediction the next value (this prediction is in the paper named Step extrapolation). Objective quality measures SR (correlation coefficient of reducing the number of samples between a number of measured and transmitted samples), and MAE (mean absolute error between the measured and predicted values of temperatures, pressures and visibility values) were calculated. The results are presented in the table and graphically.

Keywords

• VRS algorithm
• Efficiency
• Extrapolations
• Low power system

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