Calibration and Validation of INA219 as Sensor Power Monitoring System using Linear Regression

Authors

  • Farah Yuki Prasetyawati Sebelas Maret University image/svg+xml
  • Dewanto Harjunowibowo Sebelas Maret University image/svg+xml
  • Ahmad Fauzi Physics Education Department, Sebelas Maret University, Indonesia.
  • Bayu Utomo Sebelas Maret University image/svg+xml
  • Dani Harmanto De Montfort University image/svg+xml

DOI:

https://doi.org/10.53799/ajse.v22i3.595

Abstract

Electricity demand which increases up to 2.7%, needs to be evaluated to prevent power wastage. This paper proposes an INA219 sensor and a power monitoring solution based on the ESP8266. Power Monitoring stores and displays real-time data in Google Sheets via Blynk version 1.0.1. The system has been calibrated with a fixed LED and resistor as a voltage calibration load. Meanwhile, the lamp and shunt resistors calibrate the shunt voltage. The measuring tools for comparison in calibration are digital multimeters, oscilloscopes, and power data loggers. Calibration using the linear regression technique with accuracy, precision, and uncertainty analysis are determined by Mean Absolute Percent Error (MAPE), Relative Standard Deviation (RSD), and Gaussian distribution. Successively, the sensor coefficient of determination (R2), accuracy, precision, and uncertainty of the load voltage and shunt voltage are 0.999 and 0.997, 99.27% ​​and 93.71%, 99.82% and 99.55%,  0.37 V and 0.89 mV.

Author Biographies

  • Farah Yuki Prasetyawati, Sebelas Maret University

    Farah Yuki Prasetyawati is active as a Physics Education student at Sebelas Maret University. She is one of the outstanding students at his university with various national and international achievements. Apart from that, she has also studied applied physics, electronics, and renewable energy.

  • Dewanto Harjunowibowo, Sebelas Maret University

    Dewanto Harjunowibowo is active as a researcher and lecturer in Physics Education at Sebelas Maret University, Indonesia. He has expertise in physics, electronics, and renewable energy. He has also successfully published various books, scientific articles, and intellectual property rights nationally and internationally.

  • Bayu Utomo, Sebelas Maret University

    Bayu Utomo is active as a postgraduate researcher in the Department of Architecture and Build Environment, Faculty of Engineering, University of Nottingham, Nottingham, UK. He is a member of the Research Group for Electrical, Energy, and Environment, the National Research and Innovation Agency (BRIN). In addition, he has expertise in renewable energy.

  • Dani Harmanto, De Montfort University

    Dani Harmanto is an Associate Professor of Aeronautical Engineering at De Montfort University. In addition, he is also an expert in the fields of mechanical, automotive, engineering, manufacturing, and electronics.

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Published

12/27/2023

Issue

Vol. 22 No. 3 (2023): AJSE Volume 22 Issue 3

Section

Articles

License

AJSE contents are under the terms of the Creative Commons Attribution License. This permits anyone to copy, distribute, transmit and adapt the work non-commercially provided the original work and source is appropriately cited.

How to Cite

[1]
“Calibration and Validation of INA219 as Sensor Power Monitoring System using Linear Regression”, AJSE, vol. 22, no. 3, pp. 240–249, Dec. 2023, doi: 10.53799/ajse.v22i3.595.