Calibration of Dissolved Oxygen Sensors in IoT Systems for Water Quality Monitoring in Aquaculture

Authors

  • Gema Parasti Mindara Computer Engineering Technology, Vocational School, IPB University, Indonesia
  • Walidatush Sholihah Faculty of Science and Engineering, University of Groningen, Netherlands https://orcid.org/0000-0002-4276-4450
  • Inna Novianty Computer Engineering Technology, Vocational School, IPB University, Indonesia https://orcid.org/0000-0002-2170-9030
  • Lathifunnisa Fathonah Computer Engineering Technology, Vocational School, IPB University, Indonesia https://orcid.org/0009-0005-0602-0939
  • Faldiena Marcelita Computer Engineering Technology, Vocational School, IPB University, Indonesia https://orcid.org/0009-0002-9728-1760
  • Ridwan Siskandar Computer Engineering Technology, Vocational School, IPB University, Indonesia https://orcid.org/0000-0003-2911-3108
  • Dodik Ariyanto Computer Engineering Technology, Vocational School, IPB University, Indonesia https://orcid.org/0000-0001-5891-4540
  • Bayu Widodo Computer Engineering Technology, Vocational School, IPB University, Indonesia
  • Aep Setiawan Computer Engineering Technology, Vocational School, IPB University, Indonesia
  • Naufal Rizqullah Firdaus Computer Engineering Technology, Vocational School, IPB University, Indonesia

DOI:

https://doi.org/10.21009/SPEKTRA.103.06

Keywords:

DO sensor accuracy, IoT, calibration, dissolved oxygen sensor, aquaculture, water quality monitoring

Abstract

Dissolved Oxygen (DO) is an important parameter for maintaining water quality in aquaculture systems. The accuracy of DO sensors significantly affects the reliability of Internet of Things (IoT)-based monitoring systems. This study aimed to calibrate the DO sensor using a two-point calibration method and evaluate the accuracy of the sensor readings compared with those of a reference device (standard DO meter). A key novelty of this study lies in its multi-media calibration, performed directly on six distinct aquaculture water types, providing field-realistic validation conditions not commonly explored in previous studies. Furthermore, the accuracy of the calibrated sensor is evaluated quantitatively using MAE, RMSE, and percentage deviation to ensure rigorous performance assessment. The system was developed using an ESP32 microcontroller, DO sensor (SEN0237), DS18B20 temperature sensor, and ADS1115 ADC module. Testing was performed on six types of aquaculture water media and compared with a standard DO meter using a comparative approach. In total, n = 6 field measurement points (one stabilized reading per water medium) were used to compute MAE, RMSE, and percentage deviation. The comparison results showed that the calibrated sensor had high accuracy, with a Mean Absolute Error (MAE) of 0.1083 mg/L and a Root Mean Square Error (RMSE) of 0.2654 mg/L. Significant deviations occurred only in one type of water medium, whereas the other five showed results consistent with the reference device, indicating stable sensor readings. These findings confirm that proper calibration can improve the accuracy and reliability of IoT systems used for water-quality monitoring. Regular calibration is required to maintain the sensor performance, particularly for long-term use in dynamic aquaculture water environments.

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Published

2025-12-30

How to Cite

Mindara, G. P., Sholihah, W., Novianty, I., Fathonah, L., Marcelita, F., Siskandar, R., … Firdaus, N. R. (2025). Calibration of Dissolved Oxygen Sensors in IoT Systems for Water Quality Monitoring in Aquaculture. Spektra: Jurnal Fisika Dan Aplikasinya, 10(3), 215–230. https://doi.org/10.21009/SPEKTRA.103.06

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Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025

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Copyright (c) 2025 Gema Parasti Mindara, Walidatush Sholihah, Inna Novianty, Lathifunnisa Fathonah, Faldiena Marcelita, Ridwan Siskandar, Dodik Ariyanto, Bayu Widodo, Aep Setiawan, Naufal Rizqullah Firdaus

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