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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

IoT-Based System for Real-Time Water Quality Monitoring and Advanced Turbidity and pH Sensor Calibration to Improve Accuracy and Reliability Using ThingSpeak

by
Mulhim Al Drees
1,
Abbas E. Rahma
1,*,
Samah Daffalla
1,
Rawabi Alsudais
2,
Naser Fathi Alsubaie
1,
Mohammed Albrahim
1,
Hassan Abdullah Alghanim
1 and
Mustafa I. Almaghasla
3
1
Department of Environment and Natural Agricultural Resources, College of Agricultural and Food Sciences, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia
2
Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia
3
Department of Arid Land Agriculture, College of Agriculture and Food Sciences, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia
*
Author to whom correspondence should be addressed.
IoT 2026, 7(2), 42; https://doi.org/10.3390/iot7020042
Submission received: 28 February 2026 / Revised: 23 April 2026 / Accepted: 24 April 2026 / Published: 12 May 2026
Versions Notes

Abstract

Water quality has become a major concern for public health, agriculture, and industry, necessitating reliable and continuous monitoring. Conventional monitoring methods are often time-consuming, rely on manual sampling, and involve complex equipment or procedures, making them unsuitable for real-time applications. This study presents an Internet of Things (IoT)-based system for real-time water quality monitoring using ESP32 hardware integrated with the ThingSpeak platform. The system enhances the accuracy of turbidity and pH measurements using advanced sensor calibration techniques. Nephelometric methods and glass electrodes are employed for turbidity detection and pH sensing, respectively, across various water types—including tap water, groundwater, wastewater, saline water, and treated water—to address issues such as environmental drift and measurement inaccuracies. The turbidity sensor was calibrated using a standard six-point method with formazin solutions (0–1064 NTU), whereas pH calibration utilized a three-point approach with NIST-traceable buffer solutions (pH 4, 7, and 10). The results indicate that turbidity measurement errors, initially ranging from 15.75% to 422%, were reduced to below 10% after calibration. Similarly, pH accuracy was significantly improved across all tested water matrices. The system enables real-time data visualization via ThingSpeak, and the implementation of multi-point calibration ensures high data reliability for continuous monitoring. Overall, this approach offers an accurate, efficient, and practical solution for real-time water quality management.
Keywords: Internet of Things; water quality; sensor calibration; real-time monitoring Internet of Things; water quality; sensor calibration; real-time monitoring

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MDPI and ACS Style

Al Drees, M.; Rahma, A.E.; Daffalla, S.; Alsudais, R.; Alsubaie, N.F.; Albrahim, M.; Abdullah Alghanim, H.; Almaghasla, M.I. IoT-Based System for Real-Time Water Quality Monitoring and Advanced Turbidity and pH Sensor Calibration to Improve Accuracy and Reliability Using ThingSpeak. IoT 2026, 7, 42. https://doi.org/10.3390/iot7020042

AMA Style

Al Drees M, Rahma AE, Daffalla S, Alsudais R, Alsubaie NF, Albrahim M, Abdullah Alghanim H, Almaghasla MI. IoT-Based System for Real-Time Water Quality Monitoring and Advanced Turbidity and pH Sensor Calibration to Improve Accuracy and Reliability Using ThingSpeak. IoT. 2026; 7(2):42. https://doi.org/10.3390/iot7020042

Chicago/Turabian Style

Al Drees, Mulhim, Abbas E. Rahma, Samah Daffalla, Rawabi Alsudais, Naser Fathi Alsubaie, Mohammed Albrahim, Hassan Abdullah Alghanim, and Mustafa I. Almaghasla. 2026. "IoT-Based System for Real-Time Water Quality Monitoring and Advanced Turbidity and pH Sensor Calibration to Improve Accuracy and Reliability Using ThingSpeak" IoT 7, no. 2: 42. https://doi.org/10.3390/iot7020042

APA Style

Al Drees, M., Rahma, A. E., Daffalla, S., Alsudais, R., Alsubaie, N. F., Albrahim, M., Abdullah Alghanim, H., & Almaghasla, M. I. (2026). IoT-Based System for Real-Time Water Quality Monitoring and Advanced Turbidity and pH Sensor Calibration to Improve Accuracy and Reliability Using ThingSpeak. IoT, 7(2), 42. https://doi.org/10.3390/iot7020042

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