ARDUINO-BASED REAL-TIME MONITORING SYSTEM FOR WATER HARDNESS AND PH.
Ismailov Mirhalil Agzamovich,
Professor of Automation and Control of Technological Processes, PhD, National Research University "TIIAME", Department of "Automation and Control of Technological Processes"
Abdunazarov G'olibjon G'ayrat o'g'li
Master's student, National Research University "TIIAME", Department of "Automation and Control of Technological Processes"
Mansurov Bekzod Doniyor o'g'li
Master's student, National Research University "TIIAME", Department of "Automation and Control of Technological Processes"
Keywords: water hardness, pH monitoring, Arduino, SCADA, chemical treatment.
Abstract
In the current era of industrial development, the effective use of water resources and control of their quality are urgent tasks. In this study, an automatic system based on an Arduino microcontroller was developed that monitors water hardness and pH levels in real time during the chemical treatment of industrial water. The goal is to optimize the rational use of resources while reducing human error. The hardware part of the system consists of components such as sensors, a microcontroller, and a real-time display module, while the software part is written in the Arduino IDE environment. Initially, prototype tests were conducted using Fritzing simulation and laboratory conditions. The results show that the developed system can accurately record changes in water hardness and pH: the difference between the measured pH values and laboratory values did not exceed ±0.2, and the results for TDS (total dissolved solids) were observed within 5% of the reference values. This accuracy allows for better control and management of the water treatment process. The proposed system contributes to the sustainable use of water in industry through automated control based on real-time data.References
1. Turobjonov, S., Tursunov, T., & Pulatov, X. (2010). Wastewater Treatment Technology. Musiqa Publishing House, Tashkent.
2. Buriyev, E. S., & Yakubov, K. F. (2014). Wastewater Discharge Networks. Cholpon Publishing House, Tashkent.
3. Musayev, M. N. (2011). Industrial Waste Purification Technology. National Society of Philosophers of Uzbekistan, Tashkent.
4. Forhad, H. M., Uddin, M. R., Chakrovorty, R. S., et al. (2024). IoT based real-time water quality monitoring system in water treatment plants (WTPs). Heliyon, 10(23), e40746. DOI: 10.1016/j.heliyon.2024.e40746
5. El-Shafeiy, E., Alsabaan, M., Ibrahim, M. I., & Elwahsh, H. (2023). Real-Time Anomaly Detection for Water Quality Sensor Monitoring Based on Multivariate Deep Learning Technique. Sensors, 23(20), 8613. DOI: 10.3390/s23208613
6. Dwarakanath, B., Kalpana Devi, P., Anandan, R. K., et al. (2023). Smart IoT-based water treatment with a Supervisory Control and Data Acquisition (SCADA) system process. Journal of Water Reuse and Desalination, 13(3), 411–427. DOI: 10.2166/wrd.2023.052
7. Al-Ali, A. R., Zualkernan, I. A., & Aloul, F. (2019). IoT-based water monitoring system. Sensors, 19(21), 4655.
8. Lee, Y., Kumar, A., & Srivastava, S. (2021). Real-time monitoring of water parameters using embedded systems. IEEE Access, 9, 45342–45355.














