Development of a Real-Time Water Quality Monitoring System Using Internet of Things (IoT) Technology: A Case Study of the Oxidation Ditch Wastewater Treatment System at Bamrasnaradura Infectious Diseases Institute
Article Sidebar
Main Article Content
Abstract
Oxidation Ditch wastewater treatment systems are biological treatment systems that play an important role in maintaining effluent quality in healthcare facilities. However, conventional water quality monitoring based on periodic sampling and laboratory analysis has limitations in providing continuous surveillance and timely detection of abnormal conditions.
This study aimed to (1) develop a real-time water quality monitoring system using Internet of Things (IoT) technology for the Oxidation Ditch wastewater treatment system at Bamrasnaradura Infectious Diseases Institute, (2) evaluate the performance of the developed system, and (3) assess its potential to support wastewater treatment management.
This research and development study was conducted in four phases: problem analysis and system design; equipment development and installation; system testing and calibration; and field evaluation. The developed system consisted of four architectural layers: a sensing layer, a data communication layer using Modbus RS485, a processing layer using a Programmable Logic Controller (PLC), and a data storage and visualization layer using Cloud technology through a Human–Machine Interface (HMI) and dashboard. Data were continuously collected from October 2025 to May 2026 and compared with laboratory analytical results to evaluate the agreement and measurement errors of the IoT system.
The developed system successfully transmitted and displayed water quality data in real time, with data completeness of 98.26% and system availability of 99.89%. Comparison with laboratory results showed that pH measurements had a mean absolute error (MAE) of 0.10 pH units and a mean absolute percentage error (MAPE) of 1.35%; however, the correlation was not statistically significant (r = 0.478, p = 0.231). In contrast, TDS measurements showed a very strong positive correlation with laboratory results (r = 0.968, p < 0.001) and a MAPE of 2.88%. Field evaluation demonstrated that the system enabled continuous monitoring of water quality trends and system operating status, while supporting real-time alerts and data-informed wastewater treatment control.
The developed IoT-based monitoring system demonstrated potential for continuous water quality surveillance and for supporting wastewater treatment management in healthcare facilities. The system may also serve as a technological foundation for the development of smart environmental monitoring systems in healthcare settings.
Article Details
References
Medical Engineering Division. Manual for maintenance of wastewater treatment systems in hospitals. Nonthaburi: Department of Health Service Support, Ministry of Public Health; 2016. (in Thai)
Thai MOOC. Basic Internet of Things (IoTs) [Internet]. 2023 [cited 2026 Jul 20]. Available from: https://thaimooc.ac.th/courses/HU00193 (in Thai)
Forhad HM, Uddin MR, Chakrovorty RS, Ruhul AM, Faruk HM, Kamruzzaman S, et al. IoT-based real-time water quality monitoring system in water treatment plants (WTPs). Heliyon 2024; 10: e40746. doi: 10.1016/j.heliyon.2024.e40746.
Ansari SA, Vidyarthi VK. Use of Internet of Things in water resources applications: challenges and future directions: a critical review. Discov Internet Things 2025; 5: 96. doi: 10.1007/s43926-025-00193-7.
Li R, Yang X, Lu Z, Chen C. Research on water quality monitoring system based on IoT technology. In: 2019 4th International Conference on Control, Robotics and Cybernetics (CRC); 2019 Sep 27-29; Tokyo, Japan. Piscataway (NJ): IEEE; 2019. p.321-324.
Almetwally SA, Hassan MK, Mourad MH. Real time internet of things (IoT) based water quality management system. Procedia CIRP 2020; 91: 478-485. doi: 10.1016/j.procir.2020.03.107.
Ramadan MN, Ali MA, Khoo SY, Alkhedher M, Alherbawi M. Real-time IoT-powered AI system for monitoring and forecasting of air pollution in industrial environment. Ecotoxicol Environ Saf 2024; 283: 116856.
Zulkifli CZ, Garfan S, Talal M, Alamoodi AH, Alamleh A, Ahmaro IY, et al. IoT-based water monitoring systems: a systematic review. Water 2022; 14(22): 3621. doi: 10.3390/w14223621.
Kamyab H, Khademi T, Chelliapan S, Saberika - marposhti M, Rezania S, Yusuf M, et al. The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management. Res Eng 2023; 20: 101566. doi: 10.1016/j.rineng.2023.101566.
El-Shafeiy E, Alsabaan M, Ibrahem MI, Elwahsh H. Real-time anomaly detection for water quality sensor monitoring based on multivariate deep learning technique. Sensors 2023; 23(20): 8613. doi: 10.3390/s23208613.
Ministry of Natural Resources and Environment. Notification of the Ministry of Natural Resources and Environment on designation of buildings as pollution sources subject to control under Section 80 of the Enhancement and Conservation of National Environmental Quality Act B.E. 2535 (1992), B.E. 2567 (2024). Royal Thai Government Gazette. 2024; 141(Special Part 233 Ngor): 1-6. (in Thai)
Ministry of Natural Resources and Environment. Notification of the Ministry of Natural Resources and Environment on effluent discharge standards for certain types and sizes of buildings, B.E. 2567 (2024). Royal Thai Government Gazette. 2024; 141(Special Part 233 Ngor): 7-15. (in Thai)
