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All Journal Journal of Electrical Engineering and Computer (JEECOM)
Eirene Korobu
Universitas Katolik De La Salle Manado
Control & Systems Engineering Electrical & Electronics Engineering Energy

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Development Of An IoT-Based Irrigation Water Quality Monitoring System Using The CCME WQI Method for Agricultural Modernization Brigitha Raco; Ryan Laksmana Singgeta; Eirene Korobu
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.13750

Abstract

The degradation of irrigation water quality presents a critical challenge for sustainable agriculture, particularly under increasing hydrometeorological pressure. This study developed an Internet of Things (IoT)–based monitoring system and applied the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) to evaluate temporal variations in irrigation water quality.The system integrates pH, water temperature, total dissolved solids (TDS), and turbidity sensors with an ESP32 microcontroller, enabling real-time data transmission to a cloud-based platform. Water quality assessment was conducted from August to December using CCME WQI, with objectives defined based on national regulations and internationally recognized guidelines.The results reveal a progressive decline in irrigation water quality throughout the monitoring period. CCME WQI values decreased from 70.24 (Fair) in August to 32.28 (Poor) in December, indicating increasing frequency and severity of guideline exceedances. Turbidity was identified as the dominant contributor to water quality degradation, particularly during rainfall events, followed by episodic pH reductions and diurnal temperature variability. In contrast, TDS remained stable and consistently below threshold values.The integration of high-resolution IoT monitoring with the CCME WQI framework provides a reliable and objective approach for continuous irrigation water quality assessment. This method effectively captures temporal dynamics and supports early identification of critical degradation periods, offering a practical basis for adaptive irrigation water management.
Co-Authors Brigitha Raco, Brigitha Singgeta, Ryan Laksmana