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February 14, 20260 citationsOpen Access

Internet of Things-Enabled Water Quality Monitoring: Technologies, Applications, and Future Perspectives

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FPFittrie Meyllianawaty Pratiwy

Key Points

  • This research aims to evaluate the impact of IoT technologies on water quality monitoring, focusing on key indicators like pH, temperature, and dissolved oxygen.
  • Systematic literature review from 2015 to 2025
  • Analysis of sensor types and data transmission methods
  • Assessment of measurement accuracy and parameter stability pre- and post-IoT implementation
  • Evaluation of adaptive control algorithms like fuzzy logic
  • IoT-based systems improve measurement accuracy by over 95%
  • Parameter fluctuations reduced: pH maintained within ±0.2 units, temperature within ±0.4°C, DO within ±0.3 mg/L
  • Adaptive control algorithms effectively maintain aquatic environmental stability

Abstract

Abstract Sudden and unnoticed changes in water quality continue to pose serious challenges in water resource management, aquaculture production, and clean water treatment systems. Key indicators such as pH, temperature, and dissolved oxygen (DO) are highly susceptible to environmental fluctuations, making accurate and continuous monitoring indispensable. Conventional methods based on manual sampling often produce discrete and highly fluctuating data. The development of Internet of Things (IoT) technology offers an effective solution through real-time monitoring systems capable of measuring, analyzing, and automatically controlling water quality parameters. This study presents a systematic literature review focusing on the application of IoT in monitoring pH, temperature, and DO between 2015 and 2025. The analysis covers sensor types, data transmission methods, measurement accuracy, and parameter stability before and after IoT implementation. The review results indicate that IoT-based systems improve measurement accuracy by more than 95% and significantly reduce parameter fluctuations maintaining pH within ±0.2 units, temperature within ±0.4°C, and DO within ±0.3 mg/L compared to manual methods. The implementation of adaptive control algorithms such as fuzzy logic and automatic calibration has also proven effective in maintaining aquatic environmental stability. Therefore, IoT serves not only as a monitoring tool but also as a dynamic control mechanism capable of continuously maintaining water conditions within optimal ranges.

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Cite This Study

Fittrie Meyllianawaty Pratiwy (2026) studied this question.

synapsesocial.com/papers/699011712ccff479cfe580f3https://doi.org/10.5281/zenodo.18618677
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