Intelligent IoT-Based Water Quality Monitoring and Predictive Analysis Using Machine Learning
DOI:
https://doi.org/10.64229/dnq1tb95Keywords:
IoT, Machine Learning, Water Quality Monitoring, Water Quality Index (WQI), Sustainable Development Goal 6 (SDG 6), Predictive AnalyticsAbstract
This paper proposes a scalable and intelligent system integrating Internet of Things (IoT) technologies with advanced machine learning (ML) algorithms for real-time water quality monitoring and predictive analysis. The system utilizes low-cost and reliable sensors deployed on microcontroller platforms such as ESP32 and NodeMCU to continuously collect vital water parameters, including pH, turbidity, temperature, dissolved oxygen, and total dissolved solids (TDS). Sensor data is transmitted via wireless communication protocols to cloud platforms like ThingSpeak and AWS IoT for centralized storage and preprocessing. Machine learning models, including Random Forest, Support Vector Machines (SVM), Extreme Gradient Boosting (XGBoost), and Long Short-Term Memory (LSTM) networks, are trained on historical data to forecast parameter fluctuations, detect anomalies, and compute the Water Quality Index (WQI), providing a standardized quality assessment metric. The system’s automated alert and visualization layer delivers real-time dashboards and warning notifications to stakeholders, enabling timely responses to contamination events. Experimental results on self-collected IoT sensor data and benchmark public datasets demonstrate high predictive accuracy, precision, and recall, confirming the framework’s suitability for continuous environmental surveillance. This approach addresses limitations of traditional costly and time-consuming laboratory tests by offering affordable, scalable, and adaptive monitoring, supporting sustainable water resource management. Future work will explore additional sensor integration, enhanced deep learning architectures, and economic feasibility studies for large-scale implementation. The proposed framework contributes significantly to environmental protection, public health safeguarding, and intelligent infrastructure development aligned with Sustainable Development Goals (SDG 6), fostering smarter and safer water ecosystems.
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