Intelligent IoT System for Continuous Water Quality Monitoring

Traditional water quality monitoring systems (WQMS) are often outdated and lack the intelligence to provide real-time analysis and alerts. This paper proposes a smart water quality monitoring system using a Raspberry Pi as the control unit, integrated with various sensors (pH, TDS, temperature, turbidity, and flow) for data collection. The system uses GSM and WiFi modules for data transmission to a cloud database, where machine learning algorithms analyze the data, providing alerts and predictions. Currently, this project is in the development phase. The data is collected successfully from a single water source and displayed on the Raspberry Pi screen, providing real-time monitoring of key water quality parameters. The next phase involves the integration of AI and machine learning, which is still under development. This will enhance the system's ability to process data, detect anomalies, and make accurate predictions about water quality.