MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202541017177 A) filed by Srinith Kannan; Bharat A S; Kavinkumar R; and Krishnaraj R on February 27, 2025, for Iot-Based Smart Water Quality Monitoring And Prediction System.
Inventors include Srinith Kannan; Bharat A S Number; Kavinkumar R; and Krishnaraj R.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: Water quality monitoring is crucial for ensuring safe and clean water for drinking, agriculture, and industrial applications. Traditional water testing methods require manual sampling, making real-time monitoring inefficient. This project introduces an IoT-based Smart Water Quality Monitoring and PredictionSystem that continuously measures key water parameters, including pH, Total Dissolved Solids (TDS), turbidity, and temperature, using an ESP32 microcontroller. The collected data is transmitted to Firebase, which serves as both a storage and a real-time database. A user-friendly dashboard displays live readings, allowing users to monitor water quality remotely and make informed decisions. Additionally, a UV disinfection lamp is integrated into the system to enhance water purification when contamination levels exceed safe thresholds. To improve water quality assessment, the system incorporates a machine learning-based predictive model that analyzes historical trends and forecasts potential changes in water quality. This predictive capability enables proactive measures to prevent contamination before it reaches critical levels. The combination of IoT technologies ensures automated monitoring, reducing the need for manual intervention. The system is suitable for various applications, including residential water supply, industrial processes, and municipal water management, ensuring continuous and reliable water quality assessment. By utilizing Firebase for real-time data storage and visualization, this system eliminates the need for complex cloud storage solutions while providing an efficient and interactive monitoring experience. The integration of real-time sensing, predictive analytics, and automatic disinfection makes this a cost effective, scalable, and smart solution for water quality management. Its ability to deliver instant updates and insights through a web-based dashboard enhances accessibility and usability for both individuals and organizations focused on water safety. Keywords: IoT, Water Quality Monitoring, ESP32, pH Sensor, TDS Sensor, Turbidity Sensor, Machine Learning, UV Disinfection, Firebase, Smart Dashboard, Water Safety.
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