IoT Based Indian River Water Quality Prediction Model

Author(s)	Prof. Abha Pathak, Mr. Omkar Hulawale, Mr. Ajinkya Lahane, Mr. Tushar Aswar, Mr. Abhishek Ganore
Country	India
Abstract	This study aims to create IoT based model that can monitor and predict quality of river water in India . It will use real time data , machine learning and deep learning techinques .The system uses sensors for pH, temperature, dissolved oxygen,and turbidity, connected to an microcontroller for data collection. The gathered data is sent to a cloud database for storage and processing. A machine learning model, based on the best fitted algorithm, will be trained to predict the Water Quality Index (WQI) and determine if the water is safe or polluted. This model will offers an effective, low-cost, and scalable way to monitor the environment. The proposed system will accurately predicts water quality, allowing for continues , low cost monitoring and early detection of warnings. By integrating IoT with machine learning provides reliable scalable solution for water monitoring. This combination will help agencies for monitor and respond quickly to pollution warnings and supports sustainable water quality prediction model.
Keywords	Internet of Things, Water Quality, Prediction Model, Machine Learning, Sensors, River Pollution.
Field	Engineering
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-12-28
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.60913

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