Predictive Modeling of Water Quality in Indian Rivers: A Machine Learning Approach for Sustainable Resource Management

Bela Shrimali, Shivangi Surati, Aditya Patel, Rohit Kansagara

2024

Abstract

Despite water being an essential constituent of life, water pollution is increased because of sewage, pesticides, and industrial waste. Polluted water creates a negative influence on the ecosystem, affecting not only human life but also aquatic life. River water pollution is one of the major concerns of recent days in emerging countries like India, Bhutan, Bangladesh, and many more. Hence, river water quality prediction becomes essential for sustainable resource management. In this paper, after describing various parameters to monitor water quality, an innovative Machine Learning (ML)-driven approach for prediction of the water quality of Indian rivers, is presented. The research involves the implementation of various machine learning models to predict diverse water quality parameters of the Indian rivers. These models are trained to address the intricate challenges associated with comprehending the complex dynamics of water quality. The efficacy of the trained models is experimented through evaluations of a huge dataset, comprising water samples from various Indian rivers. The outcomes of this research not only predict and monitor the accuracy of water quality through a robust framework but also contribute valuable insights and tools for sustainable resource management for Indian rivers.

Paper Citation

in Harvard Style

Shrimali B., Surati S., Patel A. and Kansagara R. (2024). Predictive Modeling of Water Quality in Indian Rivers: A Machine Learning Approach for Sustainable Resource Management. In Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com; ISBN 978-989-758-739-9, SciTePress, pages 165-174. DOI: 10.5220/0013303800004646

in Bibtex Style

@conference{ic3com24,
author={Bela Shrimali and Shivangi Surati and Aditya Patel and Rohit Kansagara},
title={Predictive Modeling of Water Quality in Indian Rivers: A Machine Learning Approach for Sustainable Resource Management},
booktitle={Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com},
year={2024},
pages={165-174},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013303800004646},
isbn={978-989-758-739-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com
TI - Predictive Modeling of Water Quality in Indian Rivers: A Machine Learning Approach for Sustainable Resource Management
SN - 978-989-758-739-9
AU - Shrimali B.
AU - Surati S.
AU - Patel A.
AU - Kansagara R.
PY - 2024
SP - 165
EP - 174
DO - 10.5220/0013303800004646
PB - SciTePress