articleScientific ReportsMar 29, 2024GOLD OA

Reliable water quality prediction and parametric analysis using explainable AI models

Vellore Institute of Technology University · Shiv Nadar University · +2 more institutions

PubMed
Indexed incrossrefdoajpubmed

Abstract

The consumption of water constitutes the physical health of most of the living species and hence management of its purity and quality is extremely essential as contaminated water has to potential to create adverse health and environmental consequences. This creates the dire necessity to measure, control and monitor the quality of water. The primary contaminant present in water is Total Dissolved Solids (TDS), which is hard to filter out. There are various substances apart from mere solids such as potassium, sodium, chlorides, lead, nitrate, cadmium, arsenic and other pollutants. The proposed work aims to provide the automation of water quality estimation through Artificial Intelligence and uses Explainable…

Citation impact

117
total citations
FWCI
21.78
Percentile
100%
References
67
Citations per year

Authors

6

Topics & keywords

Keywords
  • Decision tree
  • Support vector machine
  • Random forest
  • Computer science
  • Artificial intelligence
  • Water quality
  • Machine learning
  • Naive Bayes classifier
UN Sustainable Development Goals
  • Clean water and sanitation
No related works found for this paper.