Abstract Providing fresh and clean water to all is the objective of Sustainable Development Goal 6. Consuming clean water improves health for all living beings worldwide. Therefore, accurately estimating the water quality and classifying the type of water (i.e. whether it is used for potable purposes or not) based on physicochemical parameters is considered a challenging issue due to the dynamic nature of water quality data, the selection of physical or data-driven models used to estimate the wa
Data driven water quality assessment using machine learning and synthetic data generation
N D S S Kiran Relangi·Vinod Yadav·D. Venkata Naga Raju·P.J. Raju·M Vishnu Vardhana Rao·Krishna Kant Pandey
