Development of AI-Based Predictive Models for Water Quality in India

Development of AI-based predictive models for water quality in India

Objective

• To predict the water quality at any location, depth and time in India. This would be accomplished by analysing a range of parameters using AI and an innovative mode of online/web/mobile interface.

Description

• We will collect all the available data on groundwater quality on the basis of various contaminants in India from various sources for the last 20 years. Using state-of-art data science platforms we will clean and extract the data on water quality and convert it to a geospatial format. Then, we will collect and transform remote-sensing and survey data on the climate, geology, hydrogeology(aquifer), land use, urbanization, location of water bodies, industries, agriculture, and other associated data on which water quality usually depends for the last 20 year. We will then train the machine learning models to predict spatially and temporally the occurrence of a hotspot in groundwater quality parameters.

Impact

• Social Impacts: Improved health and wellbeing of the current and future population, reduced poverty and inequality, and improved performance in schools by pupils. Health impacts: Reduction of water-related illnesses and premature deaths, and reduction of chronic diseases linked to water contamination such as cancer, cardiovascular, endocrinal, and neurological diseases. Environmental Impacts: Reduced water, soil and food pollution of groundwater and surface water bodies, and improved water quality leads to conservation of natural ecosystems. Economic impacts: Cost-effective treatments for water remediation which leads to local community empowerment and employment opportunities.