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A review on water consumption reducing technology, IoT and AI for household applications

Deepak Watvisave, Shridhar Kedar, Ajit Bhosale, Harish Shinde, Pravin Mane

Abstract


Industrialization and increased population have increased water demand enormously but climate change and depleting water resources have created water stress in many countries all over the world. At the same time development of internet of things (IOT) based technologies is happening very fast. This paper reviews research works in the area of water consumption, water quality analysis and water demand forecasting using mathematical models, water reduction technologies. Since IOT is relatively new, web articles and blogs are seen to be discussing an application of IOT for water consumption reduction, however full fledged research articles are missing. Hence a scope of IOT in water consumption pattern analysis and thereby reduction in water consumption is discussed in this paper. This study thoroughly analyzes the water consumption pattern that varies as per income groups, industries, gender, age, socio-economic status. Study reveals that water quality also affects water consumption and spread of diseases. Mathematical models were studied so as to understand the effectiveness of these models in water consumption forecasting that helps in better management. Study has identified the shortcomings like incorrect approach, inadequate data, and incorrect method of data collection, less or no use of scientific methodologies for water consumption determination and less technological use. Study suggests the use of advanced technologies like internet of things, sensors can help in real time data collection and monitoring of water equipment with standardization of methods. It concludes with comments on the possibility of IOT/AI integration for reduction of water in domestic settings.


Keywords


water consumption; water stress; smart technology; sanitation; water quality; AI in water conservation

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DOI: https://doi.org/10.32629/jai.v7i5.1557

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Copyright (c) 2024 Deepak Watvisave, Shridhar Kedar, Ajit Bhosale, Harish Shinde, Pravin Mane

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