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Introduction to ML and IoT for Water Management
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Author(s): Nalluri Poojitha (Sri Padmavati Mahila Visvavidyalayam, India), B. Ramya Kuber (Sri Padmavati Mahila Visvavidyalayam, India)and Ambati Vanshika (Sri Padmavati Mahila Visvavidyalayam, India)
Copyright: 2024
Pages: 24
Source title:
Innovations in Machine Learning and IoT for Water Management
Source Author(s)/Editor(s): Abhishek Kumar (Chandigarh University, India), Arun Lal Srivastav (Chitkara University, India), Ashutosh Kumar Dubey (University of Castilla-La Mancha, Spain), Vishal Dutt (AVN Innovations Pvt. Ltd., India)and Narayan Vyas (AVN Innovations Pvt. Ltd., India)
DOI: 10.4018/979-8-3693-1194-3.ch001
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Abstract
Planning, regulating, and sustainably using water supplies to meet various demands are all critical to managing water resources. A growing water shortage puts ecosystem health and mortal needs at risk, prompting creative solutions. The main objective is to investigate how ML, along with IoT synergies, optimise resource allocation, improve predictions for water distribution, improve quality surveillance, and identify leaks, ultimately promoting sustainability as well as informed decision-making. The study highlighted the significant potential of the ML-IoT fusion in transforming water management practises. This is accomplished by undertaking a thorough analysis of the current literature, which is supported by actual case studies. This investigation will ultimately shed light on the bright future of water resource management, wherein insights based on data as well as cutting-edge technology will pave the way for a more secure and sustainable water supply.
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