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Optimizing Water Resources With IoT and ML: A Water Management System
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Author(s): Rakhi Chauhan (Chitkara University, India), Neera Batra (Department of CSE, Maratha Mandal Engineering College, Maharishi Markandeshwar University (Deemed), Mullana, India), Sonali Goyal (Department of CSE, Maratha Mandal Engineering College, Maharishi Markandeshwar University (Deemed), Mullana, India)and Amandeep Kaur (Department of CSE, Maratha Mandal Engineering College, Maharishi Markandeshwar University (Deemed), Mullana, India)
Copyright: 2024
Pages: 16
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.ch005
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Abstract
The necessity for effective water management systems has increased recently due to the rising demand for water resources and the negative effects of climate change. This chapter gives a thorough investigation into the installation of a water management system (WMS) using machine learning (ML) and the internet of things (IoT) technologies to address these issues. The proposed WMS makes use of internet of things (IoT)-enabled sensors placed throughout various water infrastructure sites, including reservoirs, water supply networks, and pipelines to gather real-time information on critical variables like weather conditions, water quality, etc. The acquired data is then subjected to sophisticated ML algorithms to optimize water use and distribution. The WMS described in this chapter serves as an example of how ML and IoT have the potential to fundamentally alter current approaches to water management.
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