Revolutionizing Water Quality Monitoring with Artificial Intelligence: A Systematic Review

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Revolutionizing Water Quality Monitoring with Artificial Intelligence: A Systematic Review

Traditional water quality monitoring methods face significant limitations, including delayed data acquisition, high operational costs, and inadequate spatial and temporal resolution, which hinder timely responses to contamination events. This systematic review addresses these gaps by evaluating the...

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Bibliographic Details
Main Authors:	Mahmoud Saleh Al-Khafaji, Layth Abdulameer, Muthanna M. A. AL-Shammari, Najah M. L. Al Maimuri, Anmar Dulaimi, Dhiya Al‑Jumeily
Format:	Article
Language:	English
Published:	Engiscience Publisher 2025-06-01
Series:	Journal of Studies in Science and Engineering
Subjects:	Artificial Intelligence Machine Learning Real-time monitoring Smart water management Water quality monitoring
Online Access:	https://engiscience.com/index.php/josse/article/view/633
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