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Digital Water: Artificial Intelligence and Soft Computing Applications for Drinking Water Quality Assessment by Gyan Chhipi-Shrestha; Haroon R. Mian; Saeed Mohammadiun; Manuel Rodriguez; Kasun Hewage; Rehan Sadiq is a Engineering article available to read on EtoBox.

Water quality deterioration in drinking water systems (i.e., system failure) causing serious outbreaks have frequently been happening around the world. These failures can be predicted through a real-time drinking water quality monitoring system for timely actions. Although Supervisory Control and Data Acquisition (SCADA) has been commonly used for this purpose, this system suffers considerable limitations, such as the scalability of sensors, lack of predictive ability, and increased burden on operators overwhelmed by superfluous notifications. Proficient artificial intelligence & soft computing (AI & SC) techniques and cloud Internet of Things (IoT) may significantly reduce the reliance on operators and eventually improve system operations. This study critically reviewed the literature published from 2000 to 2020 to evaluate AI & SC applications' trends in drinking water quality management while developing a roadmap for autonomous digital water quality management. The investigation reveals that AI & SC were primarily used for assessing drinking and surface water quality. These techniques were largely applied to effectively predict, evaluate, and control water quality. AI & SC were

It is typically read by researchers, students, and practitioners in Engineering.

Author
Gyan Chhipi-Shrestha; Haroon R. Mian; Saeed Mohammadiun; Manuel Rodriguez; Kasun Hewage; Rehan Sadiq
Publisher
Springer Science and Business Media LLC
Published
2023
Language
EN
Field
Engineering (Physical Sciences)