Draft:Intelligent Water System
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This article, Draft:Intelligent Water System, has recently been created via the Articles for creation process. Please check to see if the reviewer has accidentally left this template after accepting the draft and take appropriate action as necessary.
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An Intelligent Water System (IWS)[1][2][3] is an integrated water management platform that employs networks of sensors, actuators, communications infrastructure, and automated controls to to monitor, manage, and optimize water distribution and treatment. This practice is often referred to as smart water management[4][5][6] and is reflective of the Digital Transformation in Water Utilities.[6][4] This transformation and IWSs build on advances in IoT technology and Artificial Intelligence; aiming to enhance operational efficiency, provide predictive maintenance guidance, and conserve resources. However these same technologies incur vulnerabilities operators must be aware of, and pro-actively safeguard from cyber-incidents.[7]
Concerns Regarding Cyberbiosecurity
[edit | edit source]IWSs being networked, and critical components of modern infrastructure; cyberbiosecurity is a major concern.[4][8][9][10][11] Increased reliance on networked devices for monitoring and control necessitates reliable methods to detect anomalies indicating potential cyber-incidents[12][13] and/or regulatory violations[14]. Facilities choose to adopt these technologies and associated risks to achieve goals such as improving operational efficiency, cost reduction, elevating public health standards, supporting smart irrigation practices, and capturing deeper insights to support achieving these aforementioned goals through data analysis.[15]
Artificial Intelligence in Intelligent Water Systems
[edit | edit source]Artificial Intelligence (AI) solutions have emerged as an approach to secure IWSs, in addition to other critical infrastructure such as nuclear plants, smart grids and smart farms.[4] In water treatment and management applications, AI is used to support informed decision making and anomaly detection that could indicate cyber-incidents.[4][9] Researchers have developed comprehensive models intended to forecast water requirements & optimize system management to meet demand while minimizing resource use; with some including detection capabilities aiding in securing IWSs.[9][16] AI can also provide greater insights to policymakers responsible for regulations affecting water quality, that IWSs must abide by.[4] This practice offers researchers and policymakers the ability to understand the effects of past regulatory changes and improve future policy decisions.[17][18][19]
References
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