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signiﬁcance of having a solid cybersecurity architecture in order to protect sensitive data
and control systems from the possibility of cyber-attacks.
In conclusion, the incorporation of Machine Learning and the Internet of Things into
desalination systems has the potential to revolutionize the method by which freshwater
is created from salty sources. This might have a signiﬁcant impact on the global water
supply. These technologies offer a path toward more sustainable, efﬁcient, and reliable
desalination processes by enabling real-time monitoring, predictive maintenance, and
data-driven decision-making. This contributes to the relief of water scarcity concerns on a
worldwide scale. This investigation offers important takeaways for researchers,
engineers, and politicians who are interested in putting the potential of machine learning
and the internet of things to use in the desalination industry.
Key words: Desalination; IoT; Machine learning; water; Sensors

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