Water Quality Estimation and Anomaly Detection: A Review





Water quality, Anomaly detection, Water management systems, Water analytics, Water distribution networks, Machine learning


Critical infrastructures that provide irreplaceable services are systems that contain industrial control systems (ICS) that can cause great economic losses, security vulnerabilities and disruption of public order when the information in it is corrupted. These ICSs, which were previously isolated, have now become systems that contain online sensors, wireless networks and artificial intelligence technologies. This situation has also increased the scope of attacks by malicious people who intend to carry out industrial espionage and sabotage these systems. In this study, water quality estimation systems and anomaly detection are comprehensively examined. In this direction, the statistics of the studies in the literature, the methods for water quality anomaly detection, the existing data sets, and the difficulties encountered in the water systems to achieve better water management are discussed. Principle findings of this research can be summarized as follows: (i) new methodologies and architectures have improved water quality assessment through anomaly detection, (ii) different datasets including multi-modal information have been presented, and (iii) remaining challenges and prospects have been investigated.


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How to Cite

D. Balta, S. Balta Kaç, M. Balta, and S. Eken, “Water Quality Estimation and Anomaly Detection: A Review”, EAI Endorsed Trans IoT, vol. 9, no. 4, p. e2, Oct. 2023.

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