P. Amanatidis, E. Lyratzis, V. Angelopoulos, E. Kouloumpris, E. Skaperdas, N. Bassiliades, I. Vlahavas, F. Maris, D. Emmanouloudis, D. Karampatzakis, “Intelligent Water Management through Edge-Enabled IoT, AI, and Big Data Technologies”, IoT, Vol. 7, No 1:5, 2026.
In the 21st century, Urbanization, population growth, and climate change have created significant problems in water resource management. Recent advancements in technologies such as Internet of Things (IoT), Edge Computing (EC), Artificial Intelligence (AI), and Big Data Analytics (BDA) are changing the operations of the water resource management systems. In this study, we present a systematic review, highlighting the contributions of these technologies in water management systems. More specifically, we highlight the IoT and EC water monitoring systems that enable real-time sensing of water quality and consumption. In addition, AI methods for anomaly detection and predictive maintenance are reviewed, focusing on water demand forecasting. BDA methods are also discussed, highlighting their ability to integrate data from different data sources, such as sensors and historical data. Additionally, a discussion is provided of how Water management systems could enhance sustainability, resilience, and efficiency by combining big data, IoT, EC, and AI. Lastly, future directions are outlined regarding how state-of-the-art technologies may further support efficient water resources management.
