Vlastimil Slany, Eva Krcalova, Jiri Balej, Martin Zach, Tereza Kucova, Michal Prauzek, Radek Martinek
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引用次数: 0
Abstract
The treatment, monitoring and distribution of drinking water is an integral component of critical national infrastructure and therefore places continually increasing demands on Water Distribution Networks (WDNs). This domain and its sub-sectors face several major problems, namely climate change and drought-induced rises in water consumption from surface and underground reservoirs, in addition to the existence of significant water leaks during transmission to end users. These problems can be addressed by deploying Internet of Things (IoT) systems and smart distribution grids to improve the efficiency and safety of water distribution and to easily detect leaks or unauthorised consumption. This type of smart grid is referred to as Smart Water-IoT (SW-IoT), a novel, comprehensive water management concept. This review article discusses the application of IoT components and artificial intelligence (AI) in five basic categories (agriculture, water treatment, security, water distribution networks and wastewater). Relevant legislation in the EU, USA, Canada, Australia, China, Japan and India is also reviewed. In this context, the mandatory implementation of smart remote data reading solutions into the critical infrastructure of EU member states is outlined to highlight the importance of responsible water handling. The article provides a detailed analysis of the current research in SW-IoT and defines the main research challenges for future investigation.
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.