Smart Water welcomes submissions to the thematic series on the role of big data analytics for realizing intelligent water networks. We are looking for papers that demonstrate how intelligent water network technologies and big data analytics can be used to enhance urban water networks. The research work should demonstrate novel concepts and applications within one or more aspects of the entire network from supply through to distribution and the customer/end-user. Operational, forecasting, customer, finance, economic, engineering, social, science, and asset management dimensions are encouraged. The use of advanced data mining and pattern recognition techniques for providing novel ways to manage urban water resources are requested. Papers that unpack the interaction between water-energy data are particularly encouraged.
Open Call for Papers: Role of Big Data Analytics for Realizing Intelligent Water Networks
Articles
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A design and implementation of low-power ultrasonic water meter
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Leak detection in water distribution networks: an introductory overview
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Experimental and numerical investigations of primary flow patterns and mixing in laboratory meandering channel
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Calibrating and validating a combined accumulation and mobilisation model for water distribution system discolouration using particle swarm optimisation
About the Editor-in-chief
The Editor-in-Chief of Smart Water, Joong Hoon "Jay" Kim, is a professor at Korea University. He specializes in water engineering and hydroinformatics, and is a member of IWA and IEEE. His research interests include applying optimization and machine learning techniques to water management systems such as smart water management systems and micro water grid systems in smart cities, real-time management of urban water systems involving smart monitoring, telemetered systems, and sensor networks.
See the full editorial board.
Aims and Scope
Smart Water is a peer-reviewed open access journal published under the SpringerOpen brand. The journal covers areas like Smart City and Smart Water Issues, next-generation Smart Water Management, Artificial Intelligence for Smart Water, and others.
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We offer a free open access support service to make it easier for you to discover and apply for article-processing charge (APC) funding.
Learn more here.
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COVID-19 and impact on peer review
As a result of the significant disruption that is being caused by the COVID-19 pandemic we are very aware that many researchers will have difficulty in meeting the timelines associated with our peer review process during normal times. Please do let us know if you need additional time. Our systems will continue to remind you of the original timelines but we intend to be highly flexible at this time.
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Affiliated with
@qua – Smart ICT for Water
Annual Journal Metrics
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Speed
80 days to first decision for reviewed manuscripts only
61 days to first decision for all manuscripts
153 days from submission to acceptance
27 days from acceptance to publicationUsage
68,279 downloads
21 Altmetric mentions
- ISSN: 2198-2619 (electronic)
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