Abstract
Water distribution systems (WDSs) are large complex infrastructures made from pipes, valves, pumps, tanks and other elements designed and erected to transport water of sufficient quality from water sources to consumers. The amount of the above elements, which can reach up to tens of thousands of links and junctions, their frequently wide spatial dispersion and the WDS characteristic of being very dynamic structures make the management of real WDSs a complex problem [1–4]. However, although the main objective is to supply water in the quantity and quality required, other requirements are essential, namely maintaining conditions far from failure scenarios [5,6], ability to quickly detect sources of contamination intrusion [7,8], minimization of leaks [9,10], etc.
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Francés-Chust, J., Izquierdo, J., Montalvo, I. (2019). LoRaWan for Smarter Management of Water Network: From metering to data analysis. In: Beyerer, J., Kühnert, C., Niggemann, O. (eds) Machine Learning for Cyber Physical Systems. Technologien für die intelligente Automation, vol 9. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-58485-9_15
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DOI: https://doi.org/10.1007/978-3-662-58485-9_15
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