Syu, W.-J.W.-J.SyuTSUN-KUO CHANGSHU-YUAN PAN2021-02-042021-02-042020https://www.scopus.com/inward/record.url?eid=2-s2.0-85078276083&partnerID=40&md5=8dfd706094de57a75df44a3ff8754e77https://scholars.lib.ntu.edu.tw/handle/123456789/548328In order to provide the real-time monitoring for identifying the sources of pollution and improving the irrigation water quality management, the integration of continuous automatic sampling techniques and cloud technologies is essential. In this study, we have established an automatic real-time monitoring system for improving the irrigation water quality management, especially for heavy metals such as Cd, Pb, Cu, Ni, Zn, and Cr. As a part of this work, we have first provided several examples on the basic water quality parameters (e.g., pH and electrical conductance) to demonstrate the capacity of data correction by the smart monitoring system, and then evaluated the trend and variance of water quality parameters for different types of monitoring stations. By doing so, the threshold (to initiate early warming) of different water quality parameters could be dynamically determined by the system, and the authorities could be immediately notified for follow-up actions. We have also provided and discussed the representative results from the realtime automatic monitoring system of heavy metals from different monitoring stations. Finally, we have illustrated the implications of the developed smart monitoring system for ensuring the safety of irrigation water in the near future, including integration with automatic sampling for establishing information exchange platform, estimating fluxes of heavy metals to paddy fields, and combining with green technologies for nonpoint source pollution control. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.Cloud technology; Data imputation; Heavy metals; Illegal discharge; Improvement strategies; Stripping voltammetry[SDGs]SDG3[SDGs]SDG6[SDGs]SDG7cadmium; chromium; copper; nickel; palladium; zinc; heavy metal; water; heavy metal; nonpoint source pollution; pollution control; pollution monitoring; water management; water quality; agricultural parameters; Article; automation; concentration (parameter); electric conductance; environmental monitoring; irrigation (agriculture); mathematical model; pH; pollution control; remote sensing; stripping voltammetry; Taiwan; water quality; China; water pollutant; Agricultural Irrigation; China; Environmental Monitoring; Metals, Heavy; Water; Water Pollutants, Chemical; Water Qualityjournal article10.3390/ijerph17030737319792502-s2.0-85078276083WOS:000517783300062