Abstract
Global freshwater demand is projected to increase, highlighting the growing importance of efficient membrane– based water reuse and advanced treatment technologies. While MF, UF, and RO systems can produce high–quality treated water, they face operational challenges such as fouling, scaling, and high energy consumption. In this study, we introduce the real–time water quality sensing platform “S.sensing” to optimize the dosing of coagulants and RO treatment chemicals. Furthermore, by leveraging AI–driven multi-objective optimization to reduce energy consumption and improve operational uptime, we contribute to the advancement of sustainable and cost–effective membrane treatment technologies.
