The Construction Path of Smart Water Plants and Control Strategies for Emerging Contaminants

TLDR

This study proposes an intelligent water plant construction path based on digital twins, Internet of Things and artificial intelligence, combined with reinforcement learning and advanced oxidation technologies for pollutant control, which can maintain more than 90% of water quality, improve energy efficiency by 11%, and operate stably under load changes.

Abstract

With the shortage of water resources and strict environmental regulations, intelligent water plants have become the key to meeting the challenges of water treatment. Traditional water plants have technical bottlenecks in the control of new pollutants, especially in the detection and removal of pollutants. This study proposes an intelligent water plant construction path based on digital twins, Internet of Things and artificial intelligence, combined with reinforcement learning and advanced oxidation technologies (AOPs) for pollutant control. The experimental results show that the framework can maintain more than 90% of water quality, improve energy efficiency by 11%, and operate stably under load changes. This study provides a technical solution for the construction of intelligent water plants and the control of new pollutants, and has important theoretical and application value for the sustainable management of water resources and environmental protection.