AI-Driven Smart Wastewater Management: Enhancing Urban Water Sustainability and Resource Recovery

Abstract

Urban wastewater management is a critical component of sustainable water cycles, but traditional systems often struggle with inefficiencies such as high operational costs, resource wastage, and environmental pollution. This paper explores how Artificial Intelligence (AI) and IoT technologies can optimize urban wastewater management by enabling real-time monitoring, predictive maintenance, and resource recovery. By integrating data from IoT sensors, water quality monitors, and treatment plants, cities can improve water quality, reduce operational costs, and recover valuable resources such as energy and nutrients. Experimental results demonstrate significant improvements in treatment efficiency, resource recovery rates, and environmental impact, offering a sustainable blueprint for smart urban wastewater systems.

Analytics

Added to PP
2025-02-08

Downloads
94 (#100,805)

6 months
94 (#67,019)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?