Authors: Ms. Anshika Yadav
Abstract: The increasing growth of urbanization and industrialization has intensified the burden on conventional sewage treatment plants (STPs), leading to higher energy consumption, operational inefficiencies, and environmental pollution. Artificial Intelligence (AI) has emerged as a transformative technology capable of improving wastewater treatment processes through predictive analytics, automation, optimization, and real-time monitoring. This research paper explores the concept of AI-powered smart sewage treatment plants and examines how machine learning, deep learning, IoT sensors, and digital twin technologies can enhance sewage treatment efficiency and sustainability. The study reviews existing literature, identifies research gaps, and proposes an AI-integrated smart sewage treatment framework for predictive maintenance, water quality forecasting, and energy optimization. The paper concludes that AI-enabled STPs can significantly reduce operational costs, improve effluent quality, and support sustainable urban water management.
DOI: https://doi.org/10.5281/zenodo.20443923
