AI-DRIVEN WATER PURIFICATION MODEL IMPLEMENTATION IN SMART CITIES: REAL-TIME SOLAR DESALINATION AND EFFLUENT TREATMENT

Abstract

The rapid urbanization and population growth in smart cities have intensified the demand for sustainable, efficient, and resilient water purification solutions. Traditional methods of desalination and effluent treatment often face challenges such as high energy consumption, operational inefficiency, and limited adaptability to fluctuating urban water needs. This paper proposes an integrated AI-driven water purification model that combines real-time solar-powered desalination systems with advanced effluent treatment mechanisms, optimized through predictive machine learning algorithms. The model leverages artificial intelligence to monitor, forecast, and regulate critical parameters, including salinity, turbidity, energy input, and contaminant levels, ensuring dynamic resource allocation and system stability. A hybrid framework is developed wherein solar-powered desalination provides a sustainable clean water source, while AI-enhanced effluent treatment units recycle wastewater streams, reducing environmental burden and promoting circular water use. The proposed system is tested through simulation and pilot-level validation, demonstrating significant improvements in purification efficiency, reduction in energy intensity, and adaptive responsiveness to varying urban water demands. Results indicate that AI optimization enables a reduction in operational costs by enhancing predictive maintenance, minimizing downtime, and improving energy utilization of photovoltaic modules. Furthermore, the integration of real-time analytics facilitates smart decision-making, aligning with the sustainability objectives of smart cities by reducing greenhouse gas emissions and ensuring water security. The findings of this study suggest that AI-driven solar desalination and effluent treatment not only address critical challenges of urban water management but also serve as a scalable and replicable model for global smart city applications. This research contributes to the evolving discourse on sustainable infrastructure by presenting an innovative approach that integrates renewable energy, artificial intelligence, and water purification technologies to achieve long-term resilience and resource optimization in urban ecosystems.