AI and Smart Water Treatment: A Bibliometric Perspective on Emerging Technologies in Water Purification

Artificial Intelligence (AI) is redefining water treatment systems, enabling smarter, more efficient, and sustainable solutions. This work employs bibliometric approaches to explore trends, advancements, and future directions in the integration of AI technologies into water purification systems. By analyzing 350 articles from 2010 to March 2025 using VOSviewer software, the study highlights AI's role in optimizing processes such as contaminant detection, filtration efficiency, and predictive maintenance. Key challenges include cost, data availability, and scalability. The research identifies influential authors, institutions, and countries driving AI innovations in water treatment. Emerging themes like machine learning (ML), Internet of Things (IoT), and real-time monitoring are explored, with techniques such as neural networks and decision tree algorithms being applied to improve water treatment efficacy. Additionally, the study addresses gaps in interdisciplinary collaboration and the need for AI-driven models tailored to diverse water treatment scenarios. It emphasizes the importance of sustainable practices, the development of eco-friendly treatment methods, and the transformative potential of advanced computational techniques in addressing global water challenges. By providing a comprehensive overview of global research trends, this analysis serves as a valuable resource for researchers, engineers, and policymakers, underscoring the vital role of AI in fostering smarter, more resilient water purification systems.