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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects

Wastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science Core Collection database. The literature was analyzed from various aspects such as publications, journals, and authors. There are collaboration relationships among various countries, institutes, and authors. Keywords were analyzed in three directions “artificial intelligence”, “wastewater treatment technology”, and “pollutant types”. Hot keywords were identified, including “support vector machine”, “random forests”, “membrane bioreactor”, “photocatalytic degradation”, and “antibiotics”. Significant advancements were obtained in intelligent water quality monitoring, innovative material development, and energy cost optimization. Machine learning algorithms, such as Convolutional Neural Networks and Long Short-Term Memory, demonstrated remarkable capabilities in predicting process parameters, enhancing material performance, and optimizing energy utilization in wastewater treatment plants. Artificial intelligence applied to wastewater treatment is still in its primary stage, and with the rapid development of artificial intelligence, significant technical innovation in wastewater treatment can be anticipated in the near future.

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