Bibliometric analysis on the use of artificial intelligence to assess the role of macrophytes in heavy metal removal
DOI:
https://doi.org/10.51798/sijis.v6i4.1063Keywords:
artificial intelligence (AI); macrophytes; bibliometric analysis; environmental remediation; heavy metals; sustainabilityAbstract
Water pollution by heavy metals has become a global concern, prompting the search for sustainable remediation strategies. This study presents a bibliometric analysis of scientific publications from 2019 to 2025 that addresses the use of artificial intelligence to assess the role of macrophytes in the removal of heavy metals from aquatic environments. Data were obtained from the Scopus database using a defined search equation and analyzed with RStudio, Bibliometrix, and Biblioshiny. A total of 66 documents were reviewed, showing a significant increase in scientific output, particularly in countries such as India, China, and the United States. The most cited topics included machine learning, water quality, and environmental remediation. Influential authors, international collaboration networks, and emerging research areas such as biosensors and hybrid models were identified. The findings highlight how artificial intelligence enhances the efficiency of phytoremediation processes by predicting and monitoring contaminant removal in real time. In conclusion, artificial intelligence is a strategic and promising tool for optimizing the use of macrophytes in the treatment of contaminated water, contributing to environmental sustainability and public health.
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