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<p>Industrial and economic growth increasingly lead to the generation of wastewater laden with diverse pollutants, posing significant threats to natural water resources. Artificial intelligence (AI) offers powerful capabilities for data analysis, classification, and prediction, particularly excelling in solving the complex, nonlinear problems prevalent in water-related research compared to conventional modeling approaches. Due to their extreme toxicity, the removal of heavy metals from water and wastewater has garnered significant research focus. Consequently, AI offers a promising avenue for developing sustainable and efficient technologies for water and wastewater treatment. As part of the wastewater treatment process, this study demonstrates how artificial intelligence modelling techniques can predict the amount of adsorbed heavy metals. Results from the case study scenario show approximately 95–98% maximum removal efficiency of zinc and lead in the wastewater. These findings confirm that Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are robust and reliable tools for modeling heavy metal removal from wastewater. In addition, AI will assist stakeholders in making decisions regarding wastewater treatment.</p>

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Process Model Development for Recovery of Heavy Metals from Wastewater Using Artificial Intelligence

  • 期刊论文

  • 发表日期：

    2026年2月3日

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  • Abiola Ezekiel Taiwo,
  • Paul Musonge

摘要

Industrial and economic growth increasingly lead to the generation of wastewater laden with diverse pollutants, posing significant threats to natural water resources. Artificial intelligence (AI) offers powerful capabilities for data analysis, classification, and prediction, particularly excelling in solving the complex, nonlinear problems prevalent in water-related research compared to conventional modeling approaches. Due to their extreme toxicity, the removal of heavy metals from water and wastewater has garnered significant research focus. Consequently, AI offers a promising avenue for developing sustainable and efficient technologies for water and wastewater treatment. As part of the wastewater treatment process, this study demonstrates how artificial intelligence modelling techniques can predict the amount of adsorbed heavy metals. Results from the case study scenario show approximately 95–98% maximum removal efficiency of zinc and lead in the wastewater. These findings confirm that Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are robust and reliable tools for modeling heavy metal removal from wastewater. In addition, AI will assist stakeholders in making decisions regarding wastewater treatment.