Current reviews of various AI techniques used for dye adsorption

Textiles, cosmetics, food, and pharmaceuticals industries are major sources of synthetic organic dyes due to their stability, cost-effectiveness, and vibrant colors. However, their widespread usage contributes significantly to environmental pollution, particularly in aquatic ecosystems. Conventional wastewater treatment methods, including adsorption, membrane separation, and Biosorption process are often expensive with limited efficiency and generate hazardous by-products. Application of Artificial intelligence (AI) including artificial neural networks (ANNs), convolutional neural networks (CNNs), and support vector machines (SVMs), offer promising solutions for optimizing dye wastewater treatment. Hybrid techniques integrating adsorption with biodegradation or membrane separation further improve dye removal performance. This review highlights the role of AI in adsorption technologies for sustainable wastewater treatment. It has been shown that ANN based model approach is used by most of the researcher due to its easy to use, more accuracy.