Artificial intelligence and water quality: From drinking water to wastewater

• DOI: 10.1016/j.trac.2024.117597
• Publication Date: 2024-02-15T11:36:59Z
• Authors: C.H. Pérez-Beltrán; A.D. Robles; N.A. Rodriguez; F. Ortega-Gavilán; A.M. Jiménez-Carvelo
• Keywords: Transformative Learning; Limiting

Fil: Pérez Beltrán, C. H.. Universidad Autónoma de Sinaloa; México<br/>Fil: Jiménez Carvelo, A. M.. Universidad de Granada; España<br/>Fil: Rodríguez, Nicolás Artemio. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Departamento de Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnología de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones en Ciencia y Tecnología de Materiales; Argentina<br/>Fil: Ortega Gavilán, F.. Universidad de Granada; España<br/>Fil: Robles, A. D.. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Departamento de Química; Argentina<br/>The transformative impact of Artificial Intelligence (AI) technologies, particularly Machine Learning (ML), on the analysis of spectroscopic data in water quality assessment cannot be overstated. We remark the ways in which AI and ML have revolutionized the analysis and prediction of water quality parameters. These technologies efficiently process spectral data from various sources, identify contaminants, and support early detection systems. However, AI tools have limitations, including the need for a large and diverse dataset for optimal performance, and some studies used small datasets, limiting the predictive power of the models. Open databases can aid in expanding AI applications in water quality control and treatment. The potential of AI and spectroscopic techniques reduce costs, promote environmentally sustainable water treatment, and enhance water and environmental quality. Finally, we emphasize the need for legislative changes and collaboration between organizations to harness the synergy between these technologies, and its vital water resources.<br/>