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.

中文翻译：

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人工智能与水质：从饮用水到废水

人工智能 (AI) 技术，特别是机器学习 (ML) 对水质评估中光谱数据分析的变革性影响怎么强调也不为过。我们回顾了人工智能和机器学习彻底改变了水质参数分析和预测的方式。这些技术可有效处理来自各种来源的光谱数据、识别污染物并支持早期检测系统。然而，人工智能工具也有局限性，包括需要大量且多样化的数据集才能获得最佳性能，而且一些研究使用小型数据集，限制了模型的预测能力。开放数据库有助于扩大人工智能在水质控制和处理方面的应用。人工智能和光谱技术的潜力可降低成本，促进环境可持续的水处理，并提高水和环境质量。最后，我们强调需要进行立法改革和组织之间的合作，以利用这些技术及其重要水资源之间的协同作用。