The application of artificial intelligence (AI) and machine learning (ML) has helped improve water quality, a recent review published in TrAC Trends in Analytical Chemistry shows (1).
Water quality is crucial for human health, environmental sustainability, and economic development. Clean water is essential for drinking, agriculture, sanitation, and industrial processes. Poor water quality can lead to the spread of waterborne diseases; to polluted aquatic ecosystems, and to disruption of food chains. Contaminated water, often polluted by chemicals, pathogens, or heavy metals, poses serious health risks to humans, animals and plants and can lead to long-term environmental damage (2). Some of these health risks include gastrointestinal illness, reproductive problems, and neurological disorders (2). Ensuring good water quality helps protect biodiversity, maintain healthy ecosystems, and supports sustainable development by providing safe, reliable water for human and ecological needs. Ultimately, water quality is vital for preserving life and ensuring the well-being of future generations.
Biologist working on water analysis. Ecology and environmental pollution concept. | Image Credit: © kaninstudio – stock.adobe.com
This review article, written by lead author A. D. Robles from the National University of Mar del Plata examines how AI and ML are positively impacting water monitoring, specifically highlighting how these technologies enhance the detection of contaminants and predict water quality parameters, offering a glimpse into the future of water resource management (1).
The review takes an in-depth look at recent developments in the application of machine learning to the analysis of water quality. By processing spectral data from water samples, AI can swiftly identify pollutants and support early warning systems, proving invaluable in monitoring drinking water, tap water, surface water, and wastewater (1).
Water quality control is critical in managing Earth’s natural resources, with surface water playing a vital role. Surface water, defined as water found at the Earth’s surface and exposed to the atmosphere, is essential for human consumption, recreational use, agriculture, and industrial applications (1). However, it is easily polluted by fertilizers, chemicals, sewage, and waste products, leading to serious health concerns when contaminated water is consumed (1).
In this context, the review highlights how AI and ML are addressing the complexity of […]
Artificial Intelligence and Machine Learning: Assessing Water Quality
