Insights on AI, water quality, and environmental protection from the Nyad team.
Deep learning models trained on spectroscopy and sensor time-series data can now identify PFAS compounds, heavy metals, and emerging contaminants faster and more accurately than any conventional lab-based method. We explore how this technology works and what it means for water utilities.
Read ArticleExpanding EPA regulations and multi-jurisdictional monitoring requirements are straining manual compliance programs. AI platforms are automating reporting, predictive exceedance detection, and schedule management.
Read MoreAI-driven automation is reducing chemical costs, cutting energy use in aeration, enabling predictive maintenance, and helping wastewater plants manage variable influent conditions with smaller operator teams.
Read MoreContinuous AI-driven sensor networks are replacing periodic sampling — delivering real-time contamination detection at source water intakes, treatment plants, and throughout the distribution system.
Read MoreContinuous sensor-based monitoring is replacing periodic sampling. Here's what the transition looks like in practice for municipal water operators managing aging infrastructure.
Read MoreThe EPA's final PFAS Maximum Contaminant Levels create significant monitoring and reporting obligations. We break down what's required and how to prepare your system.
Read MoreMachine learning models trained on pressure fluctuations and water quality data can predict pipe failures and treatment plant anomalies days before they become critical incidents.
Read MorePer- and polyfluoroalkyl substances (PFAS) are found in water systems across the country. We explain what they are, why they're dangerous, and how AI detection is changing the response.
Read MoreMost water utilities run SCADA infrastructure built in the 1990s and 2000s. Here's how to integrate modern AI analytics without replacing everything you already have.
Read MoreA 40,000-person water district detected an anomalous lead spike at a single distribution node before it reached consumer taps — preventing a potential public health crisis.
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