New Ellenton, South Carolina Commission of Public Works Facility Ushers in Next-Generation Operating System for Water and Wastewater Operators

Challenge

The Darlington Water Treatment plant in New Ellenton, South Carolina, faced a familiar but urgent challenge many mid- and small-sized systems face daily: how to maintain tight control of chlorine and pH levels under varying operational conditions. With traditional monitoring methods, staff could only react to fluctuations after they occurred, relying on static SCADA dashboards and manual review. This limited visibility exposed the plant to risks: underdosing, overdosing, compliance concerns, and inefficiencies. The need was clear - a smarter, predictive system that could anticipate quality changes before it happens and empower operators to take proactive action.

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Solution

New Ellenton CPW with their Darlington well became one of the first utilities in the Country to implement a machine learning-based predictive monitoring system for real-time chlorine and pH forecasting. Developed by Delta Bravo Artificial Intelligence, in conjunction with funding support by the National Science Foundation, the Aquaspec system represents a leap beyond basic telemetry. Using two-minute SCADA intervals, the system captures operational patterns, filters out pump-startup anomalies, and delivers precise short-term predictions for water quality parameters—automatically.

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At its core are advanced models trained on operational history, optimized with custom time-aware feature engineering, and localized real-time and predictive weather and environmental data. These models achieved 98.7% accuracy for chlorine and 99.7% for pH, transforming noisy raw data into future-facing intelligence.

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This is not just an alert system. It is the next generation operating system for water treatment—one that learns, adjusts, and continuously improves, giving operators a digital lighthouse remaining vigilantly alert for trouble ahead.

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Results

The impacts were immediate and measurable:

• Near-perfect prediction accuracy for key water quality indicators, significantly reducing the potential formation of disinfection-by-products

• Stabilized dosing strategy through predictive visibility which automatically filters the signal from the noise

• Early-warning capabilities for trend-based excursions, leading to fewer shutdowns for major repairs to equipment, and

• Reduced staff burden through intelligent operations, allowing operators to act faster and more precisely, thereby minimizing response times and ensuring that quality adjustments happen before customers ever notice a problem.

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The Aquaspec platform has enabled the utility to confidently move from reactive monitoring to proactive optimization. Operators now have a real-time edge and can adjust ahead of problems, not behind them, with confidence.

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“We’re not just monitoring anymore—we’re forecasting. This is how water plants will run in the future.”

— Patrick Jackson, Meansville-Riley Water Company

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Outcome

New Ellenton CPW’s deployment of Aquaspec’s predictive intelligence marks a new standard for utility operations. This is not an enhancement of legacy systems—it is a step into a fundamentally smarter era. By replacing lagging indicators with actionable foresight, this utility has redefined what water quality control means.

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With AI as a partner, New Ellenton Commission of Public Works has proven that even small-to-mid-sized utilities can lead the sector in innovation. This model is now poised to scale across South Carolina and beyond: wherever safe water, smart data, and cost efficiency matter.