The Operational Nitrogen Indicator (ONI): An Intelligent Index for the Wastewater Treatment Plant’s Optimization

In the context of wastewater treatment plant optimization, this study presents a novel approach based on a virtual sensor architecture designed to estimate total nitrogen levels in effluent and assess plant performance using an operational indicator. The core of the system is an intelligent agent that integrates real-time sensor data with machine learning models to infer nitrogen dynamics and anticipate deviations from optimal operating conditions. Central to this strategy is the operational nitrogen indicator (ONI), a weighted aggregation of four sub-indicators: legal compliance (Nactual%), the nitrogen dynamic trend (Tnitr%), removal efficiency (Enitr%), and microbial balance (NP%), each of which captures a critical dimension of the nitrogen removal process. The ONI enables the early detection of stress conditions and facilitates adaptive decision-making by quantifying operational status in terms of regulatory thresholds, biological requirements, and dynamic stability. This approach contributes to a shift toward smart wastewater treatment plants, where virtual sensing, autonomous control, and throttling-aware diagnostics converge to improve process efficiency, reduce operational risk, and promote environmental compliance.