AquaIntel

AquaIntel — Fused catchment-to-tap operational water corpus: minutes-interval multi-parameter station telemetry (pH, turbidity, conductivity, dissolved oxygen, nitrate) from sondes, flow and level loggers plus ingested SCADA tags, joined to rainfall, laboratory results and satellite imagery in a single data layer, and turned into forecast records — turbidity and contamination forecasts at intakes and river reaches, demand and reservoir drawdown forecasts, and burst/leak likelihood by zone. The ownable asset is the aligned multi-source training set plus the advisory record: forecast issued, re…

AquaIntel offers (Alternative, Geospatial) — Est. roughly 100,000 readings per station per year at a few-minute polling interval across a handful of water-quality parameters, so tens of stations produce low millions of readings annually before SCADA tags, lab results and satellite imagery are added. Satellite and rainfall layers are externally sourced and therefore not incremental to the ownable volume. Volume scales linearly with each new utility deployment; no deployment count is published, so this is a mechanic-derived bound rather than a measured figure.

Training early-warning contamination and turbidity nowcasting models with genuine lead-time targets; treatment process optimisation models linking upstream quality to coagulant dosing; demand forecasting and reservoir drawdown models for drought and rationing planning; zone-level burst and leak likelihood models; edge-deployed anomaly detectors (the corpus is already shaped for constrained-on-device inference, given on-station TensorRT deployment); missing-data-robust time-series methods built on the connectivity-gap replays; and multimodal fusion research that must join point sensor data with satellite imagery — a pairing most publicly available datasets do not provide aligned

The data is with 2 years of history.

Coverage spans US; Application Software; alternative, geospatial; equities.