Live sensor stream (temperature, pressure, vibration) with online anomaly detection. The model updates with every observation and resets when the distribution shifts (concept drift).
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Last 200 observations. Red dots = anomaly alerts; yellow vertical lines = drift (model reset).
What you're seeing ▼
Synthetic stream: Three phases — normal baseline, gradual concept drift, then injected anomalies (spikes and contextual outliers). The stream loops; each cycle takes ~40s.
Online learning: The detector updates with every observation; no batch retraining. When drift is detected on the anomaly score stream, the model resets to adapt.
Metrics: Precision and recall are computed in real time against ground truth labels. All counters reset at the start of each stream cycle so the dashboard reflects the current run.