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KiwisIoT Live Anomaly Detection
Collect, train, and detect live sensor anomalies
Idle
Workflow
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Select channels Pick one or more sensor channels to monitor
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Collect baseline Gather the required baseline readings (200)
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Build model Train an ML model (Isolation Forest) that learns each channel's normal range
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Monitor live Values outside the model's learned range are flagged as anomalies
Collecting baseline readings… Latest value: —
Total readings
0
Normal
0
Anomalies
0
Anomaly rate
0.0%
Live sensor stream
Normal readings
Anomaly markers
Anomaly score history
Distance from normal range (negative = outside min–max)