Warehouse environments are noisy and dynamic. Anomaly detection models must handle clutter, partial visibility, and changing workflows while preserving low false-alarm rates.
Core Strategy
Use a two-stage approach:
- Fast detector for candidate event extraction
- Context model for anomaly scoring and prioritization
This reduces alert fatigue while improving recall on meaningful incidents.
Deployment Notes
- Calibrate per camera zone
- Track drift weekly
- Use human-reviewed replay buffers for retraining
The best systems combine statistical guardrails with model confidence to keep operations stable.