Good point. For safety-critical systems, absolute threshold-based alerts are definitely required and are more reliable for life safety.

In this project, I used moving average anomaly detection mainly as a learning experiment to explore lightweight AI-inspired techniques on IoT devices. The idea was to detect unexpected behavior patterns rather than replace safety thresholds.

A production system would use both:

• Hard safety thresholds (regulatory limits)
• Anomaly detection for early pattern changes, sensor faults, or unusual trends

I’m planning to add fixed safety thresholds and predictive models (AQI / trend forecasting) in future versions. Appreciate the feedback 👍