Separate Raw Sensor Data from Interpreted State

Presence, motion and occupancy are conclusions; retain enough underlying evidence to debug those conclusions.

I keep this as a field note because the failure mode is easy to misclassify: only the final classifier label is stored. The useful move is to identify the boundary first, then change only the layer that owns it.

What I model

The system is easier to debug when intent, observation and transport are not collapsed into one state. For this case, my rule is simple: Persist evidence and decision as separate fields.

Implementation pattern

Timestamp raw or minimally processed features, derived state and calibration context so false decisions can be reconstructed.

I prefer a small explicit contract over a clever implicit one. That gives logs, tests and dashboards something concrete to verify and keeps unrelated layers from compensating for each other.

What I verify

• raw evidence aligns with state timestamps
• calibration version is known
• false transitions can be reconstructed

Failure handling

When one of those checks fails, I preserve the failing evidence before restarting or changing configuration. The first broken contract determines the next investigation. That keeps troubleshooting causal instead of turning it into a sequence of guesses.

What I keep

Persist evidence and decision as separate fields. The specific tools can change, but that ownership boundary remains useful across firmware, networks and infrastructure.