Adaptive Sampling Charge Budget

Adaptive Sampling Charge Budget

Ada re-derives this chapter’s own numbers step by step, at full precision

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Ada ADA · CALCULATION AUDIT

Adaptive Sampling Charge Budget

The adaptive-sampling widget defaults to a stable interval of 60 seconds and an active interval of 10 seconds, split 70% stable, drawing on a sensor that pulls 30 mA for 3 seconds and a radio that pulls 170 mA for 2 seconds against a 2000 mAh battery. The chapter frames this as a way to cut energy by only sampling fast when a rolling standard deviation of the last 10 readings crosses a threshold, transmitting only when the value changes by more than 5%. This audit asks the question that design invites: how many days does the fixed 10-second strategy actually buy against the adaptive 70/30 split, once every mAh is added up?

Companion to the chapter Power Accuracy and Field Hardening — every number here comes from that chapter.

See the relationship before changing it

The figure reads from left to right. The blue card is stable-time share. The middle card applies this page's rule. The green card is adaptive readings. Walk the arrows once: set the input, apply the rule, then read the result with its unit.

The retained audit below checks several chapter fixtures. This model keeps those stated values fixed and changes only stable-time share, so the numeric fixture does not switch without explanation.

Stable-time share changes adaptive readings An input card leads through the rule readings = 8,640 - 72 x stable percentage to the adaptive readings result. INPUT PAGE INPUT APPLY THE RULE predict calculate check units OUTPUT RESULT
Walk the arrows. More time at the sixty-second stable interval replaces fast samples and cuts daily readings.

Derive the baseline in four named moves

  1. 1

    Name the input. The chapter baseline is 70 %.

  2. 2

    Name the relationship. readings = 8,640 - 72 x stable percentage

  3. 3

    Substitute with units. 8,640 - 72 x 70 = 3,600 readings/day

  4. 4

    Read the result. Keep the unit beside the value. Use it only inside the technical boundary on this page.

Predict, then change stable-time share

Try Predict the direction of readings = 8,640 - 72 x stable percentage. Test another stable-time share, then compare adaptive readings.

70 %
Chapter baseline
Adaptive readings

Observe More time at the sixty-second stable interval replaces fast samples and cuts daily readings. Reset stable-time share to 70 and compare adaptive readings.

Explain More time at the sixty-second stable interval replaces fast samples and cuts daily readings.

Check yourself

What should you do before trusting a moved-control result?
Answer: Predict its direction, apply the shown relationship, keep the units, and reset to the worked baseline.
What does this small model leave out?
Answer: Only stable-time share moves here. Field effects named in the technical boundary stay fixed.

Honesty note. This teaching model changes only stable-time share. It is not a field prediction.

Try

Calculate the fixed 10-second strategy at 8640 reads/day, then apply the adaptive 70/30 split and press Check audit.

Observe

Daily charge falls from roughly 1032.24 mAh to 192.24 mAh, moving the 2000 mAh battery-life readout from about 1.94 to 10.4 days.

Explain

Adaptive sampling saves charge twice: fewer measurements shorten sensor-on time, and threshold filtering removes most 170 mA radio transmissions.

Ada: Treat the power model as charge accounting. The default widget values already give the sample intervals, stable/active split, threshold-filter rule, load currents, and battery size; the check below only turns those values into mAh per day.

The fixed strategy samples every 10 s, so it takes 24 x 3600 / 10 = 8640 readings per day.

  • Sensor charge: 8640 x 30 mA x 3 s / 3600 = 216 mAh/day.
  • Radio charge: 8640 x 170 mA x 2 s / 3600 = 816 mAh/day.
  • Sleep charge: 0.010 mA x 24 h = 0.24 mAh/day.
  • Fixed total: 216 + 816 + 0.24 = 1032.24 mAh/day; a 2000 mAh battery lasts 2000 / 1032.24 = 1.94 days.

The adaptive default spends 70% of the day at the 60 s stable interval and 30% at the 10 s active interval:

  • Stable readings: 24 x 3600 x 0.70 / 60 = 1008.
  • Active readings: 24 x 3600 x 0.30 / 10 = 2592.
  • Total readings: 1008 + 2592 = 3600, which is (8640 - 3600) / 8640 = 58.3% fewer readings than the fixed case.
  • Threshold-filtered transmissions: 3600 x 0.30 = 1080.
  • Adaptive sensor charge: 3600 x 30 mA x 3 s / 3600 = 90 mAh/day.
  • Adaptive radio charge: 1080 x 170 mA x 2 s / 3600 = 102 mAh/day.
  • Adaptive total: 90 + 102 + 0.24 = 192.24 mAh/day; a 2000 mAh battery lasts 2000 / 192.24 = 10.4 days.

The physics conclusion is narrow: adaptive sampling helps because it reduces both sensing time and radio bursts, but the 1 deg C change threshold is still a data-quality constraint. Lower energy is only a win if the threshold does not hide the event the sensor is supposed to catch.

Every number above is taken from the chapter’s own material and re-derived step by step.

Technical boundaries: The daily charge ledger omits radio retries and association, sensor warm-up variability, MCU processing, regulator loss, battery derating and self-discharge, temperature, threshold-crossing statistics, and missed-event cost.

Ready: work the ledger before checking it.