How the Weights Decide the “Best” Sensor
Ada re-derives this chapter’s own numbers step by step, at full precision
ADA · CALCULATION AUDIT
How the Weights Decide the "Best" Sensor
The chapter scores IoT temperature sensors with weighted requirements — accuracy at 9, waterproofing at 10, sleep current at 7, cost at 5, and humidity at 3, for a total possible weight of 34 — and reports the DS18B20 at 91% against the DHT22’s 50%, a 41-point gap. Those percentages are presented as the deciding argument for “best” sensor. This audit asks the question the gap invites: does the arithmetic behind 91% and 50% actually check out, and where does the 41-point gap really come from?
Companion to the chapter Choosing the Right Sensor — every number here comes from that chapter.
Ada: The weighted-scoring section reports DS18B20 at 91% and DHT22 at 50%, with a 41-point gap. Those percentages are the whole argument, so let me rebuild them from the weights: accuracy 9, waterproof 10, sleep 7, cost 5, humidity 3, for a total possible of 9 + 10 + 7 + 5 + 3 = 34.
- DS18B20 passes accuracy, waterproof, sleep, cost:
9 + 10 + 7 + 5 = 31, so31 / 34 x 100 = 91.2% - DHT22 passes accuracy, cost, humidity:
9 + 5 + 3 = 17, so17 / 34 x 100 = 50.0% - BME280 passes sleep, cost, humidity:
7 + 5 + 3 = 15, so15 / 34 x 100 = 44.1%
The gap is 91.2 - 50.0 = 41.2 points, and it comes almost entirely from the two heaviest requirements DHT22 misses – waterproof (10) and sleep current (7) sum to 17 of the 34 possible points. The design-meaningful conclusion is that the ranking is manufactured by the weights, not discovered in the datasheets: set waterproofing’s weight to zero for an indoor project and DS18B20 surrenders its 10-point lead, which is exactly why the chapter insists there is no objectively best sensor, only the best sensor for a stated priority vector.
Every number above is taken from the chapter’s own material and re-derived step by step.