sensor data influenced by other sensor?

sugo

Hi,

I just got my Air-Q Science a week ago, and playing around a bit.

Before giving my feedback I have to understand well some stuff.

Are the value retrieved via HTTP GET /data modified in some way, except calibration and average stuff? I mean:

is there some fix done using other sensors, like NO2 used to fix cross sensitivity of the O3 sensor?
is the RH and/or temperature correction done in the app or is this already "included" in the value got via HTTP get?
is there any way to get raw data, with no calibration and such?

Thanks a lot

sugo

well, it sucks a bit that nobody answered, anyway, I assume none of this is applied

is there some fix done using other sensors, like NO2 used to fix cross sensitivity of the O3 sensor?
is the RH and/or temperature correction done in the app or is this already "included" in the value got via HTTP get?

I am trying to do a good calibration inside home assistant since autocalibration it's completely useless. I understand the need to have it, for the average user who don't want to bother about tuning and still want some numbers to read, but, in particular for O3 / NO2 this does not work

sugo

https://community.home-assistant.io/t/air-q-device-any-good/512254/5

Mario [air-Q]

sorry for the late answer. I did miss the mail-reminder obviously.

I will answer your questions gladly:
is there some fix done using other sensors, like NO2 used to fix cross sensitivity of the O3 sensor?
--> no. we dont correct for cross sensitivities at the moment. We have aresearch project on this and hope we will be able to do so in the future (actually our research focuses on measuring NEW additional sensor values)

is the RH and/or temperature correction done in the app or is this already "included" in the value got via HTTP get?
--> done in the air-Q device

is there any way to get raw data, with no calibration and such?
--> hm. you could deduct the baseline calibration value from the data. reverse the temperature correction seems impossible.

"autocalibration it's completely useless."
Why do you think so?
without the autocalibration the values would drift over time and could even "jump" permanently when "climatic shocks" occur.

Mario [air-Q]

@sugo ping

sugo

"no. we don't correct for cross sensitivities at the moment. We have research project on this and hope we will be able to do so in the future (actually our research focuses on measuring NEW additional sensor values)"

Well, this is quite important considering the 1:1 sensitivity of O3 to NO2, and since we got a NO2 sensor, looks like obvious to use it, probably better fixing the current stuff than implementing new sensors

"done in the air-Q device"

after some analisys, see my review on the link above, in the HA forum, I am not sure this is done accurately, it would be nice to have the raw values and/or the formulas you use

"Why do you think so?
without the autocalibration the values would drift over time and could even "jump" permanently when "climatic shocks" occur"

because a simple correction of the zero value is not enough, I had tried a climatic shock, from outdoor 0 °C to indoor 20 °C and with the compensation I did, it looks everithing works fine, I still have to fix/fine tuning something, but what I mean is: we have a very good device with good sensors, we can and we should achieve better measurement of what we currently receive. Sensors are factory calibrated, which is a damn good stuff, we probably just need a good temperature/humidity/pressure compensation, and a fix of cross sensitivity is a must. Anyway I will go on with my review on HA forum (which BTW is a positive review) providing graph and stuff, at the end I will provide the exact formulas I used for compensation, which seems to work just fine

just my $ .02

sugo

@Mario-air-Q : at least for the science options you should provide raw value when possible, I reverse engineered %RH but I am not convinced if there's some additional daleay added for some reasons, or what's wrong, maybe I did a mistake in the math

since it say 3.8 for calibration

"temperature": {
  "Unit": {
    "humidity": "%",
    "temperature": "degC",
    "dewpt": "degC",
    "humidity_abs": "g/m^3"
  },
  "Part Number": "HDC1080",
  "Manufacturer": "Texas Instruments",
  "Description": "Temperature and Humidity Sensor",
  "Offset": {
    "temperature": -3.8
  },

I did (in home assistant but should be easy to understand)

  - sensor:
    - name: "AirQ Temperature Original"
      state: "{{states('sensor.airq_temperature') | float + 3.8 }}"  
  - sensor:
    - name: "AirQ Internal Saturated Vapour Pressure"
      state: "{{  610.94 * 2.7182818 ** ( 17.625 * states('sensor.airq_temperature_original') | float / ( 243.04 + states('sensor.airq_temperature_original') | float) ) }}"  
  - sensor:
    - name: "AirQ RH original"
      unit_of_measurement: "%"
      state: "{{  0.4615 * ( 273.16 + states('sensor.airq_temperature_original') | float) *  states('sensor.airq_absolute_humidity') | float * 100 / states('sensor.airq_internal_saturated_vapour_pressure') | float }}"

Mario [air-Q]

why should you reverse engineere RH? This value is strongly connected to Temperature, meaning they are paired and only are correct if both are corrected