Bump version to 1.1 and include detailed AQ docs

README.md

@@ -38,12 +38,12 @@ For more details, please [see my blog post on the SuperSensor project](https://w
 
 * 1x ESP32 devkit (V4 38-pin, slim) [AliExpress (HW-395)](https://www.aliexpress.com/item/1005006019875837.html)
 * 1x INMP441 MEMS microphone [Amazon search](https://www.amazon.ca/s?k=INMP441)
-* 1x BME680 temperature/humidity/pressure/gase sensor (3.3v models); BME280 or BMP280 can be subsistuted but with reduced fuctionality (comment/uncomment the appropriate blocks as needed) [AliExpress](https://www.aliexpress.com/item/4000818429803.html)
+* 1x BME680 temperature/humidity/pressure/gas sensor (3.3v models); BME280 or BMP280 can be substituted but with reduced functionality (comment/uncomment the appropriate blocks as needed) [AliExpress](https://www.aliexpress.com/item/4000818429803.html)
 * 1x TSL2591 light sensor [AliExpress](https://www.aliexpress.com/item/1005005514391429.html)
-* 1x HLK-LD2410C-P mmWave radar sensor [AliExpress (LD2410C-P)](https://www.aliexpress.com/item/1005006000579211.html)
+* 1x HLK-LD2410C-P mm-Wave radar sensor [AliExpress (LD2410C-P)](https://www.aliexpress.com/item/1005006000579211.html)
 * 1x SR602 PIR sensor [AliExpress](https://www.aliexpress.com/item/1005001572550300.html)
-* 2x Common-cathod RGB LEDs [Amazon search](https://www.amazon.ca/s?k=5mm+RGB+LED+common+cathode)
-* 1x Resistor for the common-cathod RGB LED @ 3.3v input (~33-1000Ω, depending on desired brightness and LEDs)
+* 2x Common-cathode RGB LEDs [Amazon search](https://www.amazon.ca/s?k=5mm+RGB+LED+common+cathode)
+* 1x Resistor for the common-cathode RGB LED @ 3.3v input (~33-1000Ω, depending on desired brightness and LEDs)
 * 1x SuperSensor PCB board (see "board/supersensor.dxf" or "board/supersensor.easyeda.json")
 * 1x 3D Printed case [Optional] 
 * 1x 3D Printed diffuser cover [Optional] 
@@ -51,7 +51,7 @@ For more details, please [see my blog post on the SuperSensor project](https://w
 ## Configurable Options
 
 There are several UI-configurable options with the SuperSensor to help you
-get the most out of the sensor for your particular usecase.
+get the most out of the sensor for your particular use-case.
 
 ### Voice Control
 
@@ -64,18 +64,8 @@ but can be done if desired.
 The AQ (air quality) calculation from the BME680 requires a "maximum"/ceiling
 threshold for the gas resistance value in clean air after some operation
 time. The value defaults to 200 kΩ to provide an initial baseline, but
-should be calibrated manually after setup as each sensor is different:
-
-1. Turn on the Supersensor in a known-clean environment (e.g. a sealed clean
-   container in fresh air).
-2. Leave the sensor on for 4-6 hours to burn in.
-3. Look at the historical graphs for the Gas Resistance sensor and find the
-   maximum value over the burn-in period.
-4. Round the maximum Gas Resistance value **up** to the nearest 1000.
-4. Divide the rounded maximum Gas Resistance value by 1000 to get the kΩ value.
-
-This value will then define what "100% air quality" represents, and the
-Supersensor can then be moved to its normal operating location.
+should be calibrated manually after setup as each sensor is different. See
+the section "Calibrating AQ" below for more details.
 
 ### Light Threshold Control
 
@@ -115,7 +105,7 @@ handled separately:
 #### PIR + Radar + Light
 
 Occupancy is detected when all 3 sensors report detected, and occupancy is
-cleared when any of the sensors report clearered.
+cleared when any of the sensors report cleared.
 
 For detect, this provides the most "safety" against misfires, but requires
 a normally-dark room with a non-automated light source and clear PIR
@@ -154,7 +144,7 @@ Occupancy is detected when both sensors report detected, and occupancy is
 cleared when either of the sensors report cleared.
 
 For detect, this allows for radar detection while suppressing occupancy
-without light, for insance in a hallway where one might not want a late
+without light, for instance in a hallway where one might not want a late
 night bathroom visit to turn on the lights, or something to that effect.
 
 For clear, this option can provide a useful option to clear presence
@@ -188,3 +178,139 @@ For detect, no occupancy will ever fire.
 For clear, no states will clear occupancy; with any detect option, this
 means that occupancy will be detected only once and never clear, which
 is likely not useful.
+
+## Calibrating AQ
+
+The Supersensor uses the Bosch BME680 combination temperature, humidity,
+pressure, and gas sensor to provide a wide range of useful information about
+the environmental conditions the sensor is placed in. However, this sensor
+can be tricky to work with.
+
+While it's normally recommended to use the Bosch BSEC library with this
+sensor, in my ~6 month experience I found this library to be far more trouble
+than it was worth. Specifically, it's IAQ measurement is nearly useless, with
+a strong tendency to get stuck in an upward trend constantly "calibrating"
+itself to higher and higher baselines, to the point where nonsensical values
+were being read. After much research into this, I decided to abandon the
+library in version 1.1 and went with a more custom solution.
+
+Instead of the BSEC, we use the stock BME680 ESPHome library, along with
+some calculations by thstielow on GitHub in their [IAQ project](https://github.com/thstielow/raspi-bme680-iaq).
+This provided some useful example code and formulae to calculate a useful
+Air Quality (AQ) value instead of the useless Bosch value.
+
+However using this method requires some manual calibration of the sensor
+after putting it together but before final use, in order to get a somewhat
+accurate value out of the AQ component. If you don't care about the AQ value,
+you can skip this, but it is recommended to take full advantage of the sensor.
+
+As a quick explainer, the code leverages a combination of the "Gas Resistance"
+value provided by the sensor, along with an absolute humidity calculated from
+the temperature and relative humidity of the sensor (included ESPHome sensor),
+along with two values (one configurable, one hard-coded) and several formulae
+to arrive at the resulting AQ value. For full details of the calculation,
+see the repository linked above, which was re-implemented faithfully here.
+
+The first thing to note is that each BME680 sensor is wildly different in
+terms of gas resistance values. In the same air, I had sensors reading values
+that differed by nearly 200,000Ω, which necessitates a human-configurable
+baseline value. Further, the IAQ project recommends determining a linear
+slope value for this, but instead of trying to explain how to calculate this,
+I just went with the default slope value of 0.03 for this first iteration.
+
+Thus, the main difficulty in getting a useful AQ score is finding the
+"Gas Resistance Ceiling" value. This value is configurable in the
+SuperSensor interface (Web or HomeAssistant), and should be calibrated as
+follows during the initial setup of the supersensor.
+
+1. Find a known-clean room, for instance a well-ventilated, well-cleaned
+room in your house or similar. It should have fresh air (no stray VOCs) but
+also minimal drafts or outside exposure especially if there is a poor external
+AQ level. This will be your calibration reference room. Ideally, this room
+should be somewhere between 16C and 26C for optimal performance, so air
+conditioning (or a nice spring/fall day) is best.
+
+2. Turn on the SuperSensor in this environment, and connect it to your
+HomeAssistant instance; this will be critical for viewing historical graphs
+during the following steps.
+
+3. Let the SuperSensor run to "burn in" the gas sensor for at least 3-6 hours,
+or until the value for the Gas Resistance stabilizes. It is best to avoid much
+movement or activity in the selected calibration room to avoid disrupting
+the sensor during this time. It is also best to ensure that the ambient
+temperature changes as little as possible during this time.
+
+4. Review the resulting graph of Gas Resistance over the burn-in period. You
+can usually ignore the first hour or two as the sensor was burning in, and
+focus instead on the last hour or so.
+
+5. Make note of the highest mean value reached by the sensor during this time.
+This will be your baseline value for calibrating the Gas Resistance Ceiling.
+
+6. Round the value up to the nearest 1000. For example, if the maximum value
+was 195732.1, round this to 196000.0.
+
+7. Find the difference in the temperature of the BME680 temperature sensor
+from 20C, called ΔT below. I found this part by trial-and-error, so this is
+not precise, but as an example if the calibration room is reporting 26C, your
+ΔT value in the next step is 6. If your temperature was below 20C, use 0.
+
+8. Use one of the following formulae to come up with your offset value, which
+depends on the maximum value range found in step 6.
+
+   * `<100,000`: 200 * ΔT = 0-1200
+   * `100,000-200,000`: 500 * ΔT = 0-3000
+   * `>200,000`: 1000 * ΔT = 0-6000
+
+Again this value is rough, and might not even really be needed, but helps
+avoid weird issues with AQ values dropping suddenly later as temperature
+and humidity changes.
+
+9. Add your offset value from step 8 to the rounded maximum from step 6.
+For example, 196000.0 with a ΔT of 5C (25C ambient) yields 201000.0
+
+10. Divide the result from 9 by 1000 to give a number from 1-500. This
+is the value to enter as the "Gas Resistance Ceiling (kΩ)" for this
+sensor. This value will be saved in the NV-RAM of the ESP32 and preserved
+on reboots.
+
+At this point, you should have a value that results in the "BME680 AQ"
+sensor reporting 100% AQ, i.e. clean air. You can now test to ensure
+that the value will correctly drop as VOCs are added.
+
+1. Take a Sharpie permanent marker, Acetone nail polish remover, or some
+other VOC that the BME680 gas sensor can detect, and place it near the
+sensor. For example with a sharpie, remove the cap and place the tip
+about 1-2cm from the sensor, or place a small capful of nail polish
+remover about 3-5cm from the sensor.
+
+2. Wait about 30 seconds.
+
+3. You should see the AQ value drop precipitously, into the order of 50%
+or lower, and ideally closer to 0-20%. If the value remains higher than
+50% with this test, your calculated Gas Resistance Ceiling might be
+too low, and should be increased in increments of 1000.
+
+4. Remove the VOC source (replace the cap, remove the capful of remover,
+etc.) and wait about 30-60 minutes.
+
+5. You should see the AQ value and gas resistance return to their original
+values. If it is significantly lower than before, even after waiting 60+
+minutes, restart the calculation from step 5 in the previous section
+using this new value as the baseline.
+
+At this point, the sensor should be calibrated enough for day-to-day
+casual home use, and will tell you if there is any significant
+VOC contamination in the air by dropping the AQ value from 100% to some
+lower value representing the approximate decrease in air quality. Since
+the sensor also factors in the absolute humidity (and via that, the
+ambient temperature) into the AQ calculation, high humidity will also
+drop the value, as this too impacts the air quality. Hopefully this
+is useful for your purposes.
+
+If you find that the AQ value still doesn't represent known reality,
+you can also tweak the in-code value for `ph_slope` on line 522, as
+it's possible your sensor differs significantly here. As mentioned
+above this is still a work in progress to determine for myself, so
+future versions may alter this or include calibration of this value
+automatically, depending on how things go in my testing.

supersensor.yaml

@@ -26,7 +26,7 @@ esphome:
   friendly_name: "Supersensor"
   project:
     name: joshuaboniface.supersensor
-    version: "1.0"
+    version: "1.1"
   on_boot:
     - priority: 600
       then: