Air Quality Data Logger with Raspberry Pi Pico

https://github.com/natepichler/BME680-Micropython-IAQ

Background

My neighborhood is adjacent to a packing facility. Many of my neighbors are having trouble breathing from the exhaust, bothered by the floodlights, and disrupted by noise.

Our goal, then, is to quantify the effect that this facility has on the quality of our air.

Hardware

In order to achieve this goal, I made a simple data logger running on a Raspberry Pi Pico with a BME680 VOC sensor. The Pico is powered by USB, and communicates with the BME680 sensor using I2C bus.

The BME680 sensor is capable of reading temperature, humidity, barometric pressure, and VOC concentrations. Technical data on the BME680 sensor can be found HERE.
Methods

The BME680 sensor outputs values over serial to the Pico. The readings I am interested in are:

Temperature
Humidity
Gas Resistance
IAQ Value

Methods

Bosch-Sensortec, the maker of this sensor chip, has an library available for performing calculations and interpreting the data (Bosch-Sensortec Environmental Cluster). Unfortunately, the RP2040 processor on the Pico is not compatible with this BSEC library. Therefore, I needed to find a way to convert the raw values for temperature, humidity, and gas resistance into a quantifiable IAQ value for the RP2040 using micropython.

I chose to use the IAQ calculation method from the pimoroni bme680 library, as follows:

rho_max = 6.112 * 100 * math.exp((17.62 * temperature)/(243.12 + temperature)))/(461.52 * (temperature + 273.15))

abs_humidity = humidity * 10 * rho_max

comp_gas = gas_resistance * e^(-0.0304494591240895 * abs_humidity)        

AQ = min((omp_gas/gas_max)^2,1)*100
        
IAQ = (1 - (AQ/100))*500

This provides an IAQ value that can be interpreted by the following classification chart from the BSEC datasheet (Available HERE):

The code running on the Pico is at the end of this post. the driver (bme680iaq.py) is available on my GitHub.

In short, the Pico polls the sensor at 0.33 hz (once every 3 seconds), and records the data every 60 seconds. The data is stored in .csv format in the Pico’s flash memory and includes Temperature, Humidity, Gas Resistance, and IAQ score. Of course, more outputs can be logged for verification purposes.

My research sources can be found below:

Results

The data being taken at this moment is to establish a baseline. This is being done by logging data from other communities which are not exposed to the same air pollution as ours, as well as various indoor environments.

Results and conclusions will be posted here when the experiment is complete.

Notes

One of the advantages to this configuration is that neighborhood-wide deployment is relatively accessible. The total cost for building this sensor is around $25. (Raspberry Pi Pico and BME680 are available from a variety of sources, such as DigiKey, Adafruit, or even Amazon). The data can then be used to generate a “map” for air quality in our community.

To expand the capabilities of this sensor, an air particulate sensor can be added (such as an SPS30 or SEN50-SDN-T from Sensirion). Both sensors can communicate using the I2C bus or SPI, So the same serial lines can be used for all sensors connected to the Pico.

Ideally, all of these capabilities could be addressed with a single module, specifically Sensirion’s SEN55-SDN-T, however at the time of this experiment, they are unavailable in the United States.

Code (micropython)

main.py

#     AQI REFERENCE
#-----------------------------------
#   0 - 50  | EXCELLENT
#  51 - 100 | GOOD
# 101 - 150 | LIGHTLY POLLUTED
# 151 - 200 | MODERATELY POLLUTED
# 201 - 250 | HEAVILY POLLUTED
# 251 - 350 | SEVERELY POLLUTED
# 351 +     | EXTREMELY POLLUTED

# REFERENCES
# https://github.com/G6EJD/BME680-Example (c) d.l.bird 2018
# https://github.com/robert-hh/BME680-Micropython
# https://www.bosch-sensortec.com/media/boschsensortec/downloads/datasheets/bst-bme680-ds001.pdf
# https://forums.pimoroni.com/t/bme680-observed-gas-ohms-readings/6608/17
# https://github.com/thstielow/raspi-bme680-iaq

# My GitHub: https://github.com/natepichler/BME680-Micropython-IAQ

#----------------------------------------
from machine import Pin, I2C
from time import sleep
import math
from bme680iaq import *

#----------------------------------------

# BME680 I2C Interface
#----------------------------------------
i2c = I2C(0, scl=Pin(13), sda=Pin(12))
bme = BME680_I2C(i2c=i2c)
#----------------------------------------

#GPIO 25 LED
#----------------------------------------
led = Pin(25, Pin.OUT)
for _ in range(3):
    led.high()
    time.sleep(.05)
    led.low()
    time.sleep(.5)
    
led.high()
time.sleep(1)
led.low()

gas_max=50000
for _ in range(10):
    print(bme.comp_gas)
    time.sleep(3)
    
for _ in range(2):
    led.high()
    time.sleep(.1)
    led.low()
    time.sleep(.1)

#----------------------------------------

while True:

    #repeat measurement every 3 seconds 10 times (30 Seconds)
    for _ in range(20):
        if bme.comp_gas > gas_max:
            gas_max = bme.comp_gas
            
        AQ = min((bme.comp_gas/gas_max)**2,1)*100
        IAQ = (1 - (AQ/100))*500
    
        if IAQ < 0:
            IAQ = "ERROR"

        if 0 < IAQ <=50:
            IAQ_SCORE = "EXCELLENT"
        
        if 50 < IAQ <= 100:
            IAQ_SCORE = "GOOD"
        
        if 100 < IAQ <= 150:
            IAQ_SCORE = "LIGHTLY POLLUTED"
        
        if 150 < IAQ <= 200:
            IAQ_SCORE = "MODERATELY POLLUTED"
        
        if 200 < IAQ <= 250:
            IAQ_SCORE = "HEAVILY POLLUTED"
        
        if 250 < IAQ <= 350:
            IAQ_SCORE = "SEVERELY POLLUTED"

        if  IAQ > 350:
            IAQ_SCORE = "EXTREMELY POLLUTED"

        print(bme.temperature, bme.humidity, bme.gas, bme.comp_gas, AQ, gas_max, IAQ, IAQ_SCORE)

        time.sleep(3)    
    
    #after 60 seconds, print current values
    print("Temp :",bme.temperature)
    print("%RH :",bme.humidity)
    print("Pressure :",bme.pressure)
    print("Gas Resistance :",bme.gas)
    print("AQI :",IAQ)
    print(IAQ_SCORE)
    print("---------------------------")
    
    #record current values to local file
    file=open("shady1.csv","a")
    file.write(str(bme.temperature)+","+str(bme.humidity)+","+str(bme.gas)+","+str(gas_max)+","+str(IAQ)+"\n")
    file.close()
    #blink light to confirm that the loop is still running
    led.high()
    time.sleep(.05)
    led.low()