Displaying Aranet4 CO2 readings on my website

I recently got an Aranet4 Co₂ monitor and it's a delightful little gadget. It's small and simple and after inserting the 2 AA batteries I could immediately see the CO₂ levels on a clear little screen. I've been told it's also one of the most accurate monitors on the market. Using an unofficial Python library and my Raspberry Pi I was also able to show the measurements on my website. You can skip to the end to see the result. Follow along if you're interested in doing something similar yourself.

Requirements

The setup I'm using involves the following:

• an Aranet4 CO₂ monitor
• a Raspberry Pi
• a PostgreSQL database - I'm using Supabase
• a Next.JS website

Getting started

Install the following packages on your Raspberry Pi:

sudo apt install bluetooth pi-bluetooth bluez blueman

Then use bluetoothctl to pair with your Aranet4:

sudo bluetoothctl
> scan on
> pair $MAC
> scan off

Python script

I adapted the Python script I found on this blog to get the current measurements of my Aranet4 monitor. I’m storing the data in a PostgreSQL database (hosted on Supabase) so that I can easily access it on my website. First, install the Python libraries aranet4 and psycopg2:

pip install aranet4 psycopg2

Then I use the following Python script to store the latest measurement in a PostgreSQL database:

import configparser
import time
import aranet4
import psycopg2
import os
from datetime import datetime

BASE_DIR = os.path.dirname(os.path.abspath(__file__))

config = configparser.ConfigParser()
config.read(os.path.join(BASE_DIR, 'config.ini'))

NUM_RETRIES = int(config['SETTINGS']['num_retries'])
DEVICES = dict(config['DEVICES'])

DATABASE = {
    'database': config['DATABASE']['database'],
    'host': config['DATABASE']['host'],
    'user': config['DATABASE']['user'],
    'password': config['DATABASE']['password'],
    'port': config['DATABASE']['port']
}

def create_table(cursor):
    cursor.execute('''CREATE TABLE IF NOT EXISTS readings(
      device TEXT,
      timestamp INTEGER,
      temperature REAL,
      humidity INTEGER,
      pressure REAL,
      CO2 INTEGER,
      PRIMARY KEY(device, timestamp)
    )''')

def get_readings(mac):
    for attempt in range(NUM_RETRIES):
        try:
            return aranet4.client.get_current_readings(mac)
        except Exception as e:
            print('Attempt', attempt, 'failed, retrying:', e)
    return None

def insert_readings(cursor, name, readings):
    data = (
        name,
        time.mktime(datetime.now().timetuple()),
        readings.temperature,
        readings.humidity,
        readings.pressure,
        readings.co2
    )

    print('Inserting', data)

    cursor.execute(
        'INSERT INTO readings VALUES(%s, %s, %s, %s, %s, %s) ON CONFLICT DO NOTHING', data)

def main():
    with psycopg2.connect(**DATABASE) as conn:
        cursor = conn.cursor()

        create_table(cursor)
        conn.commit()

        for name, mac in DEVICES.items():
            readings = get_readings(mac)
            if readings is not None:
                insert_readings(cursor, name, readings)
                conn.commit()

if __name__ == "__main__":
    main()

The database credentials and configuration for the Aranet4 MAC addresses can be found in the config.ini file. Here's an example:

[DATABASE]
database = postgres
host = db.<your-id-here.supabase.co
user = postgres
password = <your db password here>
port = 5432

[DEVICES]
office = <your-aranet4-address-here>

[SETTINGS]
num_retries = 2

The script runs every minute in a cronjob to make sure the measurements are always up to date.

* * * * * /usr/bin/python3 /home/pi/Code/aranet4/load_data.py >> /home/pi/Code/aranet4/logs/load_data.txt 2>&1
0 9,21 * * * /usr/bin/python3 /home/pi/Code/aranet4/cleanup.py >> /home/pi/Code/aranet4/logs/cleanup.txt 2>&1

As you can see I've also included a cleanup script that deletes any entries older than a day. This is to make sure I don't run out of disk space on my free Supabase subscription.

Result

I'll leave out the front-end code in this tutorial as it is quite straightforward. For those interested in how it works it's a combination of a React component and a Next.JS api route that calls the following service.

Should the levels rise above the recommended threshold of 1000 ppm, don't hesitate to reach out to me on Twitter or Mastodon to remind me to ventilate!