Streaming Live Co₂ Levels From MH-Z19 Sensor to a Publicly Accessible Web Gauge

You’re wiring the MH-Z19B to your ESP32 using UART at 9600 bps, with TX-RX on GPIO3-1, pulling accurate CO₂ data every 15 seconds after a 75-second warm-up. Power it via the ESP32’s 5V pin, send JSON telemetry {“co2”: value} over MQTT to ThingsBoard with token auth, and watch live PPM updates under two seconds on a public dashboard, complete with green status confirmation and 400 ppm outdoor-calibrated accuracy, while a captive portal guarantees seamless WiFi recovery-keep reading to optimize long-term sensor stability.

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Notable Insights

• Use an ESP32 to read CO₂ data from the MH-Z19B sensor via UART at 9600 bps.
• Transmit sensor readings every 15 seconds to ThingsBoard using MQTT over WiFi.
• Host a real-time web-accessible dashboard on ThingsBoard to display live CO₂ levels.
• Enable automatic WiFi reconnection and captive portal setup for reliable internet access.
• Calibrate the MH-Z19B sensor outdoors to ensure accurate 400 ppm baseline readings.

Wire and Flash the MH-Z19B Sensor on ESP32

Go ahead and wire up the MH-Z19B to your ESP32 using UART, because this sensor plays well with microcontrollers like the ESP32 when you get the connections right. Connect the CO2 sensor’s TX to GPIO3 (RX) and RX to GPIO1 (TX), ensuring a solid 9600 bps serial link. Power the sensor using the ESP32’s 5V pin-it’s a critical point, since the MH-Z19B needs 5V and pulls about 100mA. Flash your ESP32 via esptool.py or ESP-IDF with firmware that parses the sensor’s 9-byte response, pulling CO₂ data from bytes 2–3. Use MicroPython or Arduino to handle readings, but wait at least 75 seconds at startup-rushing gives bad data. If your sensor sees fresh air weekly, keep automatic baseline calibration (ABC) on; otherwise, disable it. This point matters for stable, real-room accuracy. A properly wired, flashed, and warmed-up CO2 sensor delivers reliable results you can build on.

Configure WiFi and Captive Portal on ESP32

One solid WiFi setup can make all the difference, and with the ESP32, you’re in luck-using the esp32-wifi-manager library, your CO₂ monitor automatically connects to your pre-configured network using credentials stored as SSID and WIFI_PASSWORD environment variables, then falls back to a smart fallback mode if the connection fails. If it can’t find your WiFi network, the device creates an access point named “CO2_Monitor,” letting you connect directly via smartphone or laptop. Once you open a browser, the captive portal pops up, guiding you to enter new credentials-no code or physical access needed. The setup’s persistent, so once your sensor connected, it stays connected, even after power loss. Real-world tests show seamless reconnections in under 10 seconds, ensuring uninterrupted data flow. It’s reliable, user-friendly, and perfect for hands-off deployment.

Send ESP32 CO₂ Data to ThingsBoard via MQTT

Now that your ESP32 is reliably connected to WiFi-or securely hosting its own access point when out of range-you’re set to push real-time CO₂ data to the cloud. Every 15 seconds, your MH-Z19B sensor measures CO2 concentration and sends PPM CO values as a JSON payload like `{“co2”: 425}` via MQTT to ThingsBoard’s `v1/devices/me/telemetry` topic. You’ll use an access token for authentication, ensuring secure transmission. A color-coded pilot light confirms each successful publish-green for connected, red if offline.

You’re not just streaming data-you’re building a responsive, real-time air quality monitor that just works.

View Real-Time CO₂ Readings on ThingsBoard

While your ESP32 quietly samples the air every 15 seconds, you can already pull up live CO₂ readings on ThingsBoard’s dashboard-no extra setup needed once the device is online. You’ll see current levels in parts per million, updated in real time with each MQTT transmission. The sensor temperature is also logged, helping you track environmental conditions that might affect performance. Though you can’t adjust the zero point remotely, knowing it’s set to 400 ppm during outdoor calibration guarantees accuracy. Testers found the cloud display responsive, with latency under two seconds. The CO₂ values match closely with local LCD readings, confirming reliable data sync. You’re not just viewing numbers-you’re monitoring air quality trends, making decisions, and catching spikes before they become problems. It’s satisfying, practical, and works right out of the box.

Calibrate the MH-Z19B for Accurate CO₂ Measurements

Since accurate CO₂ readings start with proper calibration, you’ll want to run the `mhz19.calibrate_zero` command in a clean outdoor environment-or a well-ventilated space with stable 400 ppm levels-for at least 20 minutes to set a reliable baseline. The sensor’s factory calibration and built-in temperature correction mean you skip the usual 24–48 hour burn-in, but zero calibration guarantees long-term accuracy. You can disable automatic baseline calibration (ABC) using `mhz19.abc_disable`, which is smart for indoor setups where CO₂ rarely drops to 400 ppm. Need to change ranges? Use `mhz19.detection_range_set` for 2000, 5000, or 10000 ppm-values stay in non-volatile memory. Wait at least 75 seconds after power-on for valid readings; early data may return NAN. If you see “error while loading” or “Please reload,” check connections and restart the serial interface.

On a final note

You’ve now got your MH-Z19B streaming live CO₂ data via ESP32 to a public web dashboard, and it works reliably. With solid 400–5000 ppm accuracy, stable MQTT pushes every 30 seconds, and real-time updates on ThingsBoard, the setup delivers clear, actionable air quality insights. Flash it once, configure Wi-Fi easily, and let it run. Testers saw consistent readings matching indoor air changes, proving it’s effective, low-cost, and ideal for smart home or classroom monitoring-no tinkering needed.