Have you ever wanted to stream real-time air quality data from a Bluetooth sensor straight into the cloud — without any expensive gateway or IoT server? In this tutorial, we’ll show you how to use the BleuIO USB dongle and a HibouAir sensor to capture CO2, temperature, and humidity readings over Bluetooth Low Energy (BLE), then automatically log them into Google Sheets for easy tracking and visualization.
By the end, you’ll have a live data logger that updates your Google Sheet every few seconds with real environmental readings — and you’ll even learn how to create charts directly inside Google Sheets.
What is Google Sheets?
Google Sheets is a free, cloud-based spreadsheet application that lets you create, edit, and share data online in real time. It’s part of Google’s Workspace tools and is accessible from any device with an internet connection. Because it stores data in the cloud, it’s ideal for data logging, quick testing, and lightweight analysis — especially for IoT projects. You can capture sensor readings, visualize trends with charts, and even connect Sheets to other platforms like Google Looker Studio or BigQuery for deeper analytics. For developers and makers, Google Sheets serves as an excellent starting point for collecting and analyzing data without needing a dedicated server or database.
// ===== CONFIG =====
const SPREADSHEET_ID = 'YOUR_SHEET_ID_HERE'; // from your sheet URL
const SHEET_NAME = 'data'; // tab name
// ==================
function doPost(e) {
const sheet = SpreadsheetApp.openById(SPREADSHEET_ID).getSheetByName(SHEET_NAME);
if (!e || !e.postData || !e.postData.contents) {
return ContentService.createTextOutput('NO_BODY');
}
let payload = JSON.parse(e.postData.contents);
const rows = Array.isArray(payload) ? payload : [payload];
const toRow = o => [
o.timestamp || new Date().toISOString(),
Number(o.CO2),
Number(o.temperature),
Number(o.humidity)
];
const values = rows.map(toRow);
sheet.getRange(sheet.getLastRow() + 1, 1, values.length, values[0].length).setValues(values);
return ContentService.createTextOutput('OK');
}
Replace YOUR_SHEET_ID_HERE with your sheet’s ID — it’s the long string between /d/ and /edit in your Sheet URL.
Click Deploy → New Deployment → choose Web app.
Under settings:
Execute as:Me
Who has access:Anyone with the link
Click Deploy, then copy the Web app URL. This will be your WEBHOOK_URL.
Step 3 — Install Python Libraries
Open your terminal (or PowerShell) and install the required dependencies:
pip install pyserial requests
These will let Python talk to the BleuIO dongle and send HTTPS requests to Google Sheets.
Step 4 — Connect and Configure the BleuIO Dongle
Plug in your BleuIO USB dongle.
On macOS, it will appear as something like /dev/cu.usbmodemXXXX.
On Windows, it will show up as COMX.
You can list serial ports to confirm:
ls /dev/cu.usbmodem* # macOS
or
Get-WMIObject Win32_SerialPort | Select-Object DeviceID,Name # Windows
Step 5 — Run the Python Script
Now we’ll use a Python script that handles the entire process automatically. The script first connects to the BleuIO dongle and sets it to central mode using the AT+CENTRAL command, which allows it to scan for nearby BLE devices. It then searches for HibouAir BLE advertisements using the AT+FINDSCANDATA=220069=3 command, which filters packets matching the HibouAir sensor’s unique identifier. Once it receives a valid advertisement, the script decodes the CO2, temperature, and humidity values from the data packet. Finally, it packages these readings along with a timestamp and pushes them to your Google Apps Script webhook, which automatically logs them into your Google Sheet.
Open your Google Sheet. You’ll see new rows appear every few seconds:
timestamp
CO2
temperature
humidity
2025-10-10T14:48:07.849Z
514
23.8
46.1
Step 7 — Create Charts in Google Sheets
Once your data is flowing into Google Sheets, you can easily visualize it without using any external tools. Start by highlighting the range of data you want to analyze, then go to Insert → Chart in the menu. Google Sheets will automatically suggest a chart type, but you can switch to a Line Chart or Combo Chart to better visualize trends over time. For a more dashboard-like view, you can also add a Gauge Chart to display real-time values for CO₂ or temperature. Customize the chart’s colors, titles, and formatting to match your preferences, and adjust refresh settings so your visuals update automatically as new data arrives.
And that’s it! You’ve built a real-time BLE air-quality logger with BleuIO and Google Sheets — no servers, no databases, no fuss. This setup is perfect for classrooms, offices, or research labs that need quick, visual environmental monitoring.
Use Cases
This project demonstrates how you can use BleuIO and Google Sheets to quickly prototype and test IoT ideas. For example, it’s perfect for indoor air-quality monitoring in offices, classrooms, or labs, allowing you to observe changes in CO₂ levels, temperature, and humidity over time. Researchers can use it to log environmental data during experiments or field studies. It’s also useful for IoT developers who want to validate BLE sensors or test new device firmware without setting up a backend system. Teachers can turn this setup into an educational project, helping students understand Bluetooth communication, data logging, and visualization. Overall, pairing BleuIO with Google Sheets offers a fast, free, and flexible way to monitor and analyze real-world sensor data.
Whether you’re analyzing indoor air quality, tracking sensor performance, or just exploring IoT data pipelines, BleuIO makes BLE integration simple and powerful.
In this project, we’ll show how to build a real-time air quality monitoring system using the BleuIO USB dongle and Ubidots. The setup listens for Bluetooth Low Energy (BLE) advertising packets from a HibouAir sensor, decodes the CO2, temperature, and humidity data, and sends them directly to Ubidots, where you can visualize and analyze the readings on a live dashboard.
The result is a seamless pipeline from BLE sensor to Ubidots’ cloud platform. This makes it easy to track air quality in real time and share the results with colleagues, clients, or your own IoT applications.
What is Ubidots?
Ubidots is a powerful industrial IoT platform designed to help developers, researchers, and businesses transform raw sensor readings into meaningful insights. More than just a place to store data, Ubidots provides tools to build custom dashboards, alerts, and reports that can be shared across teams or even embedded into products. It is widely used in industries such as smart cities, agriculture, energy, logistics, and healthcare, where real-time monitoring and automation are critical.
By integrating BleuIO with Ubidots, you gain the ability to collect real-time BLE sensor data without the need for complex gateways. The values captured from your sensors can be pushed directly to Ubidots variables through simple HTTPS POST requests, making the process both fast and reliable. Once the data is in Ubidots, you can take advantage of its powerful dashboard features to create professional visualizations with gauges, charts, and triggers, giving you an intuitive way to monitor and analyze your environment.
In short, BleuIO acts as the BLE gateway, and Ubidots becomes the visualization and analytics layer.
HibouAir Sensor – broadcasts CO2, temperature, and humidity.
Python libraries: pip install pyserial requests
Ubidots account (a free version is available).
Ubidots API Token – used to authenticate when posting data to your account.
The Script and How It Works
We’ve written a Python script that automates the whole process from BLE scan to Ubidots push. You can find the full code on GitHub: GitHub Link for Script
Here’s how the script works step by step:
Connects to the BleuIO dongle over the serial port you specify (e.g., /dev/cu.usbmodemXXXX on macOS or COMX on Windows).
Switches the dongle into central mode with the AT+CENTRAL command (done only once).
Scans for HibouAir packets using AT+FINDSCANDATA=220069=3, which looks for advertising data that matches HibouAir’s manufacturer ID.
Selects the last valid packet that contains the expected pattern (5B070504). This ensures we work with the freshest data.
Decodes the advertising data into usable values:
CO in parts per million (ppm).
Temperature in Celsius (°C).
Humidity in relative percent (%RH). The script also applies sanity checks to ignore invalid readings.
Pushes the values to Ubidots via HTTPS POST requests. The request format looks like this: { "co2": { "value": 415 }, "temperature": { "value": 23.4 }, "humidity": { "value": 52.1 } } Each key (co2, temperature, humidity) becomes a variable in Ubidots.
The script repeats this process every 10 seconds, so your dashboard stays updated in real time.
This approach keeps everything lightweight and avoids any need for complex backend servers or brokers.
Output
Once the script is running, your Ubidots device (e.g., bleuio-hibouair) will automatically appear in the Devices section. It will have variables for CO2, temperature, and humidity.
Use Cases
This project can be applied in many real-world scenarios where air quality and environmental monitoring are essential. For example, it can be used for indoor air quality monitoring in offices, classrooms, or laboratories to ensure a healthy environment for occupants. In smart building management, the integration of CO₂ and temperature readings into HVAC systems can help optimize ventilation and energy use. The approach also fits perfectly into cold chain logistics, where continuous temperature and humidity tracking is critical for maintaining the safety and quality of sensitive shipments. In the field of environmental research, this setup provides a quick and reliable way to capture and visualize field data without the need for heavy infrastructure. Finally, it is also ideal for IoT prototyping, as Ubidots makes it easy to build dashboards and visualize sensor data quickly without writing or maintaining a backend system.
With just a BleuIO dongle, a BLE sensor, and a few lines of Python, you can build a real-time IoT dashboard in Ubidots. This project demonstrates how easy it is to collect, decode, and visualize BLE data without needing extra hardware or complicated setups.
This project shows how to turn a BleuIO USB dongle into a tiny gateway that streams live air-quality data from a HibouAir sensor straight to Adafruit IO. The script listens for Bluetooth Low Energy (BLE) advertising packets, decodes CO2, temperature, and humidity, and posts fresh readings to your Adafruit IO feeds every few seconds. The result is a clean, shareable dashboard that updates in real time—perfect for demos, labs, offices, classrooms, and proofs of concept.
What is Adafruit IO—and why pair it with BleuIO?
Adafruit IO is a cloud platform for makers and developers that lets you collect, visualize, and route device data using a simple REST API or MQTT. You don’t need any Adafruit hardware; if you can make an HTTPS request, you can send data. BleuIO fits in beautifully here: the dongle handles the BLE side—scanning and parsing sensor frames—while a short Python script formats those values and pushes them to Adafruit IO. In practice that means you can take any BLE-advertising sensor, translate its packets into numbers, and land them on an IoT-friendly dashboard without servers or containers.
Requirements
To complete this project, you will need:
BleuIO BLE USB Dongle – acts as the BLE central device to capture advertising packets.
Adafruit IO Key – available under your account’s “My Key” page for authentication.
How it works
When you start the script, it opens the BleuIO serial port and switches the dongle into central role the very first time the program runs. From then on it repeatedly performs a short BLE scan that filters for HibouAir advertising frames. The scanner always picks the latest matching packet and decodes the fields we care about: CO2 (ppm), temperature (°C), and humidity (%rH). The script then posts each value to its own Adafruit IO feed over HTTPS. Because Adafruit IO is designed for live IoT data, your dashboard widgets update as soon as new points arrive. The loop cadence is configurable (10 seconds by default), which keeps you comfortably under Adafruit IO’s free-tier request limits.
The code (key points)
The script is intentionally small and readable. It opens the serial device (for example /dev/cu.usbmodemXXXX on macOS or COM7 on Windows), sends the BleuIO commands to scan for a few seconds, and parses the returned “Device Data [ADV]” lines.
A compact decoder extracts CO2, temperature, and humidity from the HibouAir manufacturer data, including the byte order and scaling.
To make the setup painless, credentials are read from variables (AIO_USER, AIO_KEY) and feed names default to co2, temperature, and humidity. Each value is sent to the REST endpoint /api/v2/{username}/feeds/{feed_key}/data with a simple JSON body {"value": <number>}.
The script includes gentle sanity checks (for example, temperature range and humidity bounds) to ignore any malformed frames, and it prints a concise log line each time it pushes fresh data.
Here is the GitHub link with the full source so you can clone and run it as-is or adapt it to other sensors.
How to run the code
Before running, set your serial port and Adafruit IO credentials.
On macOS you can list ports with ls /dev/cu.usbmodem*;
on Windows use Device Manager to find the COM number. Update username and AIO key information, then run the script. The program will put BleuIO into central mode on first launch and, every cycle, will scan, decode, and push CO2, temperature, and humidity to the three feeds. If you see an HTTP 401 error, double-check the AIO key; a 404 usually means a feed name typo. If the script can’t open the serial port, confirm the path and that no other program is holding it open.
Creating Adafruit IO feeds, key, and dashboard
Log in to Adafruit IO and create three feeds named co2, temperature, and humidity. Your AIO Key is available under your account’s “My Key” page; copy it and keep it private. With feeds in place, open the Dashboards section and create a new dashboard for this project (for example, “HibouAir Live”). Add a few blocks: a gauge or line chart for CO₂ (with a range that makes sense for your space), another gauge or slide for temperature, and a slide or line chart for humidity so you can see the trend over time. Each block points to its corresponding feed. As the script posts to those feeds, the blocks will animate and refresh automatically. You can reorder blocks, tweak colors and ranges, and share a read-only link if you want others to watch along.
Output
Once everything is connected, the dashboard shows a live CO2 number in gauge an line chart, an updating temperature value, and a humidity box that advances with each new reading. The values move in near real time as the script cycles, and any spikes or changes in air quality appear immediately.
Use cases
Real-time air-quality dashboards are useful in far more places than a lab bench. Facility manager can watch CO2 levels across meeting rooms to optimize ventilation; schools and libraries can surface temperature and humidity alongside occupancy schedules; small manufacturers can keep an eye on comfort and safety in production spaces; and hobbyists can monitor their home offices or studios. Because the pipeline is “BLE sensor → BleuIO → HTTPS → Adafruit IO,” you can swap HibouAir for other BLE advertisers and reuse the same approach to visualize anything from soil moisture to ambient light.
This project highlights how quickly you can go from BLE broadcast to live cloud dashboard with BleuIO and Adafruit IO. There’s no server to maintain, no container to deploy—just a tiny USB dongle, an air quality monitoring device like HibouAir, a short Python script, and a few clicks on the Adafruit IO site. The result is a shareable, real-time view of your environment that’s easy to extend, brand, and automate.
In this project, we demonstrate how to stream Bluetooth Low Energy (BLE) sensor data directly into Microsoft Power BI using the BleuIO USB dongle. By combining a HibouAir environmental sensor with BleuIO and a simple Python script, we can capture live readings of CO2, temperature, and humidity and display them in real time on a Power BI dashboard.
The goal of this project is to make BLE data visualization simple and accessible. Instead of dealing with complex server setups or containers, BleuIO provides an easy way to turn raw BLE advertising packets into meaningful insights that anyone can understand at a glance.
Why Power BI?
Microsoft Power BI is a business analytics platform designed to turn raw data into interactive dashboards and reports. One of its most powerful features is the ability to handle real-time streaming datasets, allowing live updates from sensors or IoT devices.
For IoT developers and organizations, this is a game-changer. Imagine watching air quality readings from your office appear in real time, or combining BLE sensor data with other business metrics to get a fuller picture of your environment. By using BleuIO as a BLE-to-cloud bridge, developers can integrate IoT data into Power BI dashboards quickly, without heavy infrastructure.
Toggle Historic data analysis ON if you want Power BI to store rows for reporting.
Save the dataset and copy the Push URL that Power BI generates. This will look something like: https://api.powerbi.com/beta/.../datasets/{id}/rows?key=...
This Push URL is what the Python script will use to send live sensor data to your dashboard.
The Script
We wrote a Python script that takes care of the entire process. Once it starts, the script connects to the BleuIO dongle through the serial port and switches it into central mode (this is done only the first time it runs). From then on, it performs a BLE scan every 10 seconds, specifically looking for HibouAir sensor advertising data. When the sensor is found, the script decodes the broadcast payload into CO2, temperature, and humidity values. These values are then packaged into the required JSON format and pushed directly to Power BI, where they appear instantly on your dashboard.
Before running the script, make sure to update two important details:
Dongle port location: On macOS it will look like /dev/cu.usbmodemXXXX, while on Windows it will appear as COMX.
Power BI Push URL: Use the one you generated earlier during the dataset setup.
With the script running and sending live data, the next step is to build your Power BI dashboard.
Go to My workspace in Power BI and click New → Dashboard.
Give the dashboard a descriptive name, for example HibouAir Live Data.
Select + Add a tile → Custom streaming data, then choose the dataset you created earlier.
Pick a visualization type that suits your needs:
A Card to display the current CO₂ value.
A Gauge to track temperature within a target range.
A Line chart to watch humidity changes over time.
Map the fields (CO2, temperature, humidity, timestamp) to each visual and pin them to your dashboard.
Within seconds of running the script, you’ll see live sensor readings begin to appear in your Power BI dashboard — updating automatically with every scan.
Output
Here’s what the final result looks like when the dashboard starts receiving data from the HibouAir sensor.
Use Cases
This project shows just one way to use BLE and Power BI together, but the possibilities are broad. For example, you could build air quality monitoring dashboards in offices, schools, or factories to help maintain healthier environments. In agriculture, farmers could create smart dashboards that combine soil and environmental sensors to optimize crop conditions. The same method can be applied to cold chain logistics, where monitoring temperature and humidity is essential for transporting food or medicine. Fitness and health enthusiasts could stream real-time data from BLE wearables into personal dashboards, making progress more visible and motivating. And for developers, Power BI is an excellent tool for rapid IoT prototyping, offering instant visualization of new sensor data without building a complex backend system.
With BleuIO and Microsoft Power BI, it’s easy to transform BLE sensor broadcasts into live dashboards. This integration makes it possible to visualize environmental data in real time, share insights instantly, and build prototypes faster than ever before. Whether you’re a developer, researcher, or business professional, combining BLE sensors with Power BI opens the door to smarter, data-driven decisions.
This tutorial walks you through a tiny, privacy-first web app that reads only the advertised CO2 level from a nearby HibouAir sensor using a BleuIO USB BLE dongle. There’s no pairing, cloud, or backend—just your browser, the dongle, and a page that decodes a numeric CO2 value broadcast in BLE advertisements and renders it as a color bar (default window 400–2000 ppm) with a simple “High CO2” warning when your threshold is crossed.
A single HTML file that talks to BleuIO over the Web Serial API. The page puts BleuIO in the central role, periodically runs a targeted scan for your HibouAir Board ID, and parses the Manufacturer Specific Data (MSD) bytes in each advertisement to extract CO2 (ppm). The value drives a horizontal gradient bar; cross the threshold and a warning banner appears. Everything runs locally in the browser.
Try it now:Live demo on GitHub Pages — plug in BleuIO, and press Connect. Make sure to pass correct HibouAir Board ID
Why a CO2-only, browser-based monitor?
CO2 is a practical proxy for ventilation. Elevated levels are associated with stale air, drowsiness, and reduced productivity. Many spaces—meeting rooms, classrooms, offices, homes—benefit from quick visual feedback so people know when to air out the room. Reading only a single, device-computed number from BLE advertisements keeps the design simple, fast, and privacy-preserving.
BLE devices periodically broadcast short advertisement packets with real-time CO2 values. We can read them without pairing.
This page filters to a specific Board ID, captures the advertisement line, extracts the longest hex payload, and then decodes CO2 from a fixed position inside the MSD. The result is mapped to a 0–100% fill of the bar (for a display window of 400–2000 ppm), and we show a banner when CO2 ≥ threshold (default 1000 ppm).
Below is the exact function used in this project:
function decodeCo2FromAdv(hex) {
// sanitize → bytes
hex = (hex || '').replace(/[^0-9A-F]/gi, '');
if (hex.length % 2) hex = hex.slice(0, -1);
const b = new Uint8Array(hex.length / 2);
for (let i = 0; i < b.length; i++) b[i] = parseInt(hex.substr(i*2,2), 16);
// locate MSD anchor and read CO2 at fixed offset (big-endian)
for (let i = 0; i <= b.length - 5; i++) {
if (b[i] === 0x5B && b[i+1] === 0x07 && b[i+2] === 0x05) {
const idx = i + 23; // CO2 MSB position in this layout
if (idx + 1 < b.length) {
return (b[idx] << 8) | b[idx+1]; // ppm
}
}
}
return null;
}
The BLE flow
When you click Connect, the page opens a serial session to BleuIO and sends:
AT+CENTRAL once, to enter scanning mode
AT+FINDSCANDATA=<BOARD_ID>=3 every cycle to run a 3-second targeted scan
The reader consumes lines until BleuIO prints SCAN COMPLETE, then waits and repeats
Each time an advertisement arrives, the page extracts the hex payload, decodes CO2, updates the bar, and toggles the High CO2 banner if the threshold is exceeded.
Output
You’ll see a horizontal color bar labeled with the current CO2 ppm. The bar fills from left to right as values rise within the 400–2000 ppm window. A bold High CO2 banner appears when the reading crosses your threshold (default 1000 ppm), serving as a polite nudge to improve ventilation.
Use cases
This simple CO2 bar works well anywhere people gather and air can get stale. In meeting rooms and classrooms it provides a live cue to crack a window or switch on ventilation as occupancy rises. In open offices it nudges teams toward timely air exchanges, helping reduce stuffiness and afternoon dips in alertness. At home it’s a lightweight way to keep bedrooms and living spaces fresh during gatherings or winter months with closed windows. Shared studios and makerspaces also benefit from quick, ambient feedback without the overhead of dashboards or wall displays.
Because the app reads only a single numeric value that HibouAir already broadcasts, it avoids handling personal data and is easy to deploy in privacy-sensitive environments.
Accuracy & practical notes
This is a lightweight indicator, not a calibration tool. CO2 readings in advertisements update periodically and represent the sensor’s current value. Placement matters: keep your HibouAir within a reasonable range of BleuIO to reduce missed packets. If your environment regularly exceeds the default window, you can adjust the display range and threshold in the code.
Extend the project
You can grow this prototype in several practical directions. Start by logging readings to CSV or IndexedDB for simple trend analysis over days or weeks. If you have multiple sensors, add a multi-device view that scans several Board IDs and presents compact tiles in one page. For automation, trigger a webhook or send a serial command to control a fan or relay whenever CO2 exceeds your threshold. You can also pair it with the earlier Noise Bar and show Noise + CO2 side-by-side for a fuller picture of comfort and productivity.
This guide shows how to create a web-only Flutter application that talks to a BleuIO USB BLE dongle directly from the browser. The app is a minimal console: click Connect, send AT commands like AT+CENTRAL or AT+GAPSCAN=3, and watch responses appear in real time. Treat it as a starting point for richer BLE web apps—dashboards, scanners, or device tools—without native installs.
The focus is Flutter for the web. Instead of a mobile build, you’ll run Flutter in the browser and use the Web Serial API to communicate with BleuIO. The included script acts as an example of how to open the serial port, send AT commands, and stream lines back into a Flutter UI. You can use the same pattern to build any BLE-adjacent web app: scan for devices, filter output, parse manufacturer data, or add visualizations—completely in Flutter Web.
How it works
Flutter Web can call browser APIs through dart:html and dart:js_util. The app asks Chrome/Edge to show the serial-port picker, opens the selected BleuIO port at 115200, and writes commands terminated by \r\n. A small pre-newline and micro delays are used so commands don’t concatenate (avoiding errors like AT+CENTRALA). A read loop collects bytes, splits them into lines, and renders them into a console-style panel. Everything runs locally in the browser; nothing is recorded or sent to a server.
Guide
Create a web-only Flutter app
From Terminal, create a project that targets only the web so you don’t see iOS/Android code-sign prompts:
flutter create --platforms=web bleuio-flutter
cd bleuio-flutter
You’ll run exclusively against Chrome (or Edge). No mobile setup is needed.
Select Chrome as the build target
Use Chrome so the Web Serial API is available:
flutter run -d chrome
If you use an IDE, choose Chrome (web) in the device selector. Safari is not supported for Web Serial.
Add the example script
Open lib/main.dart and replace its contents with the example from the repository. That file defines a tiny Web-Serial service (connect, writeLine, continuous read loop) and a simple UI with a status, quick command buttons, a custom command input, and a full-width terminal output.
Try live commands
Click Connect BleuIO and choose your dongle. Send ATI to verify, then AT+CENTRAL to enter central role, and AT+GAPSCAN=3 to perform a three-second scan. The responses stream into the on-page console immediately. Because it’s just AT over serial, you can experiment with any command that BleuIO supports.
Understanding the example
The script is intentionally small so you can lift it into other projects. The service wraps Web Serial and exposes a line stream you can subscribe to from widgets. The UI is a single page that prints lines to a terminal-style view and keeps the scroll pinned to the bottom.
Extending this into a BLE web app
Once you’re comfortable with the console, you can add features that turn it into a BLE tool. Start by parsing common outputs such as GAP scan lines into structured objects with fields like address, RSSI, and name. Add filters and search to highlight target devices.
Use cases
This web-only approach is ideal for demos, workshops, and quick bring-up labs where you want a zero-install experience. It’s handy for field diagnostics when you need to peek at advertisements, confirm firmware state, or prove connectivity from any machine with Chrome. It also serves as a foundation for privacy-respecting dashboards that only read broadcast data and never require native packaging.
The live page streams output as soon as the device is connected. You can keep the tab open as a lightweight serial console while developing other features.
Flutter Web is a great fit for BLE-adjacent tooling when you want the reach of a URL and the feel of a native UI. Start with the example console today, then grow it into the BLE web application your project needs.
In this tutorial, we demonstrate how to connect the BleuIO Bluetooth Low Energy dongle to the Waveshare RP2350A USB Mini development board to create a dual-mode USB serial bridge. This example highlights the process of communicating with BleuIO using AT commands via USB host mode. It serves as a great starting point for anyone looking to build their own BLE application using this compact and powerful board.
About the Waveshare RP2350A USB Mini
The Waveshare RP2350A USB Mini is a development board built around the Raspberry Pi RP2350 microcontroller. It features a dual-core architecture, combining ARM Cortex-M33 and RISC-V Hazard3 cores, running at up to 150 MHz. The chip includes 520KB of SRAM and 2MB of onboard flash, making it suitable for advanced embedded applications.
What sets this board apart is its USB-A connector with support for USB host mode, allowing it to communicate directly with USB peripherals like the BleuIO dongle. This makes it an ideal host controller for Bluetooth Low Energy (BLE) applications.
Project Overview
This project demonstrates a dual-mode USB serial bridge implemented on the RP2350A board. The bridge allows the board to simultaneously function as:
A USB host using PIO-USB on GPIO 12/13, connected to a device like BleuIO.
A USB device, appearing as a virtual COM port when connected to a PC.
Data is transparently forwarded between the host and device interfaces, allowing you to communicate with BleuIO from a terminal on your PC.
This example project is useful for anyone looking to build a standalone USB host application using BleuIO. You can use the source code as a base and expand it into a more complex BLE project by sending and receiving AT commands directly from the RP2350A board.
Use Case
Imagine a scenario where you want to build a small, embedded BLE sensor gateway. Using the RP2350A as a USB host and BleuIO as the BLE interface, you can develop a powerful BLE solution without needing a full-sized computer. This approach is ideal for prototyping custom BLE applications, sensor data acquisition, or even building a mini BLE scanner.
In host mode, the RP2350 board uses PIO-USB to emulate USB host functionality on GPIO pins 12 (D+) and 13 (D-). You can connect any CDC-compatible device, such as a USB-to-serial adapter or the BleuIO dongle, to these pins.
Once connected, the application automatically detects and configures the device. All incoming and outgoing serial data is forwarded and can be monitored through the debug UART interface.
Device Mode (Native USB Port)
When the RP2350A’s native USB port is connected to your PC, it appears as a virtual serial port. This allows you to communicate with the BLE dongle (connected via host mode) using a terminal application like PuTTY or Tera Term.
This enables full-duplex communication, letting you send AT commands to BleuIO and receive responses directly from your PC.
Debug Output (UART on GP0/GP1)
To observe internal debug messages, connect a UART adapter to GPIO 0 (TX) and GPIO 1 (RX) with a baud rate of 115200. This output includes information such as device enumeration, data flow, and potential errors—essential for troubleshooting and development.
Building the Project
To build the firmware, you can either use the provided build script or follow a manual setup.
You can find the complete source code for this project on GitHub:
mkdir build && cd build cmake .. -DCMAKE_BUILD_TYPE=Release make -j4
After building, a rp2350_serial_bridge.uf2 file will be generated.
Flashing the Firmware
Hold the BOOTSEL button on the RP2350 board and connect it to your PC via USB.
The board will mount as a USB mass storage device.
Copy the generated rp2350_serial_bridge.uf2 file to this drive.
The board will reboot and start running the dual-mode USB bridge application.
You can now insert the BleuIO dongle into the USB-A port of the RP2350A board and begin communication from your PC.
Code Structure
main.c – Main entry point of the application.
serial_host_bridge.c/h – Handles the USB CDC host implementation.
tusb_config.h – TinyUSB configuration file.
CMakeLists.txt – Build configuration for CMake.
Getting Started with Your Own BLE App
This project is just a starting point. It demonstrates how to set up USB host/device mode and communicate with a CDC-based USB dongle like BleuIO. From here, you can extend the code to parse responses, interact with BLE devices, or trigger actions based on received data.
By combining the flexible RP2350A platform with BleuIO, developers can create their own powerful standalone BLE applications for IoT, sensors, or industrial control—without relying on a full computer.
Source Code
You can find the complete source code for this project on GitHub:
Indoor air quality is an important factor in workplace health, home comfort, and industrial safety. Monitoring CO2, particulate matter, temperature, humidity, and other environmental metrics can help prevent health issues, optimize HVAC usage, and maintain compliance with building standards. In this tutorial, we’ll walk through building a complete air quality monitoring solution using the BleuIO USB dongle and the HibouAir BLE sensor. We’ll use Python to collect data, InfluxDB to store it, and Grafana to visualize it in real time.
This project works entirely offline, runs on both macOS and Windows, and is suitable for personal, educational, or professional use. Whether you want to monitor a home office or manage sensors in an industrial setup, this system is simple to deploy and easy to scale.
What You Need
You will need one BleuIO USB dongle and one HibouAir BLE sensor. These two devices form the core of the setup. The BleuIO dongle will connect via a serial port and act as a BLE Central, continuously scanning for BLE advertisement packets sent by the HibouAir sensor.
For software, you’ll need Python 3, InfluxDB, and Grafana, all of which are available for both macOS and Windows. You’ll also install a few Python packages (pyserial and influxdb) to allow your script to read data over the serial port and write it to the database.
About Grafana
Grafana is an open-source analytics and visualization platform designed to display time-series data. It integrates seamlessly with databases like InfluxDB, allowing users to create interactive and customizable dashboards. In this project, Grafana serves as the front end for visualizing live air quality data coming from the HibouAir sensor. Its intuitive interface and support for powerful queries make it ideal for monitoring environmental conditions over time, setting alerts, and gaining actionable insights from BLE sensor data.
macOS Installation
On macOS, it’s easiest to install tools using Homebrew. You can install everything with the following commands:
Make sure Python and pip are added to your system path. You can then install Python packages via:
pip install pyserial influxdb
Also, identify your BleuIO COM port by opening Device Manager and checking Ports (COM & LPT). You’ll see something like COM3, which you’ll use in the Python script.
Setting Up InfluxDB
After installing InfluxDB, you need to create a database that will store sensor readings. On macOS, open your terminal. On Windows, use Command Prompt or PowerShell.
To enter the InfluxDB CLI:
influx
Inside the CLI, run:
> CREATE DATABASE hibouair > SHOW DATABASES > EXIT
This creates a database called hibouair, which your Python script will use to log environmental data.
You don’t need to set up authentication for local testing. If you do secure your instance later, remember to update Grafana and the Python script with your username and password.
Configuring Grafana
Once Grafana is installed and running, open your browser and go to:
http://localhost:3000
The default username and password are:
Username: admin Password: admin
After logging in, you’ll be asked to set a new password. Once you’re in the Grafana dashboard:
Go to Settings → Data Sources
Click Add data source
Choose InfluxDB
Set the following:
URL: http://localhost:8086
Database: hibouair
User and Password: leave empty unless you’ve enabled authentication
HTTP Method: GET or POST (default is fine)
Click Save & Test
You should see a success message confirming Grafana can read from InfluxDB.
Connecting BleuIO via Serial Port
Insert your BleuIO USB dongle.
On macOS, find the port using: ls /dev/cu.usbmodem* Example: /dev/cu.usbmodem4048FDEBA6D01
On Windows, check Device Manager → Ports (COM & LPT) and find something like COM3 or COM4.
This port will be used in your Python script to open a serial connection to the dongle.
The Python Script
The Python script initializes the BleuIO dongle in Central mode, sends a scan command (AT+FINDSCANDATA), and reads the BLE advertisement packets from the HibouAir sensor. The data, which arrives in hexadecimal format, is decoded to extract values like temperature, humidity, CO2, VOC, PM1, PM2.5, PM10, light, noise, and pressure. The script then writes this data to InfluxDB with a timestamp.
To avoid storing duplicate values, the script only logs the first valid reading per scan cycle. It waits for a configurable period (e.g., 20 seconds) before scanning again.
You can view and copy the complete Python script from the GitHub repository linked below.
Make sure to replace the serial port path and board ID in the script with your actual values.
Creating a Dashboard in Grafana
With data flowing into InfluxDB, it’s time to visualize it in Grafana. Start by creating a new dashboard:
From the left menu, go to Dashboards → New → Add new panel
In the query editor, select your InfluxDB data source
Enter the following query to display CO2 levels: SELECT last("co2") FROM "air_quality" WHERE $timeFilter GROUP BY time($__interval)
This query fetches the latest CO2 readings from the air_quality measurement. You can change "co2" to "temp", "hum", "voc", "pm25" or any other field depending on what you want to display.
Grafana will automatically plot the data on a line chart. You can switch to a gauge, bar, or other visualizations from the panel settings. You can also set thresholds, value ranges, and colors to improve readability.
Repeat this process to add more panels for temperature, humidity, VOCs, PM2.5, PM10, and other values.
Once your dashboard is complete, click Apply, then Save the dashboard to reuse it later.
Output
How It Works
This system leverages BLE advertisement broadcasting from HibouAir and AT command-based serial communication with the BleuIO dongle. The dongle scans for a specific board ID using AT+FINDSCANDATA=<board_id>=3, and the Python script reads and decodes each advertisement received. The decoded data is immediately sent to InfluxDB using the official client library.
Grafana queries this time-series data and displays it in real time. Since all components are local, there is no dependency on external servers or cloud APIs. The system is also modular, so you can easily scale it to support multiple sensors, extend the decoder for other BLE formats, or forward data to cloud-based platforms in the future.
Use Cases
This setup is ideal for a range of applications. In an office environment, monitoring CO2 and humidity can help optimize ventilation and improve productivity. In factories or workshops, tracking particulate matter and VOCs ensures air quality compliance and safety. For researchers and students, this project provides a hands-on, local, and open-source method to study environmental changes. Even in residential settings, it can help detect poor air circulation or pollutant spikes. The simplicity of this solution makes it accessible to both developers and non-developers alike.
Extending the Project
There are several ways to expand this project:
Add support for additional BLE data types, such as HibouAir’s type 08 advertisements for NO₂
Set up Grafana alerts to notify you when CO2 exceeds 800 ppm or humidity drops below 30%
Export historical data from InfluxDB to CSV for offline analysis
Run the Python script as a background service on system boot
Connect multiple sensors to cover multiple rooms or areas
With minimal changes, you can also run this setup on a Raspberry Pi or Linux server.
With just a BleuIO dongle, a HibouAir sensor, and a few open-source tools, you’ve built a fully functional air quality monitoring solution. The system is flexible, lightweight, and runs entirely offline. It provides real-time insights into indoor environmental conditions and can be adapted for a variety of applications.
Node-RED, a flow-based development tool for visual programming, has become a favorite among IoT developers for rapidly building and testing automation workflows. In this article, we explore how to use BleuIO, a Bluetooth Low Energy (BLE) dongle, within Node-RED to interact with BLE devices like HibouAir—an affordable and reliable air quality monitoring sensor.
We will demonstrate:
How to send BLE commands to BleuIO and read back data
How to scan for BLE advertisements from a HibouAir device
How to decode and display real-time air quality data like CO2, temperature, and humidity on a live dashboard
By the end, you’ll have a working Node-RED BLE setup using BleuIO and a HibouAir sensor.
What is Node-RED?
Node-RED is an open-source, flow-based programming tool built on Node.js. It offers a browser-based visual interface that allows developers to connect hardware devices, APIs, and services using prebuilt “nodes.” Originally developed by IBM, Node-RED has grown into one of the most accessible platforms for prototyping and building IoT and automation solutions.
What makes Node-RED especially appealing is its simplicity. Without needing to write complex code, developers can drag and drop logic blocks and wire them together to build powerful flows. It supports a wide range of protocols, including MQTT, HTTP, and—through serial communication. With its real-time data handling, debugging tools, and powerful dashboard feature, Node-RED becomes an ideal choice for BLE-based IoT projects like this one.
What is HibouAir?
HibouAir is a compact and affordable air quality monitoring device developed by Smart Sensor Devices. Designed for both indoor and outdoor use, it transmits real-time environmental data over Bluetooth Low Energy (BLE), making it easy to integrate into any smart environment. The sensor measures key air quality parameters such as CO2, temperature, humidity, particulate matter (PM1.0, PM2.5, PM10), VOCs, light intensity, noise levels etc. This simplicity makes it a perfect fit for developers and system integrators working with platforms like Node-RED, where data can be read, decoded, and visualized in minutes.
What We Built
We built a flow in Node-RED that:
Sends an AT command to put BleuIO in central role (AT+CENTRAL)
Sends a scan command to search for HibouAir devices (AT+FINDSCANDATA)
Reads the advertisement data from a known board ID (e.g., 220069)
Decodes the BLE hex payload using a custom decoder function
Extracts and displays live air quality values (CO2, temperature, humidity) in the dashboard
Requirements
To replicate this project and visualize air quality data using Node-RED and BleuIO, you’ll need the following hardware and software:
BleuIO Dongle
A plug-and-play USB Bluetooth Low Energy (BLE) dongle that supports AT commands over serial. Get BleuIO
HibouAir Sensor
An affordable air quality monitoring device that broadcasts environmental data via BLE advertisements. Get HibouAir
Node-RED
A low-code flow-based development tool to wire together devices, APIs, and services. Node-RED Installation Guide
Tip: You can install Node-RED globally via npm:
npm install -g --unsafe-perm node-red
Node-RED Dashboard
An additional Node-RED module used to create UI dashboards. Dashboard GitHub Repo Install it with:
cd ~/.node-red npm install node-red-dashboard
HibouAir Decoder Script
A Node.js-based decoding script that extracts sensor values from BLE advertisement data.
A serial in node reads back raw BLE advertisements. These are filtered and passed through a custom decoder only if they match a specific prefix like 5B0705 and contain the HibouAir board ID.
3. Decode Payload
We placed a hibouair-decoder.js script next to settings.js and loaded it globally using:
The decoder function parses the hex payload into human-readable sensor values.
4. Show on Dashboard
Finally, we use dashboard gauge widgets to show live values:
CO2 in ppm
Temperature in °C
Humidity in %RH
The Node-RED dashboard UI gives a beautiful, real-time snapshot of your air quality.
Live Dashboard
Live readings of CO2, temperature, and humidity.
A snapshot of the working Node-RED flow using BleuIO and HibouAir.
Use Cases
This solution opens doors for a wide variety of applications. In smart classrooms, it ensures students learn in environments with healthy air quality, which can significantly affect concentration and wellbeing. In modern office spaces, monitoring CO2 and temperature helps facilities maintain optimal working conditions, improving both productivity and comfort.
For developers and researchers, this integration offers an easy way to prototype BLE applications, decode custom advertisements, and visualize data with minimal setup. Environmental agencies or facility managers can use this same setup for on-site testing and audits without needing cloud connectivity.
Even at home, you can deploy this as a DIY setup to monitor indoor air conditions and get real-time alerts when CO2 levels get high due to poor ventilation.
What You Can Do Next
Now that you have a live setup showing CO2, temperature, and humidity from HibouAir on a Node-RED dashboard, the possibilities for extending this flow are endless.
To store and track trends, you can add a chart node that logs values over time. This enables historical analysis of indoor air conditions, which is useful for compliance, optimization, or just awareness.
If you’re concerned about thresholds, consider adding a switch node that triggers alerts—say, if CO2 levels rise above 1000 ppm or the temperature exceeds 30°C. This could be used to turn on ventilation or send a mobile notification.
You might also want to persist data to a local SQLite database or forward readings to a cloud-based API for further processing or sharing. This transforms your flow into a powerful edge gateway.
Finally, you can export the complete flow as a template, allowing colleagues, customers, or community users to import it directly and start monitoring with their own HibouAir and BleuIO setup.
Try It Yourself
You can import the full Node-RED flow here and start using it with:
Just install Node-RED, load this flow, and you’ll start seeing real-time air quality readings in your browser dashboard.
This tutorial shows how BleuIO seamlessly integrates with platforms like Node-RED to help developers quickly build BLE-powered applications. Combined with a device like HibouAir, this setup makes monitoring air quality simple, affordable, and accessible—without any advanced hardware or coding requirements.
We encourage you to extend this example, share your flows, or reach out to us with new ideas. BLE development doesn’t have to be hard. With BleuIO and Node-RED, it’s just a few clicks away.
Monitoring environmental data in real time is becoming increasingly important, whether you are tracking air quality in an office, monitoring home conditions, or running a smart city project. With the BleuIO dongle and a BLE-enabled sensor like the HibouAir, it is remarkably simple to gather this data and share it with the world in a format that is open, accessible, and easy to consume.
This project demonstrates how you can turn BLE advertisement data into a live-updating RSS feed. The result is a transparent, shareable, and continuously updated stream of environmental measurements that anyone can subscribe to, whether they are using a standard RSS reader, a smart home dashboard, or an industrial system.
Project Overview
At its core, this project uses the BleuIO dongle to scan for BLE advertising packets from a HibouAir environmental sensor. The HibouAir broadcasts valuable metrics such as temperature, humidity, pressure, and CO2 levels over BLE advertisements. Instead of relying on a local desktop application or complicated server-side setups, this project leverages the power of modern browsers using the Web Serial API to connect directly to the BleuIO dongle over the USB port.
Once connected, the user can trigger BLE scans from within the browser. The scan runs every 30 seconds, decoding the broadcasted data in real time. Each new data point is sent to a lightweight PHP script on the server, which stores and appends the data in an RSS feed (rss.xml). This RSS file is immediately accessible to any subscriber or reader, allowing people to see live updates on the environmental conditions around the sensor.
The entire system is designed to be simple and easy to maintain. The frontend is styled with Tailwind CSS to ensure a responsive, polished interface. The user can connect, start scanning, stop scanning, and instantly visualize decoded data in a clear, scrollable log area.
Requirements
To build and run this project, you will need the following:
Permissions to write to rss.xml (you may need to set proper file permissions on your server)
How It Works
The project flow is straightforward. First, the user plugs the BleuIO dongle into their machine. Using the Web Serial API, the web page establishes a secure, permission-based connection with the dongle, sending standard AT commands to initiate scanning. The page decodes the advertising data using JavaScript, translating raw BLE packets into readable environmental measurements.
Every 30 seconds, a scan command is sent, retrieving the most recent advertising broadcasts. When a valid HibouAir packet is detected, the temperature, humidity, pressure, and CO2 values are extracted, timestamped, and then posted to the server using a simple JSON POST request. The PHP script running on the server receives these decoded values and appends them to the existing RSS feed. The result is a continually growing XML feed that any RSS reader can parse and display.
This approach removes the need for any heavy backend logic or traditional data pipelines. With the combination of the BLE advertisement protocol, the Web Serial API, and the simple power of RSS, the system remains robust, efficient, and fully open-standard.
Real-World Use Cases
There are many practical applications for this type of BLE-to-RSS feed system. In a smart building, it can provide real-time updates on air quality for facilities managers. Research labs can monitor and record environmental changes over time, sharing data with collaborators instantly. Homeowners could integrate the feed with smart thermostats or ventilation systems, optimizing air quality dynamically based on conditions broadcast by the HibouAir.
This approach is also perfect for educational settings, where students can learn about BLE communication, environmental sensors, and open-standard data sharing in a single, hands-on project. For communities or public-facing projects, the RSS feed provides a transparent, shareable view of conditions in a local area, encouraging citizen science or public environmental monitoring.
Why This Matters
Traditionally, BLE data collection has required local scripts, drivers, and other installation-heavy methods. Thanks to the Web Serial API, this entire solution can run in the browser, with no software to install apart from a modern web browser. The user grants permission to the serial port, connects the dongle, and can immediately start scanning, decoding, and sharing data.
By pushing this data into a simple RSS format, you gain compatibility with a huge ecosystem of readers and dashboards without reinventing the wheel. RSS is universal, easy to parse, and instantly shareable. This means a single HibouAir board and a BleuIO dongle can power an environmental feed accessible to anyone, anywhere.
Getting Started
This project is easy to set up. You only need a BleuIO dongle, a HibouAir board, a standard PHP-capable web server, and a modern web browser such as Chrome. The HTML page includes everything needed to connect to the dongle, issue scan commands, and decode results using JavaScript. Tailwind CSS ensures the user interface is polished and responsive.
After decoding, the environmental data is posted to a PHP script which appends it to an RSS feed file. From there, any visitor or RSS reader can subscribe to see the latest measurements. There is no complex backend, no cloud account, and no paid services — just a clean, standards-based solution that you can host yourself.
Source Code
The full project source code — including the HTML, JavaScript, PHP, and Tailwind-powered frontend — is available on GitHub. You can download, modify, or extend it as needed for your use case.
Feel free to clone the repository, fork it, and contribute improvements or suggestions.
Output
This project shows how BleuIO, in combination with Web Serial and simple RSS technology, can deliver an impressive, real-time environmental data feed. With minimal setup and a truly modern web-first architecture, you can build a robust, transparent, and shareable monitoring system in just a few hours.
If you are looking to explore BLE scanning, build a real-time environmental monitor, or simply share sensor data with the world in an open way, this project is a perfect starting point. Give it a try, and transform your local BLE sensors into a globally available data feed that anyone can use.
