Integrating BleuIO with Adafruit Feather RP2040 for Seamless BLE Applications – Part 5 (Two-Way Communication)

In the earlier parts of this series, we combined the Adafruit Feather RP2040 with the BleuIO USB dongle to build different BLE applications: setting up the RP2040 as a USB host, reading sensor data, advertising measurements and handling secure connections.

In this Part 5, we take the next step and create a simple two-way communication setup. Instead of only broadcasting data, we let a Python script running on your computer talk to the BleuIO dongle connected to the Feather RP2040 and control its LED in real time. At the same time, the Feather responds over the Serial Port Service (SPS), echoing messages back so you can see exactly what was sent on both sides.

This project is a good starting point if you want to remotely control devices, test custom BLE command protocols or build interactive demos using BleuIO and RP2040.

What This Project Does

Arduino project on Adafruit Feather RP2040

On the hardware side, the Adafruit Feather RP2040 is configured as a USB host for the BleuIO dongle, using the same TinyUSB and Pico PIO USB approach as in Part 1 of the series. When the board starts, it initializes the USB host stack, detects the BleuIO dongle and sends a short sequence of AT commands. These commands disable echo, ask the dongle for its own MAC address, set a friendly advertising name (BleuIO Arduino Example) and start BLE advertising. After that, the sketch simply listens for BLE connection events and SPS messages. Depending on what text message it receives over SPS, it either echoes the message back or sends a command to change the LED behaviour on the dongle.

Python script on the computer

On the computer, a Python script acts as the BLE central. It uses the MAC address printed by the Feather’s serial output to connect to the advertising BleuIO dongle. Once connected, it sends text commands over SPS such as ALERT, NORMAL or OFF, and reads back whatever the Feather sends in response. When the Python script sends one of these special words, the Feather generates BLEU AT commands to control the dongle’s LED; for any other text, it just echoes the message. This creates a complete round-trip: you type in Python, the message travels over BLE to the RP2040 and BleuIO, and a response comes back the same way.

Requirements

Hardware

Software

If you already followed Part 1, your RP2040 USB host environment and board configuration should be ready to use.

Source Code on GitHub

You can find the complete source code for this project — both the Arduino sketch and the Python script — in our public GitHub repository: bleuio_arduino_message_transfer_example. Visit the repository at:

https://github.com/smart-sensor-devices-ab/bleuio_arduino_message_transfer_example

Feel free to clone or download the repo to get started quickly. All necessary files — including the .ino, helper headers, and the Python script — are included, so you can replicate the example or adapt it for your own project.

Recap: Preparing the Feather RP2040 as a USB Host

To quickly recap the setup from the earlier article: you install the Raspberry Pi RP2040 board package in the Arduino IDE, select the Feather RP2040 board, and install the Adafruit TinyUSB and Pico PIO USB libraries. You then make sure the CPU speed is set to 120 MHz or 240 MHz, since Pico PIO USB requires a clock that is a multiple of 120 MHz.

Uploading the Arduino Sketch

  1. Open the bleuio_arduino_connect_example.ino and usbh_helper.h in the same Arduino sketch folder.
  2. Select Adafruit Feather RP2040 (or your RP2040 board) under Tools → Board.
  1. Choose the correct COM port for the Feather.
  2. Click Upload.

After upload:

  1. Open Serial Monitor at 9600 baud.
  2. You should see something like:
Connect test v1.0
Core1 setup to run TinyUSB host with pio-usb
SerialHost is connected to a new CDC device. Idx: 0

BleuIO response:
{"own_mac_addr":"xx:xx:xx:xx:xx:xx"}
----
  1. Every 10 seconds (based on ALIVE_TIME) you’ll see an update:
H:M:S - 0:0:10
own_mac_addr: xx:xx:xx:xx:xx:xx
Not connected!

Initially it will say Not connected! because no BLE central is connected yet.

The Python Script (BLE Central)

The Python script acts as a BLE central that connects to the advertising BleuIO dongle and uses the Serial Port Service (SPS).

A typical flow in the Python script is:

  1. Read the MAC address printed by the Arduino Serial Monitor (own_mac_addr).
  2. Use the BleuIO Python library (or BLE stack) to connect to that address.
  3. Once connected, send plain text messages over SPS:
    • "ALERT"
    • "NORMAL"
    • "OFF"
    • Or any other text.

On the Python side you’ll see:

  • Connection success message.
  • Any SPS response sent from the RP2040 (e.g. [RP2040] Alert command Received: [...] or [RP2040] Echo: ...).

On the Arduino Serial Monitor you’ll see:

Connected!
SPS Received!
BleuIO response:
{"type":"SPS","evt":{"len":5,"ascii":"ALERT"}}
----
Sending command: AT+SPSSEND=[RP2040] Alert command Received: [ALERT]

And the LED on the BleuIO dongle will react according to the command:

  • ALERT → Blink pattern (AT+LED=T=100=100).
  • NORMAL → Toggle LED (AT+LED=T).
  • OFF → Turn LED off (AT+LED=0).
  • Any other message → Just an echo, no LED change.

Where to Go Next

This example completes the journey from simple advertising to full two-way communication between a computer application and a BleuIO dongle hosted by an Adafruit Feather RP2040. With this pattern in place, you can replace the LED commands with your own device protocol, combine it with the sensor examples from Part 2 and Part 4, or feed the exchanged messages into larger systems for logging, dashboards or control logic. Because the communication relies on the standard Serial Port Service and BleuIO AT commands, the same structure can be reused for many other projects where a PC, an embedded board and a BLE device need to work together.

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How AI Makes BLE Development Even Easier with BleuIO

Bluetooth Low Energy (BLE) has become a key technology in modern wireless applications—from IoT devices and sensors to wearables, smart tools, and more. While BLE development can traditionally require time, experience, and familiarity with complex protocols, BleuIO dramatically simplifies the process.

BleuIO is a powerful USB BLE dongle designed to help developers of all levels build BLE applications quickly and efficiently. With straightforward AT commands, intuitive documentation, and cross-platform flexibility, it allows users to prototype and develop BLE solutions without the usual learning curve.

But now, with the rapid growth of AI tools such as ChatGPT and Gemini, the development workflow becomes even smoother. AI can help generate ready-to-run scripts, automate coding tasks, and speed up BLE experiments—making the combination of BleuIO + AI incredibly valuable for developers.

Common Challenges in BLE Development

Developing Bluetooth Low Energy applications often requires a solid understanding of BLE protocols and command structures, which can be intimidating for beginners. Developers must also write code that interfaces correctly with hardware such as dongles or embedded devices, and this process can involve repetitive boilerplate code—especially when handling tasks like scanning, connecting, and transferring data. Another common challenge is ensuring that code works consistently across different languages and platforms. These factors can slow down development and create barriers for those who simply want to prototype or test BLE functionality quickly.

How BleuIO and AI Solve These Problems

BleuIO addresses many of these challenges by offering straightforward AT commands that simplify common BLE operations. When paired with modern AI tools, the development process becomes even more efficient. AI systems can read the BleuIO AT Command List and instantly generate complete scripts that integrate these commands correctly, significantly speeding up prototyping. This eliminates the need for manually writing repetitive code, allowing developers to focus on their application rather than the setup. Because BleuIO works seamlessly with Python, JavaScript, C#, Node.js, and many other environments, developers can choose the language they prefer. Even newcomers can get started easily, as AI-generated scripts help bridge any knowledge gaps and provide a smooth entry point into BLE development.

Example: Using ChatGPT and Gemini to Generate a BLE Scan Script

To demonstrate how effectively BleuIO and AI work together, we created a simple test scenario. We began by downloading the BleuIO AT Command List PDF from the Getting Started guide and then asked both ChatGPT and Gemini to generate a Python script that communicates with the BleuIO BLE USB dongle. The script needed to use the correct AT commands, include the appropriate COM port, and perform a scan for nearby BLE devices lasting five seconds. After generating the scripts, we ran them to compare the output produced by the two AI tools.

Video Demonstration

You can watch the full demonstration below, where we walk through the entire process—from downloading the command list to generating and testing the scripts:

This example demonstrates just how powerful the combination of BleuIO and modern AI tools can be. By letting AI generate boilerplate code and BLE scripts, you can focus on building features, testing ideas, or integrating wireless communication into your products.

BleuIO already makes BLE development easy—but with AI, it becomes even more efficient, accessible, and developer-friendly.

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Ambient-Adaptive Particulate Monitor (PM1.0 / PM2.5 / PM10) with BleuIO & HibouAir

Outdoor air quality is a major focus in Europe in 2025, with tighter standards placing greater emphasis on fine particulate matter—especially PM2.5. Elevated PM levels are linked to asthma, reduced cognitive performance, and increased cardiovascular risk, making reliable monitoring essential. This project demonstrates a simple, browser-based way to visualize PM1.0, PM2.5, and PM10 in real time—supporting better ventilation decisions and aligning with evolving EU air-quality expectations.

What you’ll build

A single HTML file styled with Tailwind CSS that:

  • Puts BleuIO in a central scanning role
  • Periodically runs a targeted scan for your HibouAir Board ID
  • Decodes PM1.0 / PM2.5 / PM10 from the manufacturer data inside BLE advertisements
  • Maps the values to three horizontal bars (default display windows: PM1.0/PM2.5 → 0–150 µg/m³, PM10 → 0–200 µg/m³)
  • Shows a high particulate banner when any value exceeds your thresholds

Source code: https://github.com/smart-sensor-devices-ab/pm-monitor-bleuio
Live demo: https://smart-sensor-devices-ab.github.io/pm-monitor-bleuio/

Hardware & software

How it works

HibouAir broadcast short advertisement packets that includes real-time air quality data. We can read them without pairing.

Scan cadence. The dongle sends:

  • AT+CENTRAL once to enter scanning mode
  • AT+FINDSCANDATA=<BOARD_ID>=3 every cycle to run a 3-second targeted scan
  • It reads lines until BleuIO prints SCAN COMPLETE, then waits and repeats

Decoding. HibouAir advertises a compact environmental frame beginning with the marker 5B 07 05. PM values are 16-bit little-endian fields. In this build we anchor to the marker and read:

  • PM1.0 (raw ÷ 10 → µg/m³)
  • PM2.5 (raw ÷ 10 → µg/m³)
  • PM10 (raw ÷ 10 → µg/m³)

UI behavior. Each metric drives a bar that fills left-to-right as the value rises within its display window. Thresholds are configurable (defaults: PM1.0 1, PM2.5 2, PM10 5 µg/m³). If any metric is at or above its threshold, the page shows “High particulate levels detected.”

Customize & extend

You can tailor this monitor to your space and workflow in several practical ways. If you anticipate larger spikes, widen the display windows—for example, expand PM2.5 to 0–200 µg/m³—to keep the bar responsive at higher ranges. For lightweight analytics, append readings to a CSV file or store them in IndexedDB to explore trends over hours or days. If you’re tracking multiple HibouAir units, build a wallboard that scans a list of Board IDs and renders compact tiles for each sensor in a single view. To act on thresholds, add automation hooks that trigger a webhook or drive a fan/relay from a companion script when levels rise. Finally, pair this particulate display with your existing CO₂ or Noise monitors to create a more complete picture of indoor conditions and ventilation effectiveness.

Output

In the video , the session starts at 0.0 µg/m³ across PM1.0/PM2.5/PM10. To demonstrate responsiveness, we briefly spray aerosol near the HibouAir device. Within seconds, the bars respond and the page displays “High particulate levels detected.” After stopping the aerosol and allowing air to clear, values decay back down, the bars recede, and the banner disappears. This sequence illustrates typical behavior you’ll see during quick particulate events (e.g., cleaning sprays, dust disturbances, smoke from cooking) and their recovery.

This project turns HibouAir’s BLE adverts into a clear view of PM1.0, PM2.5, and PM10 using a BleuIO dongle. In minutes, you get live bars, thresholds, and a simple alert that makes particulate spikes obvious. It’s easy to tune—adjust display windows, tweak thresholds, and adapt the layout for different rooms. As EU air-quality expectations tighten, this lightweight monitor helps you spot issues and validate ventilation quickly. From here, you can add data export, multi-device dashboards, or pair it with your CO2 monitor for a fuller picture.

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Log Real-Time BLE Air Quality Data from HibouAir to Google Sheets using BleuIO

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.

What You’ll Need

You’ll also need a few Python libraries, which we’ll install below.

Step 1 — Set Up Your Google Sheet

We’ll use Google Sheets as our cloud storage for the data.

  1. Go to Google Sheets and create a new spreadsheet.
  2. Name it something like BleuIO_HibouAir_Data.
  3. Rename the first tab to data.
  4. In the first row, add the following headers: timestamp, CO2, temperature, humidity

Step 2 — Create a Google Apps Script Webhook

Next, we’ll build a small Google Apps Script that accepts POST requests and appends data to your sheet.

  1. Open https://script.google.com/home and click New Project.
  2. Paste this code into the editor:
// ===== 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');
}
  1. Replace YOUR_SHEET_ID_HERE with your sheet’s ID — it’s the long string between /d/ and /edit in your Sheet URL.
  2. Click Deploy → New Deployment → choose Web app.
  3. Under settings:
    • Execute as: Me
    • Who has access: Anyone with the link
  4. 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.

📂 GitHub Repository: View Source Code on GitHub

Before running, update:

  • SERIAL_PORT → your BleuIO port
  • WEBHOOK_URL → your Google Apps Script Web App URL

Step 6 — Watch Your Data Flow!

Open your Google Sheet. You’ll see new rows appear every few seconds:

timestampCO2temperaturehumidity
2025-10-10T14:48:07.849Z51423.846.1

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.

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Connecting BleuIO to Ubidots: A Practical Industrial IoT Air Quality Solution

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.

Requirements

To complete this project, you’ll need:

  • BleuIO USB Dongle – to capture BLE advertising packets.
  • 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:

  1. Connects to the BleuIO dongle over the serial port you specify (e.g., /dev/cu.usbmodemXXXX on macOS or COMX on Windows).
  2. Switches the dongle into central mode with the AT+CENTRAL command (done only once).
  3. Scans for HibouAir packets using AT+FINDSCANDATA=220069=3, which looks for advertising data that matches HibouAir’s manufacturer ID.
  4. Selects the last valid packet that contains the expected pattern (5B070504). This ensures we work with the freshest data.
  5. 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.
  6. 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.
  7. 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.

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Real-Time BLE Air Quality Monitoring with BleuIO and Adafruit IO

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.
  • HibouAir Air quality monitor – broadcasts environmental data such as CO2, temperature, and humidity.
  • Python libraries – install them with: pip install pyserial requests
  • Adafruit IO account – free to sign up at io.adafruit.com.
  • 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.

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Streaming BLE Sensor Data into Microsoft Power BI using BleuIO

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.

Requirements

To follow this tutorial, you will need:

  • A BleuIO USB dongle.
  • A HibouAir air quality monitor (for CO2, temperature, and humidity).
  • A free or paid Microsoft Power BI account.
  • The Python libraries pyserial and requests, which can be installed with: pip install pyserial requests

Setup: Power BI Streaming Dataset

Before writing any code, we need to set up a streaming dataset in Power BI.

  1. Log in to Power BI Service and go to My workspace.
  2. Select New → Streaming dataset → API.
  3. Define the fields you’ll collect from the sensor:
    • CO2 (Number)
    • temperature (Number)
    • humidity (Number)
    • timestamp (DateTime or Text)
  4. Toggle Historic data analysis ON if you want Power BI to store rows for reporting.
  5. 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.

We’ve published the full script on GitHub here:
GitHub Link for Script

To run it:

python script.py

Setup Dashboard

With the script running and sending live data, the next step is to build your Power BI dashboard.

  1. Go to My workspace in Power BI and click New → Dashboard.
  2. Give the dashboard a descriptive name, for example HibouAir Live Data.
  3. Select + Add a tile → Custom streaming data, then choose the dataset you created earlier.
  4. 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.
  5. 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.

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Ambient-Adaptive CO2 Bar with BleuIO & HibouAir

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.

This project is a follow-up to the Ambient-Adaptive Noise Bar with BleuIO & HibouAir. We reused the same structure and UI, but swap the decoder to read CO2 instead of noise.

What you’ll build

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.

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.

Hardware & software

How it works (at a glance)

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.

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Build a BLE Web App in Flutter Using BleuIO

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.

Requirements

What this post is about

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.

Source code & demo

Repository:
https://github.com/smart-sensor-devices-ab/bleuio-flutter

Live demo (open in Chrome/Edge, connect your dongle, and try AT commands):
https://smart-sensor-devices-ab.github.io/bleuio-flutter/

Output, hosted and real time

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.

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Using BleuIO with Waveshare RP2350A USB Mini Based On Raspberry Pi RP2350A 

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.

Hardware Requirements

Software Requirements

Host Mode (PIO-USB on GPIO 12/13)

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:

GitHub Repository: bleuio-rp2350

Method 1: Using the build script

cd rp2350_serial_bridge
./build.sh

Method 2: Manual build with CMake

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

  1. Hold the BOOTSEL button on the RP2350 board and connect it to your PC via USB.
  2. The board will mount as a USB mass storage device.
  3. Copy the generated rp2350_serial_bridge.uf2 file to this drive.
  4. 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:

GitHub Repository: bleuio-rp2350

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