Category: BleuIO

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

• Adafruit Feather RP2040 board
• BleuIO Pro – Bluetooth Low Energy USB dongle
• USB cable for the Feather
• USB-A port or hub for the BleuIO dongle
• Computer running Windows, macOS or Linux

Software

• Arduino IDE with RP2040 board support installed
• Adafruit TinyUSB Library
• Pico PIO USB Library
• ArduinoJson library
• Python 3.x and the Python project that connects to BleuIO over SPS

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"}
----

3. 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.

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.

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

• BleuIO USB BLE dongle
• HibouAir air quality monitor with particle sensor

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.

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

• A BleuIO USB dongle
• A HibouAir CO2 sensor
• A Google account (for Sheets and Apps Script)

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');
}

3. Replace YOUR_SHEET_ID_HERE with your sheet’s ID — it’s the long string between /d/ and /edit in your Sheet URL.
4. Click Deploy → New Deployment → choose Web app.
5. Under settings:
   • Execute as: Me
   • Who has access: Anyone with the link
6. 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:

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.