Author pete@usefulsensors.com, permanent link is usfl.ink/tcr_dev

The Tiny Code Reader from Useful Sensors is a small, low-cost hardware module that reads QR codes. It's designed to be a simple way to provision a system, for example by providing the wifi network name and password, or to provide input when there's no keyboard.

This guide will explain what information the module can return, how to interpret that information, and how to integrate with a microcontroller like an Arduino or Raspberry Pi. You will need a basic understanding of electronics, enough to integrate a temperature sensor for example, but very little coding is required.

• Getting it Working
  • Connecting
  • Mounting
  • Powering Up
  • Reading Data
• Configuration
• Sensor Characteristics
• Example Code
  • Useful Sensors Examples
    • CircuitPython
    • MicroPython
    • Arduino
    • Raspberry Pi Pico
    • Raspberry Pi
    • Micro:bit
    • Badger 2040
  • Community Examples
• Privacy
• Acknowledgements
• Appendix
  • Data Format
  • C Struct Format
  • Python Data Format Strings
  • CAD File
  • Datasheet
  • Pre-production Modules

Internally the Tiny Code Reader bundles an image sensor and a small microcontroller into a single board, but to make it as easy as possible to build into products we’ve tried to hide those implementation details. It returns information about any QR codes it sees over an I2C connection.

The board uses a standard Qwiic connector for the I2C interface. This is designed so you can only plug it in one way, but the individual lines are shown in the diagram below for reference. You can find more information about this form factor at SparkFun’s Qwiic page, but it’s now widely supported by a lot of vendors, including with Adafruit’s Stemma QT connector. SparkFun also have a guide for connecting to a Raspberry Pi, and another for Arduino Nanos. If you're using a standard connector, the wire colors are yellow for SCL, blue for SDA, red for 3.3V, and black for GND.

The sensor supports I2C bus speeds of up to 400k baud. We expect 3.3V power, other voltage levels are not supported.

The sensor uses an image sensor internally, so you need to make sure that the lens has a clear field of view. It can be mounted in any orientation, that shouldn't affect the code recognition quality. There's a mounting hole for a screw in the top left, and some alternative pads in case you don't want to use a QWIIC connector but want to wire in directly. The edge with these pads is designed to snap off, in case you need to reduce the size of the board further.

Before you start trying to read information from the sensor, a good first step is to power it up and make sure it seems to be working correctly. To do this connect the GND and 3.3V lines from your microcontroller to the sensor. If you’re using a Qwiic socket on the MCU you’ll also be connecting the SDA and SDC automatically, but if you’re breaking out to individual pins don’t worry about them yet. With the sensor powered, bring up a simple QR code on your phone and place it about fifteen centimeters or six inches in front of the module, facing the camera. You should see the LED on the front of the board rapidly flashing blue, and then turn green when the QR code is detected. It may take a bit of wiggling and moving back and forth to get a detection.

Once you have the sensor connected and mounted, you’ll want to start reading information from it. The code you use to do this will depend on the platform you’re using for the main controller device, but here’s some C example code for a Raspberry Pi Pico. The 7-bit peripheral address for the sensor is 0x0C, or 12 in decimal. Please note that some systems include the read/write bit in the address, making the 8-bit peripheral address 0x18 or 0x19.

if (!tiny_code_reader_read(&results)) {
    printf("No code results found on the i2c bus\n");
    sleep_ms(SAMPLE_DELAY_MS);
    continue;
}

if (results.content_length == 0) {
    printf("No code found\n");
} else {
    printf("Found '%s'\n", results.content_bytes);
}

This shows how you read data from the peripheral. That data is a 16-bit unsigned integer containing the length of the read QR code content, followed by the content itself in a 254 byte array. If no QR code has been seen in the last scan period, the length will be zero, and so will the content array. If the length is greater than zero, any bytes after the end of the content will be set to zero, guaranteeing a zero-terminated string.

The content will typically be a UTF-8-encoded Unicode string, but it's not guaranteed to be. As with all user inputs, you should sanitize and escape it before using it for anything sensitive. You can think of the reader like an input box on a website - users can enter whatever they want so it's important to check if you're using it to control system behavior.

The only behavior that's configurable is the module's LED. By default it flashes blue while scanning, green when a valid QR code has been detected, and red when there was an error decoding the QR code. By writing 0x00 to register address 0x01 you can turn the LED off entirely.

The module relies on an image sensor and computer vision to read QR codes, so it does require some illumination to work. The image sensor doesn’t include an IR filter, so using near-IR illumination from an LED should be possible in situations where visible light is not available, but we haven’t characterized the accuracy of the sensor in those conditions.

The reader works best with comparatively simple QR codes (20 characters or less) but the only hard limit on the size is the 254 byte content array. The module is designed to be small and low cost, and so will not have the same accuracy and range of larger, more expensive commercial readers.

The sensor has approximately a 110 degree field of view.

The model runs about five times a second. The latency is approximately the time to perform one model iteration, so roughly 200 milliseconds. There's no pin raised raised when a QR code is found, so you will need to keep polling to catch recognitions.

This version of the board requires 3.3V input, and consumes about 100 milliwatts of power (with about 5mW going to the LED when active).

We have written samples for some of the most popular development platforms.

github.com/usefulsensors/tiny_code_reader_circuit_python

github.com/usefulsensors/tiny_code_reader_trinkey_keyboard

github.com/usefulsensors/tiny_code_reader_wifi_micropython

github.com/usefulsensors/tiny_code_reader_arduino

github.com/usefulsensors/tiny_code_reader_pico_c

github.com/usefulsensors/tiny_code_reader_micro_bit

github.com/usefulsensors/tiny_code_reader_badger

We also love to feature projects created by makers, so if you'd like to see your guide, tutorial, or GitHub repo featured here, please send us a pull request adding it to this section of the documentation. We also collect maker guides at our Hackster project hub.

This module includes an image sensor, and we want to make sure that this doesn’t pose a threat to any of our users’ privacy. We’ve designed the module so that it is as resistant as possible to anyone accessing the raw image data, and only the metadata derived from each frame is available. We’ve also built it to have as slim an interface as possible, to reduce the possibility of malicious interference and make it simpler for third parties to audit our privacy claims.

This approach does constrain what developers can do with the device. One obvious restriction is that we don’t allow you to access the image data, but we also don’t support flashing the firmware or model updating, because doing so could allow unchecked changes to the sensor’s behavior. Even though there’s a microcontroller on the board, we’re hoping that you’ll be able to get enough value out of its pre-programmed behavior to compensate for the inconvenience of this user protection approach.

If you’re interested in learning more about this approach to system design, we have a research paper describing what we call Machine Learning Sensors.

This module uses an RP2040 MCU from Raspberry Pi to run the QR code recognition. It's been a great piece of hardware to work with, with more RAM and compute than anything else in its class.

We have found the zxing-cpp a very well-written and maintained source of information on barcode decoding in general and QR codes in particular. Useful Sensors is proud to be a sponsor of the project and we encourage anyone who finds these sensors useful to do so too.

Lee Jackson at Arducam has been a fantastic help sourcing high-quality, low-cost camera modules. If you need imaging solutions for your microcontroller projects I highly recommend talking to him.

The inference result is stored as an array of bytes in the following format. Information about each member is described in detail above.

The most up to date versions of these data structures can be found at github.com/usefulsensors/tiny_code_reader_pico_c/blob/main/person_sensor.h, but for reference here is a C struct version of the data format. The non-standard but commonly supported packed attribute is used to ensure no extra padding is introduced.

typedef struct __attribute__ ((__packed__)) {
    uint16_t content_length;
    uint8_t content_bytes[254]
} tiny_code_reader_results_t;

A complete CircuitPython example of decoding the sensor data can be found at github.com/usefulsensors/tiny_code_reader_circuit_python/blob/main/code.py, but the format strings for struct decoding can be summarized as:

TINY_CODE_READER_LENGTH_FORMAT = "H"
TINY_CODE_READER_MESSAGE_SIZE = 254
TINY_CODE_READER_MESSAGE_FORMAT = "B" * TINY_CODE_READER_MESSAGE_SIZE
TINY_CODE_READER_I2C_FORMAT = TINY_CODE_READER_LENGTH_FORMAT + TINY_CODE_READER_MESSAGE_FORMAT

Here is a STEP file containing a model of the sensor.

Here is a datasheet containing technical specifications for the module.

Ahead of the full release we have given away a limited number of prototype modules with slightly older firmware versions. If you have bought a module, then it will be the final release version, but if you have received one of the pre-production versions through a contest of giveaway, it should function in a very similar way. Here are the differences:

• The LED will be brighter, flashes green instead of blue, and there's no option to disable it.
• The 256 byte result structure doesn't contain zeroes after the main message content. The contents are undefined, so you'll need to be careful to take the valid substring rather than decoding and relying on a zero terminator. All of the example code should handle this.