• Recognize QR-codes with the least amount of cameras.
  • Achieve a scan speed.
  • QR-codes backlighting using LED.
  • OTA firmware updates through the mobile applications.


  • Full day of battery life.
  • No OpenCV library.
  • QR-codes backlighting using LEDs.
  • Flexible scanning algorithm configuration via the developed configuration file.
  • Measurement speed.
  • OTA firmware updates through the mobile application.


The Embrox team decided to use the Raspberry Pi 3 Model B with the Arducam Multi-Camera Adapter in order to be able to connect a few cameras.

We proposed the simplest approach based on a transistor switch in order to have the possibility to use an LED strip for capturing QR codes and turning LED strips off when light is not needed.

The electrical engineering team developed a custom battery gauge and power PSB.

The mechanical engineering team suggested using mirrors to reduce the device thickness.

All cameras work in multithreading with async handling.

The scanned data goes to the mobile application via BL connection. Later, this data gets to the server.


The Embrox team met all non-functional requirements and successfully delivered the prototype.

What our team says?

about project

Employee image

What our team says?

about project

Results image
target audience
The target audience of this smart case is farmers who harvest medium or large yield. They are in need of technological solutions in order to track the amount of harvested yield and send it to the office as quickly as possible. This optimises work and reduces the number of errors and inaccuracies.