Scanning Suitcase
CHALLENGES
- QR-codes recognition with the fewest number of cameras.
- Achieving high scanning speed.
- QR-codes backlighting using LED.
- OTA firmware updates through mobile applications.
KEY FEATURES
- Full day on a single charge (up to 3 with optimized usage).
- Efficient QR code recognition without relying on the OpenCV library.
- LED backlighting for accurate QR code scanning in various environments.
- Flexible scanning algorithms via the developed configuration file.
- Rapid measurement for efficient data collection.
- OTA firmware updates through the app.
- Fast scan feedback.
- Paralel items scanning - 8 units at a time.
- Custom QR decoder.
- Advanced camera system with a unique mirror placement solution.
- Custom and ergonomic mechanical case for field work.
OUR APPROACH
To achieve efficient QR code recognition, we utilized a Raspberry Pi 3 Model B with an Arducam Multi-Camera Adapter. This setup allows for multiple camera connections and optimized scanning performance.
We implemented a transistor switch to control the LED strip for QR code backlighting, ensuring efficient energy usage.
Our electrical engineering team developed a custom battery gauge and power PSB.
To minimize device size, the mechanical engineering team incorporated mirrors.
The system employs multithreading and async handling.
Scanned data is transmitted to the mobile application via BL connection and subsequently uploaded to the cloud for centralized management.
RESULTS
WHAT OUR TEAM SAYS
about the project
WHAT OUR TEAM SAYS
about the project
This scanning suitcase is designed for farmers with medium to large harvests who seek to:
- - Optimize harvest tracking
- - Improve data accuracy
- - Streamline operations
- - Enhance productivity
This solution provides real-time data collection and efficient reporting, reducing errors and improving overall efficiency.
