kamasys example image of camera checkout

Break times are often tight - long lines to pay at the company restaurant cost nerves accordingly. "My Plate Scanner" - a camera-controlled cash register - significantly speeds up the process.

Check the order, enter it in the cash register, take out the wallet, accept the change, stow everything away, and walk to your seat with the tray: The classic payment process in the company restaurant is a factor that should not be underestimated in terms of time and also nerve-wracking.

The self-checkout with the camera checkout "My Plate Scanner" provides a noticeable relief for staff and guests.

Faster checkout processes

Digitization and automation of payment processes means time savings for staff as well as guests and is a way to address staff shortages.

Due to the extensive database, the software can recognize food and beverages with a recognition rate of 99% within a few seconds: While conventional detection takes up to 30 seconds, the checkout process can be completed in as little as three seconds with the "My Plate Scanner" camera checkout.

However, it is not only the customers who benefit from this: for the employees, the time savings also mean an enormous reduction in workload. Since the checkout process is no longer required, the available staff can be deployed more efficiently for other tasks (e.g. preparing or serving meals).

The fast recognition of food by camera significantly increases the checkout process. Among other things, this allows for higher checkout throughput, more satisfied customers, and at the same time reduces the workload of the staff in the company restaurant.

  • Convenient teaching with few images created per product for high targeting accuracy
  • reliable recognition of different shapes and sizes of the dishes
  • uncomplicated integration into existing IT landscape
  • Various payment systems such as employee ID cards or debit cards
  • Available as camera with stand at the existing cash desk or as invisible installation in the ceiling

The database of the software is already comprehensively filled with images of dishes and beverages. This means that only a few images per product are required to teach the dishes: simply photograph the dish with the plate scanner and assign it to the dish stored in BackEnd. The plate scanner thus achieves a recognition rate of 99 percent, with detection taking place within fractions of a second.

  • PC / Cash desk
  • Intel i7 processor
  • 16 GB RAM
  • 15'' frameless Projected Capacitive Touch
  • LAN / WLAN
  • Operating system Windows 10 IoT 64 bit preinstalled
  • Compact modular network camera
  • Focal length - 3.7mm
  • Lens mount - fixed focal length
  • Angle of view Horizontal (FOV) - 57
  • Resolution standard - 1280×720
  • Power supply - POE
  • Power over Ethernet - IEEE 802.3af
  • Optional with camera arm

"The software is already so extensively fed with dishes and data from canteens and restaurants around the world that this results in high recognition rates. Even if the software has never seen a dish before, it recognizes about 99 percent of whether it is a main course. For each new dish, we therefore only need a single image."

Alexander Hirner, CTO Dishtracker