The customer: a bakery. They had difficulties in calculating the exact number of loaves. Their first attempt was to use sensors but the result was not presise and they had to calculate loaves manually.
CALCULATION OF ITEMS ON A CONVEYOR BELT
A working solution for recognition and calculation of items on a conveyor belt based on Machine Learning
GOAL
Control of item calculation on a conveyor belt
TASKS
Recognition and calculation of items on a conveyor belt
FUNCTIONAL
A program which can recognize items, count items and make a report.
WHAT HAVE WE DONE
We created a program which can recognize a loaf of bread on a video
We developed a program which counts the number of loaves per shift
We developed a form of report, where the reporting period can be a shift or any other period
BENEFITS
Recognition accuracy has increased in the whole conveyor production system
Output calculation costs have reduced
The system of defective loaf recognition (for example: loaves of uneven shape) has been developed.
Our solution is based on computer vision and uses only one camera to calculate the number of loaves.
It is quite a cheap solution: all you need is a simple camera and a computer.
Having invested in machine learning once you can get a program which recognizes different types of bread. Also the program can be customized to sort out defected loaves and this way to minimize losses and waste.
CUSTOMERS FROM ALL OVER THE WORLD TRUST US
ANY QUESTIONS LEFT?
Contact us and
we will tell you about
Machine Learning application in your business.