Solutions based on machine learning
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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.

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.

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.