Case study card:
Product quality assessment through computer vision
Primary Industries and Infrastructure
A large European agricultural business wanted to enhance product quality detection methods with an automated system.
Quality control had previously been manual, representing significant cost.
We built an application that has been performing fast and efficient quality inspection on food circuits right on the conveyor belt.
An optical sensor installed above the conveyor belt uses their image recognition to automate root rot evaluation.
We trained the machine learning algorithms to automatically analyse plants that passed through the tape.
The algorithm sent a signal to the robot that the plant was bad. The robot automatically has been removing the plants with the rot.