Artificial Intelligence is used to read and recognize different types of containers, materials, and colours to separate them as required.
This advanced technology positions Container Deposit Systems in a leading role towards developing innovative and convenient solutions to increase recycling rates and reduce litter.
Why AI vision-based?
Doesn't rely on barcodes
Accepts eligible containers in any condition
High recognition & classification speed
7,200 containers per hour* 99.8% counting accuracy* 98.9% classification accuracy
*Based on a site audit performed on an ART during business operating hours.
** In average.
A bit of background
Vision-based technology is born after observing that the available container detection and classifying technology in the market was failing to read containers in different conditions.
Crushed containers, with deformed shape and size or decoloured by damage and dirtiness, might not be detected by traditional barcode reading systems.
The first tentative solution is proposed and tested to implement sensors that could determine what material the containers were made out of. Nonetheless, due to the dirtiness condition and the liquid content that could still be found in them when returned, the accuracy of this system didn’t reach CDS standards.
Research is conducted by the University of South Australia to Sage Automation and Macweld Industries, to explore the opportunity to develop an innovative solution capable to detect and classify all sorts of eligible containers regardless of their condition.
An AI vision-based technology system tests positive for all the required standards and is ready to be rolled out along with CDS recycling solutions. This technology is not only capable to read containers in all sorts of conditions, but it also demonstrates to work at a higher speed than the current container classification solutions in the market.
Wednesday 19th of December 2018 marks the day the first Auto Redemption Terminal (ART) leaves its warehouse and CDS’s innovative technology makes an entrance into the recycling industry
Vision based technology
Classifies and separates mechanically
Identifies containers by material and colour