AI-driven recycling company WinGo Deposit has made it possible to accept damaged packaging for the first time.
The Latvia-based information technology company has launched the world's first deposit system that uses artificial intelligence, machine vision and neural network technologies to recognize and sort all types of packaging even if they have been flattened, damaged or with a missing label.
“WinGo Deposit’s smart waste sorting machine accurately identifies PET bottles, cans, tetra packs and other types of packaging that are damaged or unlabeled if the citizen is digitally authenticated,” says Vismands Menjoks, chief executive officer and co-owner of WinGo Deposit.
Digital authentication and wallet also provide a preventive function to prevent the risks of fraud. It is a novelty for the solution developed in Latvia. It offers to accept both intact and flattened bottles – the function of recognition does not only read the barcode of the package. It scales, recognizes the material and visually analyzes.
Such a system, where damaged packaging is accepted, fulfils the overarching task – it more effectively solves the issues of environmental management and waste.
The technology improves the functionality of automatic recycling deposit points, which until now, have only been able to accept undamaged products. This reduces the amount of waste it is able to accept, as many used products are often flattened after use.
“WinGo Deposit offers a system created from the point of view of the population. It will make the transfer of beverage packaging as convenient as possible for the whole society,” says Menjoks. “The smart waste sorting machine created in Latvia is a significant turning point, because the technological solution, with the help of artificial intelligence and neural networks, recognizes, accepts and sorts different types and volumes of both intact and flattened beverage packages. In nature, however, the packaging does not look like a store shelf.”
In the WinGo Deposit system, the package is not only weighed, but also photographed. Computer vision, logic analytics and other smart machine skills can evaluate different types of packaging.
This technology is adaptable to other waste groups, such as tires, household chemical packaging or hazardous waste such as deodorants and paint vials.