Called BINgo, it employs artificial intelligence, Internet of Things and smart sensors.

 

FairPrice Group is launching a pilot for the deployment of smart waste sorting bins named “BINgo”, in partnership with the Agency for Science, Technology and Research (A*STAR). BINgo employs artificial intelligence (AI), Internet of Things (IoT) and smart sensors to help address the issues of incorrect recycling practices and low recycling rates in Singapore. As part of pilot trials, one prototype BINgo machine has been deployed at AMK Hub, and other prototype BINgo machines are expected to be progressively deployed to NEX and FairPrice Hub, and will be kept on the premises for up to one year, till October 2023.

“FairPrice embraces sustainability practices in our business by proactively championing and introducing efforts to nurture and protect our environment. Through this smart bins initiative, we aim to educate and imbue the importance of recycling right in the community, and inculcate the habit of reducing our environmental footprint,” said Jonas Kor, general manager, FairPrice Foundation.

BINgo aims to encourage correct recycling practices and improve recycling rates through AI-enabled automated sorting technology and smart sensors to improve the collection processes of recyclables, including metal cans, glass, paper and plastic packaging, in recyclable condition. This means that waste fed into the machine can be identified as material suitable or unsuitable for recycling, and identified as having any contamination present that may affect its suitability for recycling (e.g. remnant liquid and pearls in a half-empty bubble tea cup). The machine’s interface also educates the user about useful recycling facts as they go through the process of feeding waste into the machine.

With simple to use step-by-step guide and user-friendly interface, BINgo is packed with interactive and educational elements to help shoppers identify recyclables from non-recyclables, enabling them to recycle more and recycle correctly. This design boosts efficiency and helps streamline collection processes, creating an enhanced experience for users. Additionally, the data of waste collected over time will improve recognition of the recyclables, as well as improve statistical analysis for better waste management.