- United Kingdom
- Sustainable development goals
- Climate action
- Responsible consumption and production
- Sustainable cities and communities
- Project link
About the project
Winnow Vision is a privately owned company which has created and recently released a machine learning-powered smart bin that recognises different foods and helps kitchen staff to reduce waste.
More project information
Winnow Vision is a privately owned company which has created and recently released a machine learning-powered smart bin that recognises different foods and helps kitchen staff to reduce waste. Winnow founder and CEO Marc Zornes who previously worked on food and sustainability for McKinsey, founded the company in 2013 to tackle food wastage.
Using machine learning, Winnow’s Vision AI device helps commercial kitchens track the financial and environmental costs of discarded food. With the data it collects, businesses and chefs can adjust food purchases to reduce waste. The device uses a camera and smart scales to keep track of what types of food are being thrown away too often, helping restaurants to save money, and the environment. The AI requires an initial period of training in the kitchen whereby the kitchen staff would present various foods that are typically used in the kitchen, but quickly reaches a higher level of accuracy in identifying food waste than the busy staff. The company reports that their clients cut their food costs by, on average, 3% to 8% every year.
The product has been in use by multiple major businesses and hotel chains such as IKEA, the Compass Group, and AccorHotels. The Winnow Vision smart bin has already been successfully trialed in 23 Ikea stores as well as a number of hotel restaurants around the world. IKEA Bergen, for example, reduced food waste by 45% over the first 12 weeks of trialing the Winnow Visions smart bin. About 75 of the devices have already been installed and the company plans to roll out hundreds more this year. Winnow estimates it has saved almost $30m of food and 39,000 tones of CO2 so far. As such, by reducing food waste and its associated effects on the environment and city health, the device meets the criteria set for the SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action).