Have you ever felt that guilt at a restaurant when you leave your plate half full or send your meal back to the kitchen because it didn’t please you? Now, imagine the colossal amount of meals served in restaurants around the world every single day. The amount of food we waste in restaurants is absolutely staggering. And that’s only the tip of the iceberg, as most of the food wasted never even gets to the plate.
Winnow Vision is a solution to help chefs reduce food waste by measuring and monitoring what gets in the bins of their kitchen. The technology combines a camera, a scale and artificial intelligence to recognize what type of food ends up in the “smart bin”. Chefs then receive a detailed daily, weekly and monthly report which gives them the financial and environmental cost of this discarded food.
“Without visibility into what is being wasted, kitchens are wasting far more food than they think. By understanding and reporting food waste’s very real costs both to the bottom line and the environment. Winnow Vision empowers chefs to take action” told Winnow CEO Marc Zornes in a recent interview with Forbes. Indeed, with this data on food waste, chefs can then adjust their food purchasing accordingly, and even adapt food quantities in plates.
Winnow Vision says it has an 80% accuracy in food recognition. But thanks to machine learning, the smart bins gets smarter over time, as it learns to recognize many types of different food.
Winnow was awarded with the Solar Impulse Efficient Solution Label because of its huge and direct impact on the environment, as food waste represents 8% of global greenhouse gas emissions annually. But not only. The Label is only granted to solutions which also have a direct economic impact. And Winnow has a clear repercussion on chef’s bottom lines.
According to Winnow, “food waste costs the hospitality industry over $100bn annually. Kitchens can waste up to 20% of food purchased, often equivalent to their total net profits”. Thanks to Winnow, users can cut their food waste in half, resulting in savings of 3 to 8% on food costs.
One of the company’s biggest successes for this new solution so far has been to install Winnow Vision at both IKEA and Emmar Hospitality Group, representing a total of 75 kitchens, and hundreds more to be equipped this year. For IKEA, this meant cost savings of up to $100,000 per store.
Prior to launching the image recognition solution, Winnow had already launched a similar process, but with a tablet which needed kitchen staff to identify the food thrown away. Since its beginning, the company has helped chefs save 23 million meals, amounting for nearly 30 million in food savings and preventing the emission of 29’000 tonnes of CO2. , making it a perfect example of a clean, efficient and profitable technology!