食品廃棄物関連技術を導入して労力も経費も節約

Computer vision is a particular type of Artificial Intelligence (AI). It works by taking the information in an image, breaking it down in detail, and then making the computer analyze this information to understand what the image is.

Winnow Vision allows kitchens to automatically track and analyze food waste. It uses AI to help chefs easily pinpoint waste, cut costs and improve performance. Kitchens using Winnow typically see food waste cut in half, saving 3%-8% in reduced food purchasing costs.

The system takes photos of wasted food as it's thrown away and, using the images, the machine trains itself to recognise what is thrown in the bin. Winnow Vision is now operational in over 1,000 kitchens worldwide. Our data shows that we have reached and surpassed human levels of accuracy in identifying wasted foods.

Typically Winnow kitchens see an ROI of 200%-1,000% within year one. Our pricing is tiered according to the specifics of your kitchens.

Find out more on our pricing page.

A Winnow Vision system is made up of a Vision Control Box that records food waste and a connected scale that captures its weight.

A Vision Control Box is comprised of:

• An in-built camera that automatically takes pictures of food as it’s thrown away and processes them in real time,
• An embedded tablet configured with the Winnow App and your kitchen’s menu, where food waste is recorded and categorised.

Once deployed, Winnow’s begins learning how to recognise food items as they’re thrown away. It takes the AI on average about four weeks to reach automation, but the exact time frame depends on the breadth of your food offer.

Winnow Vision is best suited to hospitality groups with multiple sites (30+) where larger volumes of images can be captured. The more images captured, the faster the AI learns, so large operations can expect to reach automation faster than smaller chains or individual restaurants.

Winnow Vision requires an internet connection, power supply, and wall space to install the Vision Control Box, as well as space for the bin and connected scale.

• Data quality and image-led data analytics: You know exactly what’s being thrown away and have images to validate the data. This quality data helps kitchens pinpoint waste and reduce overproduction
• Save time and improve efficiency: Automated data collection both improves efficiency and saves time when compared to other methods of food waste recording
• Digital transformation: Utilise AI in your kitchen and be seen as industry pioneers by customers and industry
• Environmental impact: Food waste produces greenhouse gases, so reducing this waste decreases your carbon footprint and environmental impact.

Winnow Vision surpasses human levels of accuracy which means that the system will be able to tell the difference between two very similar looking food items, even if the human eye might not be able to. An example of this is that the Winnow Vision system is able to differentiate between a piece of roast chicken vs. Piri Piri chicken though the human eye might not be able to.

Winnow’s data shows that commercial kitchens waste up to 20% of all food purchased (typically between 5% - 15%). Kitchens using Winnow’s analytics can expect to cut this in half in 6-12 months. This equates to average savings of between $1 - $5k a year for a smaller site through to $50k+ for a large hotel or staff restaurant.

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