1.3 Billion Tons of Food Is Wasted Every Year. How to Use AI to Help Restaurant Kitchens Save Food

By Super Neuro

Scenario description:By incorporating data analysis, computer vision and other technologies into kitchen management, a company called Winnow helps hotel companies reduce food waste in the production process, save costs and eliminate waste.

Keywords:Computer Vision Food Planning 

Food waste is not a small problem

Food waste seems to be a common thing in this era, but perhaps you are far from realizing its seriousness.

According to the Food and Agriculture Organization of the United Nations (FAO),One-third of the food produced globally is not eaten each year, which means that about $1 trillion worth of food is thrown directly into landfills every year.

The hotel industry accounts for about 10% of these data. According to statistics, the hotel and catering industry will increase its costs by more than 100 billion US dollars each year due to food waste. The wasted food accounts for 20% of the purchased ingredients, and the lost costs are roughly equivalent to the net profit of some companies.

One of the reasons behind this phenomenon is that chefs lack the necessary tools to accurately measure and manage food waste.

In order to solve this problem, many companies are actively working on it.A company called Winnow uses data analysis, computer vision and machine learning to achieve this goal..

Winnow uses technology to prevent unnecessary food waste

“Food waste is a global problem that nearly every kitchen struggles with,” said Winnow CEO Marc Zornes. “If kitchens don’t understand the situation, they will waste more food. Understanding and understanding the true cost of food waste, both financially and to the environment, will enable chefs to take action accordingly.”

This company specializes in waste

Winnow was founded in London in 2013. In response to the problem of food waste, they developed digital tools to help chefs gain access to information and avoid processing too much food.

Winnow means winnow in Chinese, which means to separate the grain from the chaff. On their website, Winnow's mission is to connect commercial kitchens with technology, carry out conservation activities, and help people cherish food.

What they do sounds simple: they count discarded food, combine it with manual or machine identification of the type of food, and then use Winnow's cloud analysis to determine the loss of this waste, while issuing regular reports to remind chefs to save money by cutting back on the food that was thrown away last time.

Long-term food discarding causes great losses

Winnow typically reduces food costs by 3% – 8% using this approach.

But Winnow is not an artificial intelligence hardware company. Its core is data services. Through data analysis, they allow kitchen staff to intuitively see their waste situation and then make corresponding countermeasures. The introduction of hardware and machine learning is to better achieve this goal.

Focus on using technology to make a difference

In early versions, their peripheral system consisted only of a digital scale and a connected tablet. The weight was automatically recorded by processing discarded food, and the chef could select the discarded food through a screen.

Early demonstration diagram

But the disadvantage of this method is that it requires a lot of manual input. After two years of exploration and research, Winnow introduced computer vision and machine learning to launch their new product Winnow Vision. 

The biggest improvement of Winnow Vision is that it introduces automation through cameras, using machines to replace manual food identification. This new product was launched in January last year and was used as a pilot project by several well-known brands, achieving excellent results.

Winnow Vision in the kitchen

Today’s systems can predict what food will end up in the bin more reliably than a busy kitchen team can.In fact, in its first attempts, the system correctly identified 80 percent of the foods.

As Winnow Vision acquires more image data, the accuracy of its judgment will become higher over time.

Winnow promises its users that restaurant companies can get a 2-10 times return on investment in the first year, which is equivalent to reducing food waste by about $50,000.

A universally accepted system

Winnow said the past system has been used by thousands of chefs in more than 40 countries and has helped them save the equivalent of $30 million in food from landfills each year.

Driven by artificial intelligence, Winnow Vision uses computer vision technology to automate food waste management. This will be an important node for AI to enter the kitchen on a large scale and will promote more accurate food waste data monitoring.

With this new approach, they lower the barrier to entry for thousands of kitchens around the world.Once the system is adequately trained, no repeated staff training or data entry is required, and the kitchen automatically receives information on discarded food to determine the type and volume of discards.

New system identifies discarded food

Fundamentally, Winnow Vision is a game changer for the industry and leading the fight against food waste on a global scale.

Their technology was also recognized at the World Economic Forum in Davos in January, ultimately winning the 2019 Tech Disruptor Award.

The future is a present tense

Since the company was founded in 2013, it has been six years since its establishment. They have been working hard to fight food waste, just to better use technology in this field.

Now, with the help of technologies such as machine learning, more companies and users will be able to prevent food from going directly to the trash.

The company's head said, "We have learned a lot from these developments. These experiences are incorporated into the design of Winnow Vision. Through Winnow Vision, our impact will continue to expand, and more companies will be able to join the fight against food waste."

Winnow has been used in many areas

With the launch of Winnow Vision, they hope to achieve annual savings of $1 billion by 2025.

Furthermore, the team claims that this is just the beginning and they are more excited than ever about future developments and using new technologies to tackle the problem of food waste.