The business case for using food waste technology

Food waste machine learning

Machine learning and AI offer the potential of optimising areas of the food business and dramatically reducing waste. For example, data collected by a group of data scientists at Blue Yonder predict that AI and machine learning could save £144 million each year for the group of eight biggest UK supermarkets. This is based on four key benefits that machine learning and AI can deliver to reduce food wastage. Fundamentally, this technology will help in the following ways:

1. Forecasting: AI can now significantly improve the forecasting of demand by taking into account vast data sets. By processing this information at great speed, retailers will have a more accurate signal of the likely demand for food, thus minimising waste.
2. Inventory management: through a better understanding of the risk of food loss and wastage, retailers can find the right balance of managing inventory of every product in the store.
3. Pricing: AI can help to set responsive pricing that adjusts the price depending on the expiry date of the product.
4. Sensing transportation disruption: by analysing weather and transport disruption, machine learning can help grocery retailers by advising alternative routes to ensure the risk of food waste is mitigated.

At the heart of all these examples is a central theme: machine learning and AI offer the possibility to take enormous quantities of data, assess it, and make actionable recommendations. This can help grocers around the world - and other food businesses - to utilise numerous sets of data at speed. The result is a more reliable decision-making process that can reduce food waste across the business.

Data capture vision technology

Another growing area of food waste technology uses computer vision technology to capture and identify images of food. This technology breaks images down in detail and then makes the computer analyze that information to help us understand what the image is.

This data capture vision technology has at least two main benefits. Principally, computer vision can assist companies to measure and manage their food waste throughout their operation. 

In 2019, Winnow launched food waste AI into the commercial kitchen at scale. This development automates the process of collecting food waste data at the point it enters the bin, collates this data and presents it back to the kitchen team in a useful format. This insight can then be used to prevent food wastage in the future.

There are also some companies developing computer vision technology to detect unripe or contaminated food. This will help to automatically detect the quality of food in factories and warehouses.

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Biotech: can insects eat all of our food waste?

There are other technologies being developed that attack the problem from a different angle. Could insects be the solution to our food waste problem?

Several entrepreneurs are turning to insects to help turn food waste into other valuable products. For instance, the larvae of the black soldier fly can feast on up to four times its own body weight each day, and at the end of the life, can either turn into natural fertiliser or fish food.

In China, a billion cockroaches are fed with 50 tonnes of kitchen waste each day, which is also nutritious food for pigs and other livestock. Utilising insects in this way could mean less farmland would be required to grow feed for animals.