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AI is being used to address the global food wastage problem that is seeing around a third of all food failing to make it to the dinner table. Innovations in the form of technology that can select when fruit is ready to pick, minimize spoiling of produce in transit, monitor food waste through attributing dollar values and generating accurate food demand forecasts are employing AI and machine learning to help to reduce waste.
Food Waste, A Global Issue
Each year, 1.6 billion tonnes of food is wasted around the world, and experts predict this will increase to 2.1 billion by 2030. This represents around $1 trillion in wastage, and around a third of the world’s annual food production.
Data reports that chronic undernourishment impacts over 10% of the global population, which could be resolved by reducing food waste. As the global population is expected to rise to around 10 billion by 2050, limiting food waste in order to provide enough food for a rising number of people is essential. In addition, food waste accounts for 8% of greenhouse gas emissions, which are in desperate need of reduction.
Minimizing food waste is fundamental to addressing both the global food crisis as well as emissions. Technology companies and food businesses are innovating new ways to tackle food waste with the help of AI and machine learning.
Attributing Dollar Value to Waste
The Ellen MacArthur Foundation along with Google recently released a report that estimates that technology aimed at tackling food waste might be generating as much as $127 billion in annual revenue by 2030. Many technological developments are already underway, with innovations in AI and machine learning with the capabilities of identifying when fruit is ready to be picked, forecasting the demands of retailers, as well as minimizing spoilage with edible connected sensors.
Two further technologies have also recently been announced. Winnow Solutions, a London based startup, has claimed that it has established new technology which will reduce food waste by identifying and weighing food waste for commercial kitchens.
The technology then attributes a dollar value to the waste, which has been proven to be more than 80% accurate, helping companies to monitor their waste. Through monitoring, kitchen managers can gain insights into their level of food waste, and what this is costing their business. With the data, managers have a way to set food waste goals and measure their performance. Studies have shown that kitchens using the system manage to reduce food waste by around half.
Recently, IKEA partnered with the startup and has installed its technology into stores in the UK and Ireland. As a result, kitchens in those stores have reduced food waste by 50%, the same as 1.2 million meals throughout the year.
Accurate Predictions to Optimize Food Supply
Another innovation that has recently made headlines is the forecasting and optimization technology that Ocado has begun to use. It has already been able to minimize food wastage to just 1 in every 6,000 food items by using machine learning to calculate the food that customers actually need, reducing over ordering that results in waste.
In addition, Ocado does not sell produce that is close to its expiration date as another method of limiting waste. Instead, these items are automatically flagged and get sent to local food banks or animal parks.
The technology is being used by Ocado to generate over 20 million forecasts daily, these forecasts are helping the company continue to reduce the ratio of food that is wasted by increasing the accuracy of its predictions over time.
The area of technology to reduce food waste is a growing one, and we can expect to see further developments in the coming years. The impact of which will hopefully lessen the amount of food wasted, and help to create a sustainable system in which people have access to sufficient nutrition, even as the population grows.