Artificial Intelligence focusing to lessen food waste

artificial intelligence focusing to lessen food waste

Waste the pro, don’t. As the saying goes, for more than 250 years, it is wise to use its resources or bear the consequences. This is also a good introduction to food waste. The Food and Agriculture Organization of the United Nations (FAO) currently: About one-third of the world’s food is lost or wasted from farms to refrigerators every year, about 1.3 billion tons. The estimated annual economic cost is US$ 1 trillion.

Technology has long been helping to solve the problem of hunger in the world. Today, most discussions about the impact of technology on all areas of the economy inevitably link artificial intelligence to sophisticated software that enables machines to make decisions and even predictions in a human-like manner. The same is true for food waste technology. A report by the Mr. Ellen MacArthur Foundation and Google evaluations that by 2030, a technology that uses AI to “design food waste” can help generate up to $127 billion in revenue each year. These technologies range from machine vision to harvestable fruit to technology that predicts demand to ensure that retailers do not overstock certain foods.

Winnow Solutions is a London startup that makes captions ‘reducing food waste’. The company received US$ 20 Mn in equity funds and loans in October to expand its artificial intelligence platform, Winnow Vision, that identifies and weighs the food waste in commercial kitchens globally. It automatically assigns a dollar value to each of the scraped food. In retail, such as an Israeli startup three years ago, the software can track the price of a product in real-time and adjust the cost based on its expiration date, so products with shorter shelves can also be inserted into the store’s merchandise. The operation of inventory management and other links. In 2018, the organization said that about US$ 125 million was invested in food waste start-ups, but it is estimated that the private sector needs to account for about a third of the total investment of US$ 18 billion to achieve the about 20% reduction target.

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