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Apr 01 , 2021Views : 25148
Artificial intelligence for reducing food waste
There are various causes for avoidable waste, ranging from overproduction to fluctuations in raw materials' quality to the food failing to fulfill specific aesthetic requirements. The REIF project partners are focusing on dairy, meat and bakery products. Waste occurs with these products mainly because they spoil quickly. “Two aspects are key to significantly reducing food losses in these sectors – minimizing overproduction and avoiding waste,” explains Patrick Zimmerman, a scientist at Fraunhofer IGCV and member of the consortium. He and Philipp Theumer as well as five other colleagues are looking at how a company's internal potentials, such as in plant and machinery or production planning and control, can be optimized to reduce waste using AI methods. “We apply AI to the entire value chain, especially in the production facilities. To do that, we adapt and select the algorithms that are suitable for the respective application,” explains Zimmerman. We look at the predictability and controllability in all areas – from production on the farm to sale in the supermarket – to optimize their potential. “Overproduction and waste can be avoided by making targeted forecasts on food requirements, improving the predictability and controllability of the value creation processes and reducing quality-related food loss,” adds Theumer.
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