Invest KOREA

◦ Improving the limitations of the food industry, which relied solely on experience, with objective data measurement
 1) a matter of fact
   - Operating expenses are wasted due to the absence of data predicting demand and objective data on disposal. This is expected to increase cost spending due to rising prices 
   - The efforts of the existing food industry to reduce food waste consist of handwriting and contact-type measurements on a scale, which has limitations in objectivity and sustainability 
 2) key technology
   - Easily scan users' food plates and dishes using an AI food scanner, and then measure and collect food types and weight data
   - Identify the types, quantities, and nutrients of food images collected through deep learning (CNN) image recognition and 3D vision technologies and predict drinking water through big data records
      → Analysis of individual eating habits data such as nutrition balance, meal rate, and preferred food can be made
   - Providing eco-cafeteria services optimized for food waste reduction through data mining and visualization of analysis data
 3) Expected effect
   - It is possible to order the right amount of food materials through the prediction of drinking water, and as a result, it is possible to prevent waste of money by reducing the source of food materials 
   - Improving menus through analysis of customer preferences (analyzing leftover food) and improving food quality by reinvesting savings costs to improve meal satisfaction
   - Creating a positive effect on the European market by reducing food costs, customized diets for consumers, and further reducing food waste to realize low-carbon, green growth