Abstract: The system and method to measure, identify, and reduce food defects from manual or automated processes uses a combination of sensors, computer vision, and machine learning to optimize yield, and quality for food processes. Specific features are monitored, analyzed, and quantified. Real time and aggregated data are available to relevant stakeholders to aid in understanding and optimizing food yield, quality and throughput. A cut guidance protocol, fingerprinting and embedding of food object is done using food data from a database in a processor.

Abstract: The system, device, process and method of measuring food, food consumption and waste with image recognition and sensor technology is presented to empower cafeterias, processors, quick service restaurants, and other institutions and locations to reduce food waste. Using kitchen and consumer data, the system allows food providers to characterize key food properties, optimize portion sizing, ingredient combinations, and meal preparation, to maximize profits and minimize excess. The current system, process and method optimize the food chain uses analytics and prediction insights. Gathering data through the use of a sensor package (typically including a camera system), and/or smartphone application, a digital platform is then used to give insights to institutions over time. This feedback includes food supplier changes, quality reports, preparation changes, portion sizing, ingredient usage, and customer feedback.