Study of active food processing technology using computer vision and AI in coffee roasting

作     者：Kim, Youngjin Lee, Jooho Kim, Sangoh 

作者机构：Sangmyung Univ Dept Plant & Food Engn Sangmyeongdae Gil 31 Cheonan 31066 Chungcheongnam South Korea 

出 版 物：《FOOD SCIENCE AND BIOTECHNOLOGY》 (食品科学与生物工程杂志)

年 卷 期：2024年第33卷第11期

页      面：2543-2550页

核心收录：

学科分类：0832[工学-食品科学与工程（可授工学、农学学位）] 08[工学] 

基　　金：Sangmyung University [2021-A000-0292, 2022-A000-0314] Sangmyung University 

主　　题：Artificial intelligence Machine learning Coffee roasting machine Computer vision Active processes 

摘      要：In the modern food processing industry, which is more complex than in the past, it is important to utilize real-time computer vision for active food processing technology using artificial intelligence. An integrated solution of computer vision and Deep Learning (DL) technology provides quality control and optimization of food processing in complex environments with obstacles. In this study, Coffee Bean Classification Model (CBCM) made by Machine Learning (ML) showed excellent performance, accurately distinguishing coffee beans through the avoidance of obstacles and empty spaces inside a rotating roasting machine. CBCM achieved a maximum validation accuracy of 98.44% and a minimum validation loss of 5.40% after the fifth epoch. Using a test dataset of 137 samples, CBCM achieved an accuracy of 99.27% and a loss of 2.82%. The developed solution using the CBCM was able to quantify the color change of the coffee beans during roasting.