دورية أكاديمية

A Remote Access Server with Chatbot User Interface for Coffee Grinder Burr Wear Level Assessment Based on Imaging Granule Analysis and Deep Learning Techniques

التفاصيل البيبلوغرافية
العنوان: A Remote Access Server with Chatbot User Interface for Coffee Grinder Burr Wear Level Assessment Based on Imaging Granule Analysis and Deep Learning Techniques
المؤلفون: Chih-Yung Chen, Shang-Feng Lin, Yuan-Wei Tseng, Zhe-Wei Dong, Cheng-Han Cai
المصدر: Applied Sciences, Vol 14, Iss 3, p 1315 (2024)
بيانات النشر: MDPI AG, 2024.
سنة النشر: 2024
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: image processing, deep learning model, artificial intelligence, granule analysis, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Coffee chains are very popular around the world. Because overly worn coffee grinder burrs can downgrade the taste of coffee, coffee experts and professional cuppers in an anonymous coffee chain have developed a manual method to classify coffee grinder burr wear so that worn burrs can be replaced in time to maintain the good taste of coffee. In this paper, a remote access server system that can mimic the ability of those recognized coffee experts and professional cuppers to classify coffee grinder burr wear has been developed. Users only need to first upload a photo of coffee granules ground by a grinder to the system through a chatbot interface; then, they can receive the burr wear classification result from the remote server in a minute. The system first uses image processing to obtain the coffee granules’ size distribution. Based on the size distributions, unified length data inputs are then obtained to train and test the deep learning model so that it can classify the burr wear level into initial wear, normal wear, and severe wear with more than 96% accuracy. As only a mobile phone is needed to use this service, the proposed system is very suitable for both coffee chains and coffee lovers.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/14/3/1315; https://doaj.org/toc/2076-3417
DOI: 10.3390/app14031315
URL الوصول: https://doaj.org/article/271f4f79138149c287da2a70379979c3
رقم الأكسشن: edsdoj.271f4f79138149c287da2a70379979c3
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app14031315