A Real-Time Coffee Roasting level Estimation Based on Artificial Intelligence
| Autor: | LIN, HUAN-JAN, 林煥然 |
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| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 The goal of this project is to develop A Real-Time Coffee Roasting level Estimation Based on Artificial Intelligence. It can be used in combination with the roasting machine to greatly prevent the coffee baker from the tedious hand checking of the current coffee roasting level, and allows the use of the (more effective) Agtron-Time curve to replace the traditional (less effective) Temperature-Time curve in coffee roasting. The key ideas include: 1. Apply the Convolutional Neural Network (CNN) technique to classify and report in real-time the roasting level of coffee beans under roasting. 2. Based on the above real-time roasting level estimation technique as well as proper sensors, to automatically sample (each second) and collect coffee roasting related signals such as {Time, Agtron level, room temperature }, in order to establish and auto-update the Coffee Roasting Method, which combined with Regression Analysis can estimate and remind the baker (human or machine) the time required for the next category of coffee roasting level. Overall, Through the use of proper sensors and advanced artificial intelligence techniques including CNN and Regression Analysis, may allow the baker (human or machine) to grasp the real-time roasting conditions more precisely. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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