應用人工智慧技術於二次加攪拌機優化之研究

本研究針對食品加工中的麵團二次加工攪拌過程進行優化，開發一款基於人工智慧技術的智慧型自動攪拌系統。本系統運用影像識別與溫度控制技術，自動監控麵團狀態，並透過深度學習模型調整馬達轉速與揉製時間，減少人工操作所造成的誤差，提升生產效率與產品一致性。本系統配備非接觸式溫度感測器，確保麵團溫度保持在最佳發酵範圍(20-24°C)，以提升麵團品質與發酵穩定性。所有操作數據，包括影像、溫度及馬達運行狀態，皆可透過AIoT平台傳輸至用戶裝置，實現遠端監控與動態調整，進一步提升工作效率。本研究不僅實現攪拌機的智能化與自動化，還整合了AIoT控制面板、數據傳輸及深度學習模型，為食品加工業帶來創新解決方案，並提供技術升級的未來發展方向。

This study focuses on optimizing the secondary processing of dough in food production by developing a smart automatic mixer system based on artificial intelligence technology. The system employs image recognition and temperature control techniques to automatically monitor the dough’s condition and adjust the motor speed and kneading time through deep learning models, reducing errors caused by manual operation and enhancing both production efficiency and product consistency. The system is equipped with a non-contact temperature sensor to maintain the dough's temperature within the optimal fermentation range (20-24°C), ensuring dough quality and fermentation stability. All operational data, including images, temperature, and motor performance, are transmitted via an AIoT platform to user devices, allowing for remote monitoring and dynamic adjustments to further improve operational efficiency. This research not only achieves the automation and intelligence of the mixer but also integrates AIoT control panels, data transmission, and deep learning models, providing an innovative solution for the food processing industry and offering future pathways for technological upgrades.