Machine Operation
       Connecting a Raspberry Pi with a servo motor and an ultrasonic sensor. Using Python programming on the Raspberry Pi, the ultrasonic sensor detects the box, and the servo motor changes its angle to rotate the conveyor belt and close the box. By integrating software functions, the checkout process is completed.

機器運作

       將樹莓派與伺服馬達、超音波感測器連接。在樹莓派利用python語法程式控制超音波偵測到盒子，伺服馬達的角度改變，來轉動輸送帶、關閉盒子。並結合軟體功能，完成結帳流程。

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AI Recognition
       We first collect a large number of photos and label the bread types using Roboflow. Then, we use Google Colab for training, and subsequently import the model into VS Code. The recognition process uses the YOLOv9 module for detection, the OpenCV module for image reading, and the PyQt5 module to display the quantity and price of the bread. The recognized images, as well as the quantity and price of the bread, can be displayed on the screen in real-time.

AI辨識

       我們事先收集大量的照片放入roboflow標註麵包種類，再使用google colab訓練，接著匯入vs code，利用yolov9模組進行辨識、opencv模組影像讀取、PyQt5模組顯示麵包數量、價格。辨識的畫面及麵包數量、價格能同步在螢幕上顯示。

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Checkout
       The interface has a checkout button. When the customer confirms that the recognized bread is correct, they press the checkout button, which connects to a backend Flask program. A checkout QR code will appear for payment. Afterward, the servo motor closes the box, a voice announcement provides the purchase information, and the purchase information is sent to the store's backend system.

結帳

       介面設有結帳按鈕。當顧客確認辨識到的麵包正確後，按下結帳按鈕，連結後端Flask程式，將會出現結帳QR code結帳付款，接著伺服馬達將蓋上盒子，然後語音播出購買資訊、將購買資訊傳至店家後台。