This paper discusses creating an automated billing system tailored for modern retail stores, specifically for millet purchases. By eliminating the manual process currently employed in retail stores, this system streamlines the purchase of loose items. To achieve this, several crucial objectives were pursued. A CAD model was developed using SolidWorks, detailing the setup comprising a box with four weighing plates, which was then fabricated using wood based on the CAD design. A dataset specifically focused on millet grains was collected by purchasing millets and capturing images within the designed setup. These images were then used to train a deep learning model—YOLOv8 algorithm to accurately identify the type of millet grains. Additionally, an appropriate load cell was chosen and calibrated to ensure consistent and precise weight readings. Then the software and other hardware components, such as the HX711 amplifier, PIR sensor, relay switch, camera, and Raspberry Pi, were integrated to enable autonomous function. Finally, a user-friendly graphical user interface (GUI) was designed to facilitate invoice viewing, billing details, and online payment options, ensuring an effortless transaction experience for customers. Ultimately when the required millets are placed in the system, the platform equipped with load cells measures the weight, and simultaneously the camera identifies the type of millets. Following this, a digital invoice is generated, detailing the millet type, quantity, and total price. Customers can then confirm and pay via an intuitive touchscreen interface.