The NexGen Billing Cart project addresses critical challenges in retail, including prolonged billing times and inefficient inventory management, by introducing an automated billing system that leverages IoT and machine learning. Utilizing a Raspberry Pi, a camera module, and YOLO-NAS for object detection, the system identifies and processes items placed in the cart, automating the checkout experience. This solution provides real-time inventory updates and enhances customer experience by streamlining the checkout process, minimizing human error, and reducing labor demands. Experimental results demonstrate high accuracy in item recognition and efficient real-time processing, indicating the model`s potential to optimize retail operations. The propose system represents a significant advancement toward seamless and automated retail experiences, providing a scalable and practical solution for inventory control and customer service improvement.

Automated Billing, IoT in Retail, Machine Learning, YOLO-NAS, Inventory Management, Retail Automation, Smart Cart, Computer Vision

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