IOT BASED SELF CHECKOUT SYSTEM USING CLOUD DATABASE AND RFID FOR PAYMENT PROCESS OPTIMIZATION

Abstract

The rapid advancement of technology has significantly transformed various aspects of daily life, including retail processes in academic institutions. This paper presents an IoT-based self-checkout system designed to enhance payment processing efficiency within a college environment. The proposed system integrates Radio Frequency Identification (RFID) technology with a cloud-based database to streamline the checkout process and reduce operational overhead. The system leverages RFID tags for item identification and tracking, enabling students to quickly and accurately select and pay for items without manual intervention. The RFID-enabled checkout process is seamlessly connected to a cloud database, which manages inventory, tracks transactions, and ensures real-time data synchronization across multiple points of sale. This integration allows for immediate updates on stock levels, facilitates the generation of detailed sales reports, and supports dynamic pricing strategies based on real-time data analytics. By automating the checkout process and minimizing the need for cashier interaction, the system not only speeds up transaction times but also reduces the likelihood of errors and enhances the overall user experience. The cloud database infrastructure provides scalability, data security, and accessibility, ensuring that the system can accommodate varying demands and adapt to future technological advancements. This innovative approach addresses common challenges in traditional checkout systems, such as long wait times and inventory mismanagement, while offering a practical solution tailored to the needs of a college setting. The paper discusses the design, implementation, and potential benefits of this IoT-based self-checkout system, highlighting its contribution to optimizing payment processes and improving operational efficiency in academic environments.