1.       Introduction

The rapid advancement of automation and Internet of Things (IoT) technologies has significantly transformed traditional retail systems. In conventional shopping environments, customers often experience long waiting times at billing counters due to manual barcode scanning and cashier dependency. These delays not only reduce customer satisfaction but also increase operational workload and human error. To overcome these limitations, smart retail solutions are being developed to automate the shopping and checkout process. One such innovative solution is the Smart Assistant Cart [1].

A Smart Assistant Cart is an intelligent shopping trolley embedded with sensors, microcontrollers, and wireless communication modules that enable automatic product identification and real-time billing. The system primarily uses RFID technology, where each product is attached with a unique RFID tag. When an item is placed into the cart, the RFID reader detects the tag and sends the information to the controller, which retrieves the product details such as name and price from a stored database. The total bill is updated instantly and displayed on an LCD or mobile application, allowing customers to monitor their expenses while shopping.

The integration of IoT further enhances the functionality of the smart cart by enabling wireless data transmission to cloud servers. This allows for digital bill generation, inventory management, and mobile notifications [2]. Customers can complete their shopping without standing in long checkout queues, as the billing process is already completed within the cart itself. Additionally, retailers benefit from reduced manpower requirements, improved billing accuracy, and better data analytics for sales and customer behavior.

The Smart Assistant Cart system is especially relevant in the context of modern supermarkets, shopping malls, and smart stores where efficiency, speed, and contactless operation are crucial. It supports the growing demand for smart infrastructure and provides a scalable platform that can be upgraded with advanced features such as mobile payment integration, voice assistance, indoor navigation, and theft detection. Overall, the Smart Assistant Cart represents a practical and effective step toward fully automated and intelligent retail environments [3].

With increased customer footfall and demand for contactless operations post-COVID-19, retailers need to adopt intelligent automation to improve store management and customer satisfaction. Smart carts fulfill this by offering: Instant item scanning without manual barcode scanning, Reduced billing queues, Enhanced customer experience, Integration with mobile devices and e-receipts

The main goals of this project are:

·         To design and implement a smart shopping cart with autonomous item detection.

·         To generate real-time billing and display it to the user.

·         To integrate the system with cloud platforms for data storage and mobile notifications.

·         To reduce human dependency and billing time in retail.

2.       Literature Review

In recent years, the concept of smart retail has gained significant attention due to advancements in embedded systems, Internet of Things (IoT), and wireless communication technologies. Several researchers have proposed intelligent shopping cart systems to reduce manual effort, minimize billing time, and enhance customer convenience. IoT-based smart shopping cart using RFID technology for automatic product identification and billing. Their system utilized an Arduino microcontroller, RFID reader, and LCD display to show the total bill in real time [4]. The study demonstrated that RFID-based billing significantly reduces checkout time compared to traditional barcode scanning; however, the system faced challenges related to RFID tag collision when multiple products were placed in the cart simultaneously. A barcode-based smart cart integrated with a mobile application. In this approach, users manually scanned product barcodes using a smartphone, and the bill was generated within the app. Although the system was cost-effective and easy to implement, it still required user interaction for scanning and was dependent on camera quality and lighting conditions. A smart cart system using weight sensors combined with RFID to improve accuracy in product detection. The inclusion of load cells helped verify whether an item was added or removed from the cart. While this approach improved reliability, it increased system complexity and power consumption. The use of computer vision and deep learning techniques for cashier-less shopping systems. Cameras installed on the cart or ceiling were used to recognize products visually. Although this method eliminated the need for RFID tags, it required high computational power, complex training models, and expensive hardware, making it less suitable for low-cost retail environments [5]. More recent studies have focused on cloud-connected smart carts that integrate IoT platforms for inventory management and customer analytics. These systems allow real-time data storage, digital receipts, and mobile payment options. However, issues related to data security, network reliability, and system scalability remain key research challenges. From the literature, it is evident that RFID-based smart assistant carts offer a balanced solution in terms of cost, accuracy, and ease of implementation. Existing research highlights the need for improved collision handling, energy-efficient design, and seamless integration with retail management systems. The proposed Smart Assistant Cart aims to address these gaps by providing a reliable, scalable, and user-friendly automated shopping solution.

3.       Problem Statement:

Flow Diagram

Fig 1: Flow Diagram [1]

In conventional retail and supermarket systems, the billing process is largely dependent on manual barcode scanning and cashier-operated checkout counters. This results in long waiting queues, increased billing time, human errors, and higher operational costs, especially during peak hours. Additionally, the growing demand for contactless and efficient shopping experiences highlights the limitations of traditional systems. There is a need for an automated, accurate, and user-friendly solution that can identify products, generate bills in real time, and reduce human intervention. The Smart Assistant Cart is proposed to address these issues by integrating RFID and IoT technologies to enable automatic product detection and real-time billing within the shopping cart itself.

4.       Result

The Smart Assistant Cart system was simulated using Proteus Design Suite to verify the functionality of the proposed hardware and software before real-time implementation. The simulation included the Arduino microcontroller, RFID reader module, LCD display, buzzer, and serial communication to emulate Wi-Fi data transmission.

During simulation, RFID tag values were provided as predefined inputs representing different products with unique identification numbers. When an RFID tag was detected, the microcontroller successfully read the tag ID, matched it with the stored product database, and retrieved the corresponding price. The LCD display immediately updated the item status and total billing amount, confirming real-time processing.

When multiple RFID tags were scanned sequentially, the system accurately added each item to the cart and updated the cumulative bill without duplication errors. The buzzer provided an audible alert for every successful item detection. Removal of an item (simulated using a control input) correctly adjusted the total billing amount, demonstrating system reliability.

Serial monitoring results showed correct data transmission between the Arduino and the simulated Wi-Fi module, indicating successful cloud communication. The billing data was transmitted in structured format, validating IoT connectivity for digital receipt generation and inventory monitoring.

5.       Conclusion

The Smart Assistant Cart system offers an effective and modern approach to automate the shopping and billing process in retail environments. By utilizing RFID technology, embedded microcontrollers, and IoT connectivity, the system enables automatic product detection and real-time bill generation, thereby reducing checkout time, minimizing human effort, and eliminating manual billing errors. The simulation results validate the reliability and accuracy of the proposed design, demonstrating smooth operation, quick response, and efficient data transmission. The user-friendly interface enhances customer convenience, while the contactless nature of the system supports current smart retail demands. Overall, the Smart Assistant Cart provides a scalable and cost-effective solution that can be further enhanced with advanced features such as mobile payments and inventory management for future smart store applications.