• International journal of advanced smart convergence
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• v.6 no.1
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• pp.44-49
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• 2017

In the modern technology era, it is possible to connect objects and the internet anytime and anywhere through IoT of hyper-connected society. Accordingly, a smart shopping cart was designed and realized by applying IoT. Therefore, this paper builds the IoT shopping cart system according to the trend of IoT environment.. When RFID is installed in the Arduino and the tagged item is inserted into the IoT shopping cart, the product information and price are displayed on the Arduino linked Raspberry Pi. We built a web server on the Raspberry Pi to handle this data, and built an App on the smartphone to implement the IoT shopping cart environment. Consumers can receive pricing and product information through smartphone apps through raspberry pie, can make quick calculations through smartphone, and provide various information to consumers through apps.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.262-269
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• 2020

Recently, many attempts have been made to reduce the time required for payment in various shopping environments. In addition, for the Fourth Industrial Revolution era, artificial intelligence is advancing, and Internet of Things (IoT) devices are becoming more compact and cheaper. So, by integrating these two technologies, access to building an unmanned environment to save people time has become easier. In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep-learning object-detection technology. The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product is put into or taken out of the shopping cart, an application for smartphones that provides a user interface for a virtual shopping cart, and a deep learning server where learned product data are stored. Communication between each module is through Transmission Control Protocol/Internet Protocol, a Hypertext Transmission Protocol network, a You Only Look Once darknet library, and an object detection system used by the server to recognize products. The user can check a list of items put into the smart cart via the smartphone app, and can automatically pay for them. The smart cart system proposed in this paper can be applied to unmanned stores with high cost-effectiveness.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.37-44
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• 2009

In this paper, we present a switched beamforming RFID reader and propose a convenient shopping system using it. The smart gate with the switched beamforming RFID reader(s) improves tag detection probability, tag false alarm probability, automatic detection functionality of shopping system compared to existing RFID based systems. The proposed system consists of a smart gate to read and verify the tags within cart, a check-out counter to approve customer purchase, and a central server to manage inventory & delivery and to analyze customer purchase trend. The proposed shopping system is more practical, convenient, and cost-effective to A/S than existing RFID shopping systems.

• Journal of Distribution Science
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• v.18 no.3
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• pp.87-97
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• 2020

Purpose: The aim of this study is to understand the internal and external responses that consumers experience when they are exposed to an innovative system in retail stores. This study considered the SST(Self-Service Technology) system in a retail setting as a type of functional environmental stimuli and selected a smart shopping cart as an example of SST system. The influences of functional environmental stimuli on consumers' emotional, cognitive, and behavioral responses were examined by applying S-O-R model. In addition, this study attempted to extend the traditional S-O-R model by (a) incorporating personal characteristics variables such as time pressure and perceived crowding and (b) considering not only emotional but also cognitive aspects of consumers' internal responses. Research Design, Data, and Methodology: This study used a video-scenario technique. Participants watched a video about grocery shopping situations using a smart shopping cart and responded to their emotional, cognitive, and behavioral responses. An online survey was conducted using Amazon's Mechanical Turk (N = 185). All participants were US consumers over 20 years old and had been shopping at the grocery store in the last month. Data were analyzed through structural equations modeling with AMOS 20. Results: Test results showed that consumers who perceived higher levels of time pressure and perceived crowding in usual shopping situations were more likely to evaluate the SST system favorably. The results showed that personal characteristics have a significant impact on consumers' evaluation of functional environmental stimuli in retail setting. As consumers evaluated the SST system favorably, they experienced more positive affect and less negative affect during their shopping behaviors. Positive affect led to good service quality inference, which further increased patronize intention. However, negative affect did not show a significant impact on service quality inference, but only on patronize intention. Conclusions: This study attempted to investigate the influence of SST system by extending the traditional S-O-R model. This study classified the SST system as functional environmental stimulus of retail stores and analyzed the effect of stimulus on consumers' internal and external responses. The results of this study showed that the introduction of innovative SST can serve as an effective store differentiation strategy in an increasingly competitive retail environment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.665-667
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• 2023

본 논문에서는 효율적인 쇼핑 경험을 제공하기 위해 숏카트라는 자동화된 쇼핑 카트 시스템을 제안한다. 숏카트는 사용자의 편의성을 높이기 위해 자동화 기술을 활용하며, 사용자가 상품을 선택하면 카메라를 통해 바코드를 인식하고, Python을 활용하여 바코드값을 읽어온다. 읽어온 바코드 값을 데이터베이스의 바코드 값들과 비교하여 동일한 값을 가진 상품을 사용자의 장바구니에 자동으로 추가한다. 이를 통해 사용자는 편리하게 상품을 선택하고, 계산 과정을 자동화하여 시간을 절약할 수 있다. 또한, GUI 프로그램을 PyQT로 개발하여 사용자에게 시각적으로 장바구니 내용을 표시해 준다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.265-266
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• 2024

본 논문은 대형 마트에서의 쇼핑 편의성을 향상시키기 위한 스마트 쇼핑 카트 시스템을 제안하고 구현한 것을 다룬다. 현재의 쇼핑 환경에서 소비자들이 물품을 찾는데 불편함과 계산하는 과정에서 발생하는 대기시간의 문제점들이 있다. 본 시스템은 이 문제점을 해결하기 위해 카트 디스플레이를 활용하여 물품의 위치를 실시간으로 안내하고, 데이터베이스와 라즈베리파이를 활용하여 물품을 개별적으로 다시 스캔하지 않고도 계산대와 카트를 연결하여 자동 결제 기능을 제공한다. 이를 통해 쇼핑 과정을 효율적으로 만들어 고객들이 보다 신속하고 편리하게 쇼핑을 마칠 수 있도록 한다. 연구 결과로는 쇼핑 계산과정에서 대기시간의 감소와 물품 위치의 정확한 안내가 고객들에게 높은 효율성과 편의성을 제공한다는 점을 강조하며, 이로 인해 마트의 고객 회전률이 상승하여 지역 활성화에 기여할 것으로 기대된다.