• Review of Korea Contents Association
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• v.1 no.2
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• pp.75-82
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• 2003

인터넷의 보급과 더불어 대용량 저장장치의 가격이 하락하면서 멀티미디어 데이터의 저장과 공유가 보편화되었다. 또한 멀티미디어 데이터를 활용하는 지리정보시스템, 멀티미디어 의료 정보시스템, 전자신문, 전자도서관, 홈쇼핑, VOD등의 새로운 응용 분야들이 각광을 받고 있다. 이러한 환경적인 요인은 대용량의 멀티미디어 테이터를 효율적으로 추출, 저장, 검색하기 위한 멀티미디어 데이터 처리기술이 요구된다.(중략)

• Korean Institute of Interior Design Journal
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• v.19 no.2
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• pp.15-23
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• 2010

First appeared in the 1970s, the underground shopping mall has been spreading across the country, and there reportedly exist 77 malls in the 2010. After over 30 decades operation, many underground shopping malls are now under the planning phase for renovation in many cities. This study considers the renovation issue of the underground shopping mall in the perspective of spatial re-configuration. A case is taken from Kangnam TerminalUnderground Shopping Mall in Seoul for detailed observation and suggestion. The monotonous and confusingspatial layout of the existing mall is investigated by observation methods. Based on the observation, a modifiedplan is suggested and evaluated by means of computer simulation program, Depth Map. The program mainly deals with visual network analysis in order to quantify the optical exposure in a given space. It is argued in this paper that the enhanced visual connectedness could affect the pedestrian performance positively in the shopping mall, and this leads to an easy and quick access to each shops in users' stand point. It is thought that this configurational solution for the remodelling of a specific case would be an effective reference for other malls in the country which are facing the similar problems.

• Journal of the Korea Computer Industry Society
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• v.5 no.8
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• pp.819-828
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• 2004

Recently, while research for the ubiquitous networking and ubiqutous computing is gone with activity, RFID(Radio Frequency IDentification) that recognize movement of things and take position advantage of RFID echnology in ubiquitous environment are required. In this paper, we propose and design a system that can taking customer's position in large size mart and analyzing customer's shopping movement to manage customer and merchandise of most suitable.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.246-254
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• 2007

최근 유비쿼터스 환경이 대두됨에 따라 정보의 밀도가 높아지고 있으며, 기업에서는 고객이 제품을 구매함과 동시에 고객의 정보를 저장하여 활용할 수 있게 되었다. 이와 같은 환경은 고객의 요구사항을 사전에 미리 파악하여 적절한 시점과 상황에 맞는 정보를 전달할 수 있도록 하는 추천시스템에 대한 필요성을 증대시켰으며, 다양한 영역에서 추천시스템과 관련된 연구들이 활발하게 이루어지고 있다. 지금까지의 추천시스템은 주로 제품 중심으로 논의되어 왔으나, 유비쿼터스 시장 환경에서는 매장에 대한 논의가 필요하게 되었다. 이는 고객이 다양한 매장을 방문할 수 있으며, 동일한 제품이라도 여러 매장에 동시에 존재할 수 있고, 매장 간의 동선이나 매장의 위치 및 분위기, 제품의 품질이나 가격 등에 대한 개인 선호도에 따라 같은 제품이라도 선호하는 매장은 다를 수 있기 때문이다. 따라서 본 연구에서는 고객의 선호도를 기반으로 유비쿼터스 시장 환경에 적합한 매장 추천시스템을 제안하고자 한다. 매장 추천시스템은 협업 필터링을 기반으로 하고 있으며, Apriori 알고리즘을 이용하여 관련성이 높은 매장들의 집합을 찾아 추천한다. 이 시스템은 기업보다는 고객 중심의 서비스를 제공해 줌으로써 고객의 쇼핑 효율성을 제고시킬 뿐 아니라 장기적인 관점에서 시장 활성화에 기여할 수 있을 것으로 기대한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.504-506
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• 2015

RFID란, 무선 주파수를 이용해 원거리에서 태그의 정보를 판독하거나 인식할 수 있는 객체 인식 기술 중 하나이다. 최근 바코드를 대체하여 RFID 기술을 이용하는 산업이 물류, 유통, 환경, 보안 등 다양한 분야에 걸쳐 전 세계적으로 성장세를 보이고 있는 추세이다. 특히 RFID 기술 중 위치 탐지 및 측정 기술을 이용한 사례가 많다. 본 연구에서도 이러한 기술을 이용하여 공항이나 쇼핑몰 등과 같은 넓고 개방된 공간에서 객체들을 추적하는 시스템을 구현하고자한다. 모든 객체들이 RFID를 가지고 있는 환경에서 Cluster와 센서 네트워크를 이용해 RFID를 감지하면 RFID의 데이터를 서버에 전송하고 서버는 이 데이터들을 분석하여 객체의 위치 및 동선을 추적한다. 객체 추적을 함으로써 정확하고 신뢰성이 있는 데이터를 얻는 것을 본 연구의 목적으로 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.111-112
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• 2023

학교, 대형 쇼핑몰, 공항 등과 같은 큰 실내 공간에서는 군중의 동선과 밀도를 파악하고 관리하는 것은 안전사고와 연관되어 있어 매우 중요하다. 와이파이 센싱은 기존에 존재하던 CCTV 카메라나 센서를 활용한 혼잡도 관리보다 효율적이고 정확한 방식으로 추정하는 데 도움이 되며, 설치 및 유지보수 측면에서도 효율적이다. 본 논문에서는 실내 환경에서 군중 수를 추정하기 위해 딥 러닝을 이용한 무선랜 신호 분석 기법을 제안한다. 송수신기가 같은 공간에 위치했던 기존 연구들과는 달리 본 논문에서는 송신기와 수신기가 서로 다른 공간에 배치된 환경에서도 무선랜 수신 신호를 통해 다른 공간의 군중 수를 정확히 예측할 수 있다는 것을 실험으로 검증하였다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.75-82
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• 2022

There are various exhibition halls, shopping malls, theme parks around us and analysis of interest in exhibits or contents is mainly done through questionnaires. These questionnaires are mainly depend on the subjective memory of the person being investigated, resulting in incorrect statistical results. Therefore, it is possible to identify an exhibition space with low interest by tracking the movement and counting the number of visitors. Based on this, it can be used as quantitative data for exhibits that need replacement. In this paper, we use deep learning-based artificial intelligence algorithms to recognize visitors, assign IDs to the recognized visitors, and continuously track them to identify the movement path. When visitors pass the counting line, the system is designed to count the number and transmit data to the server for integrated management.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.99-106
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• 2021

This study examined whether relationship marketing activities affected relationship satisfaction and ultimately relationship continuity intention for 180 online store users. As a result of hypothesis test through path analysis, it was found that financial activities and structural activities such as delivery services in shopping malls had a positive effect on relationship satisfaction. In particular, it was found that the influence of structural activities was greater. This suggests that fast delivery or easy-to-search traffic is more meaningful to relationship satisfaction than economic benefits. At the significance level p<0.05, it was found that social activities did not have a significant effect on relationship satisfaction. Because it is not easy to develop social bonds between salespeople and customers at online stores, but the direction is considered positive. Therefore, if online stores can form social bonds with customers, this will have a positive effect on relationship satisfaction, but it is expected that this will become a factor that can differentiate them from competitors.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.61-74
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• 2012

As the retail industry has been challenged by stiff competition, the retailer becomes more interested in better understanding consumers' in-store behavior to gain and sustain competitive advantage. Consumers' shopping paths provide valuable clues to understanding customers' in-store behavior, which has been a long standing research issue in business. This study is to explore the shopping path patterns in a grocery using RFID technology and clustering method. To this end, we designed the RFID systems, affixing active RFID tags to the bottom of grocery carts. The tag emit signal that is received by receptors installed at various location throughout the store. The RFID systems provide the time and location of the cart while consumers shop around the store. The point of sale data are matched with the cart movement records to provide a complete picture of each shopping path. To find the distinctive patterns of consumers' shopping paths, we proposed the distance-index matrix using dijkstra method and normalization method to conduct the clustering in order to handle the problem in measuring the similarity among shopping paths, which is raised by the spatial nature of consumer movement in a grocery. After analyzing the RFID data obtained in one of the groceries in a major Korean retailer, we could successfully identify several distinctive patterns of shopping paths, which prove to provide the valuable implications for store management.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.91-110
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• 2012

Recently the effort of retailers improving the efficiency of store operations by using the information technology (IT) is increasing. Among them, the analysis of the shoppers' flow in retail stores is one of the critical tasks since it is an essential part in optimizing store layout and item grouping, and in developing the customized services specialized to shoppers' classification. Agent-Based Modeling and Simulation (ABMS) is one of the most promising methods which support analyzing the shoppers' flow. In this paper, we suggested a shopper's behavior model and developed an agent-based simulator for optimizing the operations of retail stores. In order to model the shoppers' behavior, we analyzed the behavioral characteristics of shoppers based on their shopping lists, suggesting BDI-based agent models of the shoppers' behavior. The shopping agent model were suggested, which has an additional mental state, the shopper's behavioral characteristic, as well as the original mental states of the BDI theory which has beliefs, desires and Intentions. The result of this study can be used in as a preliminary study for modeling and simulation of retail stores congestion and in the end the optimization of item grouping and store layout.