• Title/Summary/Keyword: Smart IoT

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A Study on the Use of Retailtech and Intention to Accept Technology based on Experiential Marketing (체험마케팅에 기반한 리테일테크 활용과 기술수용의도에 관한 연구)

  • Sangho Lee;Kwangmoon Cho
    • Journal of Internet of Things and Convergence
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    • v.10 no.2
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    • pp.137-148
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    • 2024
  • The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.

A Study on the Structural Relationship between IoT Usage and Life Satisfaction Among University Students (대학생의 사물인터넷 이용과 생활만족의 구조적 관계 연구)

  • Lee, Sangho;Cho, Kwangmoon
    • Journal of Internet of Things and Convergence
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    • v.7 no.2
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    • pp.55-63
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    • 2021
  • The purpose of this study was to investigate the structural relationship between the use motives of the Internet of Things (IoT), which was presented as a technology strategy priority for university students, on usage attitudes, usability performance and life satisfaction. From April 1 to April 30, 2021, a non-face-to-face survey was conducted targeting university students living in Gwangju Metropolitan City and Jeollanam-do, and the study was conducted in a total of 213 copies. The collected questionnaires were analyzed using IBM's SPSS 21.0 and AMOS 21.0 programs. The research results are as follows. First, the motivation for using IoT was found to have an effect on usage attitude, and it was found to have an effect on life satisfaction and also on usage performance. Second, it was found that the attitude of using the Internet of Things had an effect on the usability performance. However, it was found that there was no effect on life satisfaction. Third, it was found that the use of IoT has an effect on the life satisfaction of college students. Fourth, it was found that the indirect effect on the attitude of use had an indirect effect on the relationship between the motivation for use and the performance of use. However, it was found that there was no indirect effect on the relationship between use motivation and life satisfaction. Fifth, the indirect effect on the usability performance was found to have an indirect effect on the relationship between use motivation and life satisfaction, Also, it was found that there was an indirect effect on the relationship between usage attitude and life satisfaction. Sixth, in the relationship between use motivation and life satisfaction, there was no double indirect effect via use attitude and utilization performance. Based on these results, the motivation for using the Internet of Things for college students and a solution to the information gap were proposed.

Design for Safety System get On or Off the Kindergarten Bus using User Authentication based on Deep-learning (딥러닝 기반의 사용자인증을 활용한 어린이 버스에서 안전한 승차 및 하차 시스템 설계)

  • Mun, Hyung-Jin
    • Journal of Convergence for Information Technology
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    • v.10 no.5
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    • pp.111-116
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    • 2020
  • Recently, many safety accidents involving children shuttle buses take place. Without a teacher for help, a safety accident occurs when the driver can't see a child who is getting off in the blind spot of both frontside and backside. A deep learning-based smart mirror allows user authentication and provides various services. Especially, It can be a role of helper for children, and prevent accidents that can occur when drivers or assistant teachers do not see them. User authentication is carried out with children's face registered in advance. Safety accidents can be prevented by an approximate sensor and a camera in frontside and backside of the bus. This study suggests a way of checking out whether children are missed in the process of getting in and out of the bus, designs a system that reduce blind spots in the front and back of the vehicle, and builds a safety system that provide various services using GPS.

The study of the field customized SW training course design based on the analysis of the field suitability of the university SW education (대학 SW 교육의 현장 적합도 분석에 기반한 현장 맞춤형 SW 교육 과정 설계에 대한 연구)

  • Cha, Joon Seub
    • Smart Media Journal
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    • v.4 no.4
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    • pp.86-92
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    • 2015
  • Recently, it is entering the hyper connectivity age due to the development of sensor and communication technology. In particular, it is emerging new industries such as the IoT, bigdata, cloud by convergence with the ICT and other industries. Because these industries are high the gravity of the software, the demand for software manpower is increasing rapidly. But university curriculum don't deviate from the traditional curriculum, and lack of positive response to these changes is occurring a mismatch with the industry demand. In this paper, investigate a software curriculums of the four-year university, and will attempt to investigate the perception about the university software course of the corporate perspective. Also, we draw a on-site fitness of universities training course by analysis of importance on software training courses between universities and businesses. Finally, we propose a strategy model for software training course design appropriate for the field.

Research on major technology trends in the field of financial security through Korea and foreign patent data analysis (국내외 특허 데이터 분석을 통한 금융보안 분야 주요 기술 동향 분석연구)

  • Chae, Ho-Kuen;Lee, Jooyeoun
    • Journal of Digital Convergence
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    • v.18 no.6
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    • pp.53-63
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    • 2020
  • Electronic financial transactions are also actively increasing due to the rapid spread of information communication media such as the Internet, smart devices, and IoT, but as a derivative by-product, threats of financial security such as leakage of various personal information and hacking are also increasing. Therefore, the importance of financial security against this is increasing, but in Korea, financial security technology is relatively insufficient compared to advanced countries in the field of financial security, such as Active-X. Therefore, this study aims to present the major development direction in the domestic financial security field by comparing key technology trends with IPC classification frequency analysis, keyword frequency analysis, and keyword network analysis based on domestic and foreign financial security-related patent data. In conclusion, it seems that recent domestic and foreign trends have focused on the development of related technologies according to the development of smart device-based electronic financial services. Accordingly, it is intended to be used as the basis data for technology development of financial security by mapping the trend of financial security research trend and technology trend analysis through thesis data analysis that reflects the research of the preceding aspect as the technology of commercialization in the future.

Extended TAM Analysis of a Residential DR Pilot Program (확장된 기술수용모델을 이용한 가정용 에너지 수요반응 프로그램 실증분석)

  • Jung, Euna;Lee, Kyungeun;Kim, Hwayoung;Jeong, Sora;Lee, Hyoseop;Suh, Bongwon;Rhee, Wonjong
    • Journal of the HCI Society of Korea
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    • v.12 no.4
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    • pp.65-73
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    • 2017
  • While electricity demand is generally increasing, stably controlling supply is becoming a serious challenge because renewable energies are becoming popular and often their productions are dependent on the weather. The 'demand response' programs can be used to complement the problems of renewable energies, and therefore their role is becoming increasingly important. This study provides an analysis of a demand response pilot that was conducted in Korea. The study first focused on questionnaire surveys and in-depth interviews, and the data was used to perform a Technology Acceptance Model (TAM) analysis. The goal of the pilot was to have the residential users reduce their power consumptions when an energy reduction mission is issued during peak load hours. The experimental subjects consisted of two groups with different characteristics. Subjects in group A obtained smart meters as an optional function of IoT platform service provided by a mobile service company, and received a charge deduction as their compensation. Subjects in group B either voluntarily purchased smart meters as individuals or received them by participating in an energy self-sufficient village program that was run by a local government, and were entitled to a donation as their compensation. With the analysis, group A was found to fit the extended technology acceptance model that includes perceived playfulness in addition to perceived ease of use and perceived usefulness. On the contrary, group B failed to fit the model well, but perceived usefulness was found to be relatively more important compared to group A. The results indicate that the residential energy groups' behavior changes are dependent on each group's characteristics, and group-specific DR design should be considered to improve the effectiveness of DR.

Development of IoT-based real-time Toxic Chemical management System (IoT 기반의 실시간 유해 화학물 관리 시스템 개발)

  • Kang, Min-Soo;Ihm, Chunhwa;Jung, Yong-Gyu;Lee, Minho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.5
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    • pp.143-149
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    • 2016
  • Recent accidents caused by toxic chemicals and the social problems caused by frequent. As of 2010, there are more than 100,000 types of deadly toxic chemicals being distributed throughout Korea, and severely intoxicated patients along with an enormous number of patients can be induced at the time of an accident involving deadly toxic chemicals. Internationally, the seriousness of large-scale disasters due to a NBC disaster (nuclear, biologic and chemical disaster) is being highlighted as well. So, we obtain the information of the RFID tag attached to a glass bottle with containing the toxic chemical to transfer the data to the smart device has been studied a system that can monitor the status of the toxic chemical in real time. The proposed system is the information was sent to the main system using a zigbee communication by recognizing the tag vial containing the toxic chemical with the 13.56MHz bandwidths good permeability. User may check the information in real time by utilizing the smart device. However, the error of the system for managing the toxic chemical generates a result that can not be predicted. Failure of the system was detecting the error by using a comparator as this can cause an error. And the detected error proposed a duplex system so that they do not affect the overall system.

Analysis of Small Cell Technology Application for Performance Improvement in Simulation-based 5G Communication Environment (시뮬레이션 기반 5G 통신 환경에서 성능향상을 위한 스몰셀 기술 적용 분석)

  • Kim, Yoon Hwan;Kim, Tae Yeun;Lee, Dae Young;Bae, Sang Hyun
    • Smart Media Journal
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    • v.9 no.2
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    • pp.16-21
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    • 2020
  • Recently, mobile traffic is increasing exponentially as major traffic is transferred to IoT and visual media data in the dissemination of mobile communication terminals and contents use. In order to overcome the limitations of the existing LTE system, 5G mobile communication technology (5G) is a technology that meets 1000 times data traffic capacity, 4G LTE system acceptance, low latency, high energy efficiency, and high cost compared to 4G LTE system. The path loss due to the use of the frequency domain is very high, so it may be difficult to provide a service compared to the existing 4G LTE system. To overcome these shortcomings, various techniques are under study. In this paper, small cell technology is introduced to improve the system performance of 5G mobile communication systems. The performance is analyzed by comparing the results of small cell technology application, macro communication and small cell communication, and the results of the proposed algorithm application for power control. The analysis results show that the use of small cell technology in the 5th generation mobile communication system can significantly reduce the shadow area and reduce the millimeter wave path loss problem.

A Practical Attack on In-Vehicle Network Using Repacked Android Applications (커넥티드 카 환경에서 안드로이드 앱 리패키징을 이용한 자동차 강제 제어 공격)

  • Lee, Jung Ho;Woo, Samuel;Lee, Se Young;Lee, Dong Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.3
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    • pp.679-691
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    • 2016
  • As vehicle started to contain many different communication devices, collecting external information became possible in IoT environment. In such environment, remotely controling vehicle is possible when vehicle information is obtained by looking in to vehicle network through smart device. However, android based smart device applications are vulnerable to malicious modulation and redistribution. Modulated android application can lead to vehicle information disclosure that could bring about vehicle control accident which becomes threat to drivers. furthermore, since vehicles today does not contain security methods to protect it, they are very vulnerable to security threats which can cause serious damage to users and properties. In this paper, many different vehicle management android applications that are sold in Google Play has been analyzed. With this information, possible threats that could happen in vehicle management applications are being analysed to prove the risks. the experiment is done on actual vehicle to prove the risks. Also, access control method to protect the vehicle against malicious actions that could happen through external network in IoT environment is suggested in the paper.

A Study on the Design of Supervised and Unsupervised Learning Models for Fault and Anomaly Detection in Manufacturing Facilities (제조 설비 이상탐지를 위한 지도학습 및 비지도학습 모델 설계에 관한 연구)

  • Oh, Min-Ji;Choi, Eun-Seon;Roh, Kyung-Woo;Kim, Jae-Sung;Cho, Wan-Sup
    • The Journal of Bigdata
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    • v.6 no.1
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    • pp.23-35
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    • 2021
  • In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.