• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.509-523
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• 2015

With the introduction of smart devices as a new channel of information distribution, the mass tourism that has been dominating the travel scene is being transformed into individual tourism. Therefore, it is more than important to establish an advanced smart tourism environment using cutting-edge ICT technologies in order to go into one of tourism developed countries. In line with that, this study draws both local and international cases to show where smart tourism stands now by mapping out problems and solutions by category. Firstly, in terms of infrastructure, establishing distribution platform and big data analyzing systems were suggested. Secondly, to fit the needs of consumers, converged tourism content and user experience based content development are in need. Lastly, in terms of governance forming public-private consultative body and incubating creative tourism companies are suggested. The study results will serve as a fruitful reference to those who want to establish business strategy related to smart tourism.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.35-45
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• 2021

The e-commerce industry using mobile or web is growing rapidly, and the emergence of various platform services is causing innovative changes in the e-commerce industry. This study aims to identify the attachment types of e-commerce users and to demonstrate the relationship between the PPerceived Usefulness, and Perceived Ease of Use by TAM. In order to empirically verify the research model of this study, a survey was conducted on ordinary people with experience using e-commerce and path analysis was conducted by using PLS to analyze its Internal consistency, Confirmatory factor analysis, Discriminant validity and Goodness-of-fit verification. As a result, a significant relationship between Perceived Stability, Perceived Usefulness, and Perceived Ease of Use was identified, could verify the association with the TAM and Acceptance Intention.

• Journal of Korea Entertainment Industry Association
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• v.14 no.5
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• pp.1-14
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• 2020

This study conducted a topic modeling and semantic network analysis of 'korean wave' and its meaning in Korean society from 2000 to 2019 by applying an agenda setting theory. For this purpose, a total of 197,992 newspaper articles which reported 'korean wave' issues were analyzed by applying topic modeling and semantic network analysis. As a result, first, the word 'korean wave' mainly appeared in korean-related regions in the korean press. culture and economy. second, a total of 9 topics related to korean wave issues appeared. This was followed by 'broadcast', 'export', 'domestic and foreign affairs', 'education', 'beauty and fashion', 'music and performance', 'tourism', 'media(platform)', and 'region'. Lastly, korean wave was mainly discussed at the cultural and economic ares. In addition, it was clustered into five characteristics: 'cultural hallyu', 'business hallyu', 'education', 'environment', and 'geography'.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.53-58
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• 2024

IoT, Big-data, AI, and Cloud technologies, which are core technologies of the 4th Industrial Revolution, have recently been applied to various fields and are being used as core technologies for new growth engines. Accordingly, these core technologies are applied to the agricultural field without exception, contributing to solving the problem of labor shortage, reducing production costs, and reducing environmental burden through remote and automated production without time and space constraints. However, as these core technologies are utilized, security incidents are occurring in the agricultural field as well. Accordingly, this study divides smart farms into three stages(Basic, Middle, and High) and presents the characteristics and security threats of each stage. In particular, as the number of container-based services and research increases under cloud platforms, we would like to suggest countermeasures focusing on security threats.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.206-209
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• 2018

According to data released by the WHO(World Health Organization), the death toll from indoor air pollution in 2016 was about 3.8 million. While many people are aware of outdoor air pollution, indoor air pollution is getting less attention. Recently, however, indoor air pollution has also become a big problem, raising many issues. Frequent indoor activities such as cooking and heating produce various pollutants, which can cause children and elderly with weak immune systems to be exposed to pollutants, which can cause serious health problems such as poor lung function and respiratory diseases. Therefore, in this paper, the IoT(Internet of Things) platform that measures and monitors indoor air quality using AQ(Air Quality) sensors is developed so that data can be monitored in real time through applications and reactive web.

• Journal of Platform Technology
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• v.8 no.3
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• pp.22-29
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• 2020

The 4th industrial revolution is progressing by country as a mega trend that leads various technological convergence directions in the social and economic fields from the initial simple manufacturing innovation. The epidemic of infectious diseases such as COVID-19 is shifting digital-centered non-face-to-face business from economic operation, and the use of AI and big data technology for personalized services is essential to spread online. In this paper, we analyze cases focusing on the application of artificial intelligence technology, which is a key technology for the effective implementation of the digital new deal promoted by the government, as well as the major technological characteristics of the 4th industrial revolution and describe the use cases in the field of disaster response. As a disaster response use case, AI assistants suggest appropriate countermeasures according to the status of the reporter in an emergency call. To this end, AI assistants provide speech recognition data-based analysis and disaster classification of converted text for adaptive response.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.75-80
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• 2018

The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.141-154
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• 2022

In the data economy era, various policies are being implemented to create an active data distribution environment. In South Korea, the formation of a big data distribution platform and data trading began with the launch of the Financial Data Exchange under public data governance. In the case of major advanced countries in the data field, they have built a data distribution environment based on the data broker industry for decades and have strengthened national data competitiveness through added values generated from the industry. However, behind the active data distribution through data brokers, there are numerous information security issues, which have resulted in various privacy issues and national security threats. These problems can occur sufficiently in the process of domestic financial data exchange. In our study, we analyzed various information security issues of data trading caused by data brokers and derived information security requirements to be considered when trading data. We verified whether information security requirements are well reflected in the information security policy for each transaction stage of the domestic financial data exchange. Based on the verification, measurements to strengthen information security for financial data exchange are presented in our paper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.274-280
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• 2017

The smart-car industry has emerged as the important variable that will decide the future industrial contour of the automotive industry, together with commercialization of electronic vehicles, connected cars, infotainment, telematics, and the autonomous/self-driving car. This study analyzes the strategic position of platform companies and car manufacturers that would determine the future of the smart-car market. The findings of this study show that despite the entry barriers in industrial factors, such as economies of scale, the industrial infrastructure, and global production networks, and technical factors like exclusive head-sector information, car manufacturers may be deprived of their industrial leadership by platform companies with map and user data, big data capabilities, and user interface experience if they lag behind ICT innovation. This insight is based on the emerging importance of software and platforms, and the simplification of car structures, proven by the successful commercialization of electronic vehicles. This study complements existing studies mainly focused on technical aspects of the smart-car industry by examining the strategic dimensions of platform companies and their approach to the future smart-car market by comparing them with existing car manufacturing multinationals.

• Knowledge Management Research
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• v.21 no.3
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• pp.229-247
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• 2020

In the remarkable growth of P2P financial platform in the field of knowledge management, only companies with big data and machine learning technologies are surviving in fierce competition. The ability to analyze borrowers' credit is most important, and platform companies are also recognizing this capability as the most important business asset, so they are building a credit evaluation system based on artificial intelligence. Nonetheless, online P2P platform providers that offer related services only act as intermediaries to apply for investors and borrowers, and all the risks associated with the investments are attributable to investors. For investors, the only way to verify the safety of investment products depends on the reputation of P2P companies from newspaper and online website. Time series information such as delinquency rate is not enough to evaluate the early stage of Korean P2P makers' credit analysis capability. This study examines the credit analysis procedure of P2P loan platform using artificial intelligence through the case analysis method for well known the top three companies that are focusing on the credit lending market and the kinds of information data to use. Through this, we will improve the understanding of credit analysis techniques through artificial intelligence, and try to examine limitations of credit analysis methods through artificial intelligence.