• International journal of advanced smart convergence
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• v.12 no.2
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• pp.108-116
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• 2023

Smart home and artificial intelligence technologies are developing rapidly, and various smart home systems associated with artificial intelligence (AI) improved the quality of living for people. In the present research, we examine the role of individuals' motivational system in their responses to the application of AI in smart homes. In particular, this research focuses on individuals' prevention motivational system and investigates whether individuals' attitudes toward the application of AI in smart homes differ according to their level of prevention motivation. Specifically, it is hypothesized that individuals with strong (vs. weak) prevention motivation will have more favorable attitudes toward the application of AI in smart homes. Consistent with the hypothesis, the results reveal that the respondents in the strong (vs. weak) prevention motivation reported significantly more favorable attitudes toward the six types of AI-based application in smart homes (e.g., AIbased AR/VR games, AI pet care system, AI robots, etc.). Our findings suggest that individuals' prevention motivational system may be an effective market segmentation tool in facilitating their positive responses to the application of AI in smart homes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.84-86
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• 2022

최근 미디어, 금융 등 다양한 분야의 기업들이 AI를 활용해 제공하는 서비스가 늘어남에 따라 학습된 모델을 엣지 자원에 배포하여 기능을 제공하는 서비스형태 또한 늘어나고 있다. AI-Application이 동작하기 위해서는 AI-Model 파일뿐 아니라 동작을 위한 설정 파일들이 필요하여 AI-Application이 사용 중인 AI-Model의 정보를 수집, 관리하는 것은 중요한 이슈라고 할 수 있다. 하지만 단일 서비스서버에서 동작하는 형태가 아닌 각 자원이 산재되어 다양한 형태로 서비스를 제공하는 엣지컴퓨팅의 구조적인 특성상 AI-Application의 기존 서비스구조, 기능을 수정하지 않고 정보를 수집하는 과정은 다양한 문제에 부딪치게 된다. 이에 따라 본 논문에서는 기존 서비스구조를 변경하지 않고 독립적으로 AI-Application에서 사용중인 AI-Model의 정보를 파악하고, 사용자 요청에 대응할 수 있는 관리구조를 제안한다.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.99-110
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• 2021

Governments around the world are actively establishing strategies and initiatives to spread the use of artificial intelligence (AI), for AI is not a mere new technology, but is an innovative technology that brings about extensive changes in industrial and social structures and is a core engine that will lead the 4th Industrial Revolution. The South Korean government has also been paying attention to AI as a technology and tool for innovative growth, but its application to the industries is still rather sluggish. The government has prepared multifarious AI-related policies with the aim of constructing South Korea as an AI powerhouse, but there is no clear strategy on which detailed policies to implement first and which industries to apply AI preferentially. With these limitations of South Korea's AI policies in mind, this paper analyzed the priorities of industries in AI adoption and the priorities of AI-related national policies, using Delphi-AHP method for 30 top-level AI experts in South Korea. The results of analysis show that AI application is urgent and necessary in the fields of medical/healthcare, public and safety, and manufacturing, which seems to reflect the peak of the COVID-19 crisis in the second half of 2020 at the time of the investigation. And it turns out that policies related to AI talent cultivation, data, and R&D investment are important and urgent above all in order for organizations to apply AI. This suggests that strategies are required to focus limited national resources on these industries and policies first.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.19-24
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• 2024

The future military combat environment is rapidly expanding the role and importance of artificial intelligence (AI) in defense, aligning with the current trends of declining military populations and evolving dynamics. Particularly, in the civilian sector, AI development has surged into new domains based on foundation models, such as OpenAI's Chat-GPT, categorized as Super-Giant AI or Hyperscale AI. The U.S. Department of Defense has organized Task Force Lima under the Chief Digital and AI Office (CDAO) to conduct research on the application of Large Language Models (LLM) and generative AI. Advanced military nations like China and Israel are also actively researching the integration of Super-Giant AI into their military capabilities. Consequently, there is a growing need for research within our military regarding the potential applications and fields of application for Super-Giant AI in weapon systems. In this paper, we compare the characteristics and pros and cons of specialized AI and Super-Giant AI (Foundation Models) and explore new application areas for Super-Giant AI in weapon systems. Anticipating future application areas and potential challenges, this research aims to provide insights into effectively integrating Super-Giant Artificial Intelligence into defense operations. It is expected to contribute to the development of military capabilities, policy formulation, and international security strategies in the era of advanced artificial intelligence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1103-1110
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• 2022

Due to the rapid development of AI-related industries, countless edge devices are working in the real world. Since data generated within the smart space consisted of these devices is beyond imagination, it is becoming increasingly difficult for edge devices to process. To solve this issue, EdgeCPS has appeared. EdgeCPS is a technology to support harmonious execution of various application services including AI applications through interworking between edge devices and edge servers, and augmenting resources/functions. Therefore, we propose a knowledge-sharing graph-based componentized AI application support system applicable to the EdgeCPS platform. The graph is designed to effectively store information which are essential elements for creating AI applications. In order to easily change resource/function augmentation under the support of the EdgeCPS platform, AI applications are operated as components. The application support system is linked with the knowledge graph so that users can easily create and test applications, and visualizes the execution aspect of the application to users as a pipeline.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.7-16
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• 2024

This study aims to explore driving factors of Artificial Intelligence application for city marketing strategy with perspectives of millennials and generation Z. This study proposed the following research questions: i) how perceived place branding factor, public service factor, affective factor, immersive experience factor, cognitive factor, cost benefit factor, social networking factor, and promotional value factor affect attitude toward AI application for city marketing; and ii) how attitude affect satisfaction and prospect toward AI application for city marketing? This study conducted an online survey with the assistance of a well-known research agency and applied factor and regression analysis to test hypotheses. The results found that effects of place branding, cognitive, social networking, and promotional value affect attitude significantly in the case of millennials, while effects of public service, affective, cost benefit, social networking, and promotional value affect attitude significantly in the case of generation Z. The results found that effects of attitude on satisfaction and prospect of AI showed significance. The results provide implications and different aspects for AI application of city marketing strategy with perspectives by generations, while millennials and generation Z perceived effects of promotional value as the most significant factor for AI application of city marketing strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2867-2881
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• 2022

This study investigates fashion Artificial Intelligence (AI) curation services to expand sustainable consumption. We analyzed the factors that affect the AI fashion curation service experience of women in their 20s and 30s using their clothes. An online survey was conducted from March 29, 2021, to June 4, 2021, for women of the previously mentioned age groups residing in the metropolitan area. Before answering the questionnaire, they installed the "Style Bot" application on their phone, took five or more photos of their clothes according to the manual provided by the application, stored them in a virtual wardrobe on the application, and then responded to the questionnaire using the AI recommended coordinating function. The effect of the properties of fashion AI curation service application on the use of clothes was investigated. Among the attributes of the fashion AI curation service application, convenience, speed, and usefulness were found to have a positive effect on the use of clothes, and promptness had no effect. Second, regarding the impact of clothing utilization on environmental sustainability, clothing utilization was found to have a positive effect on environmental sustainability. Third, environmental sustainability was found to have a positive effect on satisfaction. Fourth, clothing utilization had a positive effect on satisfaction. Thus, fashion AI curation service would help promote service development so that clothes could be used actively through an in-depth understanding of the properties of these services. Finally, the results of this study would contribute to promoting environmental sustainability.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.856-857
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• 2023

실종자를 찾는 빈번한 안전재난문자로 인해 피로도가 높아짐에 따라 본 연구에서는 실종자 탐색 문자 발송량을 줄이기 위해 드론과 인공지능을 활용하여 도시에서의 실종자 탐색의 가능성을 제시한다. 실시간으로 얼굴을 인식하여 실종자를 탐색하는 접근 방식을 사용하여 구현해 실종자 탐색이 가능함을 보였고 이를 통해 인구 밀집 지역에서의 실종자 탐색이 효율적일 것으로 기대한다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.31-38
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• 2024

In this paper, we propose an ASAP(AI-driven Service for Advertisement Production) application that provides a generative AI-based automatic advertising image production service. This application utilizes GPT-3.5 Turbo Instruct to generate suitable background mood and promotional copy based on user-entered keywords. It utilizes OpenAI's DALL·E 3 model and Stability AI's SDXL model to generate background images and text images based on these inputs. Furthermore, OCR technology is employed to improve the accuracy of text images, and all generated outputs are synthesized to create the final advertisement. Additionally, using the PILLOW and OpenCV libraries, text boxes are implemented to insert details such as phone numbers and business hours at the edges of promotional materials. This application offers small business owners who face difficulties in advertising production a simple and cost-effective solution.

• The Journal of Economics, Marketing and Management
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• v.12 no.1
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• pp.29-38
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• 2024

Purpose: The purpose of this study is to explore the perceptions of millennials and Generation Z regarding AI applications in marketing, an area that has been rarely explored in previous researches. This study formulated research questions how millennials and Generation Z perceive the impact of brand image, AI-assistant customer service, affective factor, immersive experience, cognitive factor social factor and competitiveness of products and brands on overall attitude through the lens of AI applications in marketing. Additionally, this study also explored the influence of overall attitudes on satisfaction, intention to use, and loyalty towards AI applications. Research design, data and methodology: To gather data, this study employed an online survey conducted in collaboration with a reputable research organization. This study utilized factor analysis, ANOVA, and regression analysis for data analysis. Results: The findings revealed that the impact of brand image, AI-assistant customer service, and competitiveness on attitude demonstrated significance in both millennials and generation Z cohorts. The study identified that cognitive and social factors significantly influenced attitudes among millennials, whereas affective and immersive experiences showed significance in influencing attitudes among Generation Z. Conclusions: The findings offer valuable managerial implications, shedding light on the application of AI in marketing with distinct perspectives between millennials and Generation Z.