• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.23-29
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• 2021

Recently, a situation in which a specific content service is impossible worldwide has occurred due to a failure of the platform service and a significant social and economic problem has been caused in the global service market. In order to secure the stability of platform services, intelligent platform operation management is required. In this study, big data flow management(BDFM) and implementation method were proposed to quickly detect to abnormal service status in the platform operation environment. As a result of analyzing, BDFM technique improved the characteristics of abnormal failure detection by more than 30% compared to the traditional NMS. The big data flow management method has the advantage of being able to quickly detect platform system failures and abnormal service conditions, and it is expected that when connected with AI-based technology, platform management is performed intelligently and the ability to prevent and preserve failures can be greatly improved.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.127-133
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• 2018

The purpose of this study is to analyze the technology trend of artificial intelligent speaker(AI speaker) and to suggest direction of domestic AI speaker through the case study of AI speaker. As a research method, technical background was studied through literature, and then, case of AI speaker was investigated. As a result, It attempts to extend it to the visual interface. One of these attempts is attention to the built-in screen AI speaker. AI speakers should be a platform for humans and computers to interact with, not just convenience facilities. Based on the implications presented in this study, we hope to be able to use it as a reference for predicting the service development direction of domestic artificial intelligent speakers in the future.

• Knowledge Management Research
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• v.21 no.1
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• pp.175-195
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• 2020

The development of platform service based on the information and communication technology has revolutionized patterns of commercial transactions, driving the growth of global economy. Furthermore, the radical advancement of artificial intelligence(AI) presents the huge potential to innovate almost all the industrial and economic activities. Given these technological developments, the goal of this paper is to investigate AI's impact on the platform service innovation as well as its influence on the business performance. For the goal, this paper presents the review of the types of service innovation, the nature of platform services, and technological characteristics of leading AI technologies, such as chatbot and recommendation system. As an empirical study, this paper performs a multiple case study of Kakao Group which is the leading mobile platform service with the most advanced AI in Korea. To understand the role and effect of AI on Kakao platform service, this study investigated three cases, including chatbot agent of Kakao Bank, Smart Call service of Kakao Taxi, and music recommendation system of Kakao Mellon. The analysis results of the case study show that AI initiated innovations in platform service concepts, service delivery, and customer interface, all of which lead to a significant decrease in the transaction costs and the personalization of services. Finally, for the successful development of AI, this research emphasizes the significance of the accumulation of customer and operational data, the AI human capital, and the design of R&D organization.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.265-277
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• 2021

Data is the core of AI technology. With the development of technology, AI technology is also accelerating as the amount of data increases explosively than before. However, compared to the interest in AI education, research on data education with AI is still insufficient. According to the case analysis of exsisting AI data education, there were cases of educating the process and part of data science, but it was hard to find studies related to data collection. Cause physical computing tools have a positive effect on AI education for elementary school students, data collection cases using tools were studied, but researches related to data collection were rare. Therefore, in this study, an efficient data collection method using physical tools was designed. A structural diagram of a data collection program was created using COBL S, a modular physical computing teaching tool, and examples of program screens from the service side and the user side were configured. This study has limitations in that the establishment of an AI education platform that can be used in conjunction with future program production and programs should be prioritized as a proposal in terms of design.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.01-09
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• 2022

Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.47-54
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• 2024

The importance of cultural arts education utilizing digital tools is increasing in terms of enhancing tech literacy, self-expression, and developing convergent capabilities. The creation process and evaluation of innovative multi-modal AI, provides expanded creative audio-visual experiences in users. In particular, the process of creating music with AI provides innovative experiences in all areas, from musical ideas to improving lyrics, editing and variations. In this study, we attempted to empirically analyze the process of performing tasks using an Audio and Music Generative AI platform and discussing with fellow learners. As a result, 12 services and 10 types of evaluation criteria were collected through voluntary participation, and divided into usage patterns and purposes. The academic, technological, and policy implications were presented for AI-powered liberal arts education with learners' perspectives.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.1019-1034
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• 2022

Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.644-655
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• 2020

The study examined differences between perceptions of AI speakers and intention to continuous use of AI speakers according to usage function. We divided usage patterns into single- and multi-function orientations based on the usage by different functions of audio content (music, news, and search), and analyzed the differences between perceptions of using AI speakers and the intention to continuous use. 335 men and women who had experience using AI speakers participated in an online survey. Results are as follows. First, men used AI speakers mainly for acquiring news, and the extent to which 20s and 40s acquire news was different. Second, perceptions of usefulness and ease of use were found to be higher in the multi-functional group(music-news-search). Last, regarding the intention to continuous use of AI speakers, the multi-functional group was highest, and users focusing on music listening were relatively higher than users for other functions. The findings of the study are expected to be used as foundational data for expanding the use of AI speakers and developing strategies for service provision in each AI speaker brand.

• The Journal of Bigdata
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• v.6 no.1
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• pp.115-125
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• 2021

Due to various ICT Technology innovations and Digital Transformation, the Internet of Things(IoT) environment is increasingly requiring intelligence, decentralization, and automated service, especially an advanced and stable smart service environment in the Industrial Internet of Things(IIoT) where communication network(5G), data analysis and artificial intelligence(AI), and digital twin technology are combined. In this study, we propose IIoT Edge middleware systems for flexible interface with heterogeneous devices such as facilities and sensors at various industrial sites and for quick and stable data collection and processing.