• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.302-313
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• 2023

This paper aims to develop a framework that can fully automate the quality management of training data used in large-scale Artificial Intelligence (AI) models built by the Ministry of Science and ICT (MSIT) in the 'AI Hub Data Dam' project, which has invested more than 1 trillion won since 2017. Autonomous driving technology using AI has achieved excellent performance through many studies, but it requires a large amount of high-quality data to train the model. Moreover, it is still difficult for humans to directly inspect the processed data and prove it is valid, and a model trained with erroneous data can cause fatal problems in real life. This paper presents a dataset reconstruction framework that removes abnormal data from the constructed dataset and introduces strategies to improve the performance of AI models by reconstructing them into a reliable dataset to increase the efficiency of model training. The framework's validity was verified through an experiment on the autonomous driving dataset published through the AI Hub of the National Information Society Agency (NIA). As a result, it was confirmed that it could be rebuilt as a reliable dataset from which abnormal data has been removed.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.77-84
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• 2017

With the entry into the aging society, we are increasingly interested in wellness, and personalized medical services through artificial intelligence are expanding. In order to provide personalized medical services, it is difficult to provide accurate medical analysis services only with the existing hospital system components PM / PA, OCS, EMR, PACS, and LIS. Therefore, it is necessary to present the hospital system model and the construction plan suitable for personalized medical service. Currently, some medical cloud services and artificial intelligence diagnosis services using Watson are being introduced in domestic. However, there are not many examples of systematic hospital system construction. Therefore, this paper proposes a hospital system model suitable for personalized medical service. To do this, we design a model that integrates medical big data construction and AI medical analysis system into the existing hospital system components, and suggest development plan of each module. The proposed model is meaningful as a basic research that provides guidelines for the construction of new hospital system in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1259-1265
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• 2022

Recently, AI, big data, and IoT technologies are being used in various solutions such as fire detection and gas or dangerous substance detection for safety accident prevention. According to the status of occupational accidents published by the Ministry of Employment and Labor in 2021, the accident rate, the number of injured, and the number of deaths have increased compared to 2020. In this paper, referring to the dataset construction guidelines provided by the National Intelligence Service Agency(NIA), the dataset is directly collected from the field and learned with YOLOv4 to propose a collision risk object detection system through object detection. The accuracy of the dangerous situation rule violation was 88% indoors and 92% outdoors. Through this system, it is thought that it will be possible to analyze safety accidents that occur in industrial sites in advance and use them to intelligent platforms research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.1-8
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• 2021

This study developed low-cost and high-efficiency pavement condition monitoring technology to produce the key information required for pavement management. A noise and artificial intelligence-based monitoring system was devised to compensate for the shortcomings of existing high-end equipment that relies on visual information and high-end sensors. From idea establishment to system development, functional definition, information flow, architecture design, and finally, on-site field evaluations were carried out. As a result, confidence in the high level of artificial intelligence evaluation was secured. In addition, hardware and software elements and well-organized guidelines on system utilization were developed. The on-site evaluation process confirmed that non-experts could easily and quickly investigate and visualized the data. The evaluation results could support the management works of road managers. Furthermore, it could improve the completeness of the technologies, such as prior discriminating techniques for external conditions that are not considered in AI learning, system simplification, and variable speed response techniques. This paper presents a new paradigm for pavement monitoring technology that has lasted since the 1960s.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.488-490
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• 2022

Recently, interest in industrial accidents such as the Industrial Safety and Health Act and the Serious Accident Punishment Act is increasing, and the demand for safety managers for safety management of workers in research institutes and industrial fields of various fields is increasing. For worker safety management, CCTVs are being installed in factories and workplaces, and workers are monitored to enhance safety management. In this paper, we intend to design a dangerous situation assessment system by constructing data using CCTV in such a workplace and modeling it in JSON format. The data modeling was produced by referring to the data set construction guide for artificial intelligence learning and the quality management guideline of the Korea National Information Society(NIA). Through this system, we want to check what kind of risk management exists in the workplace by risk situation scenario and use it to build a more systematic system.

• Management & Information Systems Review
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• v.38 no.1
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• pp.83-101
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• 2019

Blockchain is considered as an innovative technology along with Artificial Intelligence, Big Data, and Internet of Things. However, since the inception of the genesis of blockchain technology, the cryptocurrency Bitcoin, the technology is not utilized widely, not let alone disruptive applications. Most of the blockchain research deals with the cryptocurrency, general descriptions of the technology such as trend, outlook of the technology, explanation of component technology, and so on. There are no killer applications like Facebook or Google, of course. Reflecting on the slow adoption by businesses, we wanted know about the current status of the research on blockchain in Korea. The main purpose of this paper is to help business practitioners to identify the application of blockchain to enhance the competitiveness of their organization. To do that, we first use the framework by Iansiti et al (2017) and categorize the blockchain related articles published in Korea according to the framework. This is to provide a benchmark or cases of other organizations' adoption of blockchain technology. Second, based on the value proposition of blockchain applications, we suggest evolutionary paths for adopting them. Third, from the demand pull perspective of technology adoption for innovation, we propose applicable areas where blockchain applications can be introduced. Fourth, we use the value chain model to find out the appropriate domains of blockchain applications in the corporate value chains. And the five competitive forces models is adopted to find ways of lowering the power of forces by incorporating blockchain technology.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.713-722
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• 2024

This study highlights the impact of Artificial Intelligence (AI) technology on journalism, discussing its utility and addressing major ethical concerns. Broadcasting companies and media institutions, such as the Bloomberg, Guardian, WSJ, WP, NYT, globally are utilizing AI for innovation in news production, data analysis, and content generation. Accordingly, the ecosystem of AI journalism will be analyzed in terms of scale, economic feasibility, diversity, and value enhancement of major media AI service types. Through the previous literature review, this study identifies key ethical and social issues in AI journalism as well. It aims to bridge societal and technological concerns by exploring mutual development directions for AI technology and the media industry. Additionally, it advocates for the necessity of integrated guidelines and advanced AI literacy through social consensus in addressing these issues.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.35-47
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• 2020

Immediate and serious attention on CGF(computer generated forces) behavior modeling for defense M&S (modeling & simulation) is required in response to the reduction in the number of troops and development of 4^th industrial technologies. It is crucial for both military person and engineer to understand such technologies. The research aims to provide guidelines for establishment of research direction on CGF behavior modeling. We investigate traditional and/or novel methodologies such as rule-based, agent-based, and learning-based method. Discussions on future direction of applicable area and strategies are followed. We expect that the research plays a key role for understanding CGF behavior modeling.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.439-447
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• 2020

Public data refers to all data or information created by public institutions, and public information that leads to communication and cooperation among all people. Public data is an important method to lead the next generation of new industries such as artificial intelligence and smart cities, Korea is continuously ranked high in the international evaluation related to public data. However, despite the continuous efforts, the use of public data or industrial influence is insufficient. Quality issues are continuously discussed in the use of public data, but the criteria for quantitatively evaluating data are insufficient. This paper reviews indicators for public data quality evaluation and performs quantitative evaluation on selected public data. In particular, the quality of open standard data constructed and opened based on public data management guidelines is examined to determine whether government guidelines are appropriate. The data quality assessment includes the metadata and data values of open standard data, and is reviewed based on completeness and accuracy indicators. Based on the data analysis results, this paper proposes policy and technical measures for quality improvement.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.271-276
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• 2017

This project has been conducted to improve the usability of Chatbot Services such as Google(Allo) and Facebook M(Messenger. Based on the evaluation, this study aims to suggest the solutions to improve the usability of domestic Chatbot services and future directions for their development. It provides the overall understanding of the AI Chatbot service and the feature of Chatbot service through literature search. Furthermore, we summarized the current standing and the prospect of domestic messenger-based assistant Chatbot services. For conducting user evaluation, Peter Morville's honeycomb model is applied to in-depth user interviews. The followings are elements that could be amended to improve the service. The service should be incorporated by intuitive elements for users' understanding its functions and eliminate any elements that interfere with usability. The accuracy should be increased to improve the user satisfaction. This research will provide the future guidelines to improve the usability of Chabot services through continuous evaluation by users.