• Title/Summary/Keyword: AI Utilization

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5G Mobile Communications: 4th Industrial Aorta (5G 이동통신: 4차 산업 대동맥)

  • Kim, Jeong Su;Lee, Moon Ho
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.1
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    • pp.337-351
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    • 2018
  • This paper discusses 5G IOT, Augmented Reality, Cloud Computing, Big Data, Future Autonomous Driving Vehicle technology, and presents 5G utilization of Pyeongchang Winter Olympic Games and Jeju Smart City model. The reason is that 5G is the main artery of the 4th industry.5G is the fourth industrial aorta because 5G is the core infrastructure of the fourth industrial revolution. In order for the AI, autonomous vehicle, VR / AR, and Internet (IoT) era to take off, data must be transmitted several times faster and more securely than before. For example, if you send a stop signal to LTE, which is a communication technology, to a remote autonomous vehicle, it takes a hundredth of a second. It seems to be fairly fast, but if you run at 100km / h, you can not guarantee safety because the car moves 30cm until it stops. 5G is more than 20 gigabits per second (Gbps), about 40 times faster than current LTE. Theoretically, the vehicle can be set up within 1 cm. 5G not only connects 1 million Internet (IoT) devices within a radius of 1 kilometer, but also has a speed delay of less than 0.001 sec. Steve Mollenkov, chief executive officer of Qualcomm, the world's largest maker of smartphones, said, "5G is a key element and innovative technology that will connect the future." With 5G commercialization, there will be an economic effect of 12 trillion dollars in 2035 and 22 million new jobs We can expect to see the effect of creation.

Life Satisfaction Depending on Digital Utilization Divide within People with Disabilities (스마트 도시(Smart City)의 데이터 경제 구현을 위한 개인정보보호 적용설계(PbD)의 도입 필요성 분석)

  • Jin, Sang-Ki
    • Informatization Policy
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    • v.26 no.3
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    • pp.69-89
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    • 2019
  • In order to implement smart cities that will become living spaces in the fourth industrial revolution era, detailed privacy information such as residents' living information, buildings and facilities information must be collected and processed in real time. While city functions and convenience for individuals are being facilitated, threats to personal information exposure and leakage are also likely to increase at the same time. Therefore, the design concept for personal information protection should be considered and accordingly reflected from the stages of smart city design, technology development and operation planning of intelligent information (AI) facilities. The results of the analysis show that for activation of smart cities and operation of data-driven cities, the concept of Privacy by Design (PbD) has already been introduced in the institutional, industrial and technological aspects, particularly in the cases of European countries and the US. In order to strengthen the local and global competitiveness of smart cities and the country, Korea also needs to actively deploy PbD as a strategy to secure a data-driven economy, which is the core strategy for smart cities. Therefore, the study suggests policy implications focused on approaches to legislative improvement and technology development support, which reflect the basic properties of PbD as defined in the study.

Digital Transformation Based on Chatbot in Legacy Environment (챗봇을 이용한 Legacy 환경의 Digital Transformation)

  • Jang, Jeong-ho;Kim, Jin-soo;Lee, Kang-Yoon
    • The Journal of Bigdata
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    • v.3 no.2
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    • pp.79-85
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    • 2018
  • As the utilization of chatbots grows and the AI market grows, many companies are interested. And everybody is spurring growth by offering chatbot build services so that they can create chatbots. This makes chatbots easier to service on the messenger platform, which is changing the existing application market. In this paper, we present a methodology for designing and implementing existing DB-based applications as instant messenger platform-based applications, and summarize what to consider in actual implementation to provide an optimal system structure. According to this methodology, we design and implement a chatbot that serves as an teaching advisor who provides information to the students in the curriculum. The implemented application objectively visualizes the user's desired information from the user's point of view and delivers it through the interactive interface quickly and intuitively. By implementing these services and real service, it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. Enterprise legacy application will take chatbot technology as one of important digital transformation initiative.

Technology Convergence & Trend Analysis of Biohealth Industry in 5 Countries : Using patent co-classification analysis and text mining (5개국 바이오헬스 산업의 기술융합과 트렌드 분석 : 특허 동시분류분석과 텍스트마이닝을 활용하여)

  • Park, Soo-Hyun;Yun, Young-Mi;Kim, Ho-Yong;Kim, Jae-Soo
    • Journal of the Korea Convergence Society
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    • v.12 no.4
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    • pp.9-21
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    • 2021
  • The study aims to identify convergence and trends in technology-based patent data for the biohealth sector in IP5 countries (KR, EP, JP, US, CN) and present the direction of development in that industry. We used patent co-classification analysis-based network analysis and TF-IDF-based text mining as the principal methodology to understand the current state of technology convergence. As a result, the technology convergence cluster in the biohealth industry was derived in three forms: (A) Medical device for treatment, (B) Medical data processing, and (C) Medical device for biometrics. Besides, as a result of trend analysis based on technology convergence results, it is analyzed that Korea is likely to dominate the market with patents with high commercial value in the future as it is derived as a market leader in (B) medical data processing. In particular, the field is expected to require technology convergence activation policies and R&D support strategies for the technology as the possibility of medical data utilization by domestic bio-health companies expands, along with the policy conversion of the "Data 3 Act" passed by the National Assembly in January 2019.

Development of Noise and AI-based Pavement Condition Rating Evaluation System (소음도·인공지능 기반 포장상태등급 평가시스템 개발)

  • Han, Dae-Seok;Kim, Young-Rok
    • 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.

A Study on Geospatial Information Role in Digital Twin (디지털트윈에서 공간정보 역할에 관한 연구)

  • Lee, In-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.268-278
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    • 2021
  • Technologies that are leading the fourth industrial revolution, such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cyber-physical systems (CPS) are developing and generalizing. The demand to improve productivity, economy, safety, etc., is spreading in various industrial fields by applying these technologies. Digital twins are attracting attention as an important technology trend to meet demands and is one of the top 10 tasks of the Korean version of the New Deal. In this study, papers, magazines, reports, and other literature were searched using Google. In order to investigate the contribution or role of geospatial information in the digital twin application, the definition of a digital twin, we investigated technology trends of domestic and foreign companies; the components of digital twins required in manufacturing, plants, and smart cities; and the core techniques for driving a digital twin. In addition, the contributing contents of geospatial information were summarized by searching for a sentence or word linked between geospatial-related keywords (i.e., Geospatial Information, Geospatial data, Location, Map, and Geodata and Digital Twin). As a result of the survey, Geospatial information is not only providing a role as a medium connecting objects, things, people, processes, data, and products, but also providing reliable decision-making support, linkage fusion, location information provision, and frameworks. It was found that it can contribute to maximizing the value of utilization of digital twins.

Research on the Evaluation and Utilization of Constitutional Diagnosis by Korean Doctors using AI-based Evaluation Tool (인공지능 기반 평가 도구를 이용한 한의사의 체질 진단 평가 및 활용 방안에 대한 연구)

  • Park, Musun;Hwang, Minwoo;Lee, Jeongyun;Kim, Chang-Eop;Kwon, Young-Kyu
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.36 no.2
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    • pp.73-78
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    • 2022
  • Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.

Data-Driven Technology Portfolio Analysis for Commercialization of Public R&D Outcomes: Case Study of Big Data and Artificial Intelligence Fields (공공연구성과 실용화를 위한 데이터 기반의 기술 포트폴리오 분석: 빅데이터 및 인공지능 분야를 중심으로)

  • Eunji Jeon;Chae Won Lee;Jea-Tek Ryu
    • The Journal of Bigdata
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    • v.6 no.2
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    • pp.71-84
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    • 2021
  • Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

A Study on the Utilization of Drilling Investigation Information (시추조사 정보 활용방안에 관한 연구)

  • Jinhwan Kim;Yong Baek;Jong-Hyun Lee;Gyuphil Lee;Woo-Seok Kim
    • The Journal of Engineering Geology
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    • v.33 no.4
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    • pp.531-541
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    • 2023
  • The most important thing in the 4th industry, AI era, and smart construction era is digital data. Basic data in the civil engineering field begins with ground investigation. The Ministry of Land, Infrastructure and Transport operates the Geotechnical Information Database Center to manage ground survey data, including drilling but the focus is on data distribution. This study seeks to devise a plan for long-term use of the results of drilling investigation conducted for the design and construction of various construction projects. For this purpose, a pilot area was set up and a 'geotechnical design parameters digital map' was created using some geotechnical design parameters from the drilling investigation data. Using the developed algorithm, a digital map of friction angle and permeability coefficient for the hard rock stratum in the pilot area was created. Geotechnical design parameters digital map can identify the overall condition of the ground, but reliability needs to be improved due to the lack of initial data input. Through additional research, it will be possible to produce a more complete geotechnical design parameters digital map.

A Study on the Intelligent Online Judging System Using User-Based Collaborative Filtering

  • Hyun Woo Kim;Hye Jin Yun;Kwihoon Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.1
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    • pp.273-285
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    • 2024
  • With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.