• 제목/요약/키워드: Big-Data Platform

검색결과 503건 처리시간 0.024초

The status of metaverse and digital twin technology development

  • CHUNG, Myung-Ae;KIM, Kyung-A;KANG, Min-Soo
    • 한국인공지능학회지
    • /
    • 제10권2호
    • /
    • pp.19-24
    • /
    • 2022
  • Metaverse refers to a world that transcends reality. Metaverse is a compound word of meta (transcendence) and universe (universe). The impact of the corona pandemic has provided an opportunity to rapidly grow the metaverse based on realistic content along with online and non-face-to-face environments. Various content and service platforms reflecting the concepts of metaverse and digital twin are rapidly spreading around the world in line with the pandemic situation. As their needs accelerate in response to the COVID-19 situation, the technology of metaverse and digital twin is attracting attention again as an indispensable condition for business, culture and art, national industry, and public services. In particular, the metaverse requires the balanced development of ecosystem components based on various advanced convergence technologies. In this paper, the concept of metaverse and digital twin, types of platforms, and development status are examined, and trends of key element technologies are investigated and analyzed. As these key element technologies, XR sensory technology, avatar technology, and other XR devices and parts were examined. Through this, we want to clearly pinpoint the direction in which the metaverse will develop through future technologies, services, and follow-up research.

Analysis of Google's success factors and direction

  • LEE, Sang-Youn;KIM, Se-Jin
    • 한국인공지능학회지
    • /
    • 제8권2호
    • /
    • pp.11-16
    • /
    • 2020
  • Among the innovative companies leading the era of the 4th industrial revolution, the world's largest Internet company is Google. Google has grown by providing convenient services such as Internet search, Android smartphone operating system, and video. Now, Google is leading the global IT industry by continuing to develop in various new business fields based on open service platforms, artificial intelligence, and big data. In this study, an exploratory discussion was conducted on Google's success factors and future directions. The purpose of the research is to understand the development process of the IT field from the successfactors of Google and to analyze the development direction of the future IT industry. Google's success factors were its open platform policy and successful acquisitions of external companies. In fact, most of the services Google offers come from companies that have acquired and acquired them. In addition, there was a corporate culture that values and supportsthe spirit of challenge and autonomy of members who are not afraid of failure. Based on this study's review of Google's direction analysis, the follow-up study will infer the direction of the IT industry in depth and look at the future technologies that IT majors need to prepare.

Neural Network and Cloud Computing for Predicting ECG Waves from PPG Readings

  • Kosasih, David Ishak;Lee, Byung-Gook;Lim, Hyotaek
    • Journal of Multimedia Information System
    • /
    • 제9권1호
    • /
    • pp.11-20
    • /
    • 2022
  • In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

The Intelligent Blockchain for the Protection of Smart Automobile Hacking

  • Kim, Seong-Kyu;Jang, Eun-Sill
    • Journal of Multimedia Information System
    • /
    • 제9권1호
    • /
    • pp.33-42
    • /
    • 2022
  • In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

인공지능 교육을 위한 멀티 플랫폼 오목 프로그램 설계 (Design of a Multi-Platform Omok Program for Artificial Intelligence Education)

  • 차주형;우영운
    • 한국정보통신학회:학술대회논문집
    • /
    • 한국정보통신학회 2021년도 추계학술대회
    • /
    • pp.530-532
    • /
    • 2021
  • 본 논문은 프로그래밍의 기초 교육을 이수한 개발자가 빅데이터와 인공지능을 학습하기 위해, C/C++ 언어로 프로그래밍을 할 수 있는 인공지능 교육서비스에 대해 다룬다. 또한 개발 환경에 따른 맞춤형 개발 환경 구성 시스템과 사용자가 인공지능 구현하여 테스트하는 방법에 대해 설명한다. 이 외에도 다양한 내부 파라미터 조작을 통해 인공지능에 미치는 영향을 확인할 수 있는 기능을 갖추고 있다. 향후 네트워크 통하여 언어의 제약이 없는 인공지능 교육 서비스 개발이 가능할 것으로 예상한다.

  • PDF

물류 스타트업 육성방안에 관한 연구 -인천광역시를 중심으로- (A Study on Activation Plan for Logistics Startups in Korea - Focused on Incheon Metropolitan City)

  • 강동준;이명화;강효원
    • 무역학회지
    • /
    • 제46권2호
    • /
    • pp.263-280
    • /
    • 2021
  • With the advent of the era of the 4th Industrial Revolution, various support policies and programs are being introduced as the promotion of startups related to the 4th industry is promoted as a core policy of the government. Based on major technologies such as Artificial Intelligence(AI), Big Data, Internet of Things(IoT), Blockchain, and Automation leading the 4th industrial revolution, logistics and distribution companies are expanding the range of markets and services provided. The purpose of this study is to examine the current status of startups in the logistics field based on major technologies of the 4th Industrial Revolution, which are rapidly growing at home and abroad, and suggest implications for revitalizing logistics startups through a policy demand survey. As a result of the study, in order to foster domestic logistics startups, we propose policy support for integration of logistics startups, integrated management of information, provision of physical space, network platform, and practical education and mentoring.

가상화 환경의 안전한 데이터 공유를 위한 다중 인스턴스간 상호인증 기법 (Mutual Authentication Scheme between Multiple Instances for Secure Data Share of Virtualized Environment)

  • 최도현;김상근
    • 한국인터넷방송통신학회논문지
    • /
    • 제16권6호
    • /
    • pp.83-94
    • /
    • 2016
  • 최근 클라우드, 빅데이터, 인공지능 등 다양한 분야의 서버 플랫폼이 가상화 기술을 사용하고 있지만 지속적으로 발생하는 구조적인 보안 취약성이 이슈화 되고 있다. 또한 대부분 가상화 보안 기술은 종류가 제한적이고 플랫폼 제공자에 의존적인 것으로 알려져 있다. 본 논문은 가상화 환경의 안전한 데이터 공유를 위한 다중 인스턴스간 상호인증 기법에 대해 제안한다. 제안하는 기법은 다중 인스턴스 간에 독립적인 상호인증을 고려하여 보안 구조를 설계하고 키 체인 기법을 적용하여 데이터 공유에 보안 프로토콜의 안전성을 강화 시켰다. 성능분석 결과 기존 보안 구조와는 다른 방식의 안전한 가상화 인스턴스 세션을 생성하고, 상호인증 과정의 각 인스턴스에 대한 효율성이 우수 하다는 것을 확인하였다.

인공지능 기반의 데이터 분석을 적용한 건강검진 지식 베이스 구축 모델링 연구 (Study on the Modeling of Health Medical Examination Knowledge Base Construction using Data Analysis based on AI)

  • 김봉현
    • 융합정보논문지
    • /
    • 제10권6호
    • /
    • pp.35-40
    • /
    • 2020
  • 미래 사회로 접어들면서, 건강한 삶의 증대를 위한 노력은 현대인들의 주요 관심 분야이다. 특히, ICT 기술과 경쟁력 있는 의료산업 환경을 융합하여 건강한 삶을 위한 기술 개발은 차세대 성장 동력으로 자리잡고 있다. 따라서, 본 논문에서는 건강 검진 프로세스에서 검진 결과에 대한 인공지능 기반의 데이터 분석을 적용하여 종합 판정의 신뢰성을 향상시킬 수 있는 지식 베이스 모델링을 구축하는 연구를 수행하였다. 이를 위해, 딥러닝 분석을 통한 알고리즘을 설계하여 검사 결과지수를 산출, 검증하고, 판정 지식을 통한 종합 검진 정보를 제공하는 모델링을 연구하였다. 제안한 모델링의 적용을 통해, 국민 건강에 대한 빅데이터 분석, 활용이 가능하여 의료비 절감 및 건강 증대의 효과를 기대할 수 있다.

스마트 IT 융합 플랫폼을 위한 지능형 센서 기술 동향 (Intelligent Sensor Technology Trend for Smart IT Convergence Platform)

  • 김혜진;진한빛;염우섭;김이경;박강호
    • 전자통신동향분석
    • /
    • 제34권5호
    • /
    • pp.14-25
    • /
    • 2019
  • As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.

텍스트마이닝을 활용한 정보보호 키워드 기반 소셜미디어 빅데이터 분석 (Social Media Bigdata Analysis Based on Information Security Keyword Using Text Mining)

  • 정진명;박영호
    • 한국산업정보학회논문지
    • /
    • 제27권5호
    • /
    • pp.37-48
    • /
    • 2022
  • 디지털 기술의 발전으로 사회적 이슈들이 SNS와 같은 디지털 기반 플랫폼을 통해서 소통되고 여론을 형성하기도 한다. 본 연구에서는 소셜미디어를 통해서 공유되고 있는 정보보호 이슈관련 여론을 살펴보기 위하여 대표적인 단문 소셜네트워크서비스인 트위터 빅데이터 분석을 진행하였다. 2021년 1년간 14개 정보보호 관련 키워드를 중심으로 데이터를 수집한 후, 데이터마이닝 기술을 활용하여 용어 빈도(TF)분석과 피어슨 계수를 활용한 상관분석을 통해 키워드간의 상관관계를 밝혔다. 또한 잠재적 확률기반 LDA 토픽모델링을 실시하여 정보보호분야에 많은 관심을 받았던 6개의 주요 토픽을 도출하였다. 이러한 결과는 관련 산업의 전략수립이나, 정부 정책수립 시 주요 키워드를 도출하는 기초데이터로 활용될 수 있을 것으로 기대된다.