• Title/Summary/Keyword: AI. Big data

검색결과 487건 처리시간 0.731초

Deep Learning City: A Big Data Analytics Framework for Smart Cities (딥러닝 시티: 스마트 시티의 빅데이터 분석 프레임워크 제안)

  • Kim, Hwa-Jong
    • Informatization Policy
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    • 제24권4호
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    • pp.79-92
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    • 2017
  • As city functions develop more complex and advanced, interests in smart cities are also increasing. Smart cities refer to the cities effectively solving urban problems such as traffic, safety, welfare, and living issues by utilizing ICT. Recently, many countries are attempting to introduce big data, Internet of Things, and artificial intelligence into smart cities, but they have not yet developed into comprehensive urban services. In this paper, we review the current status of domestic and overseas smart cities and suggest ways to solve issues of data sharing and service compatibility. To this end, we propose a "Deep Learning City Framework" that incorporates the deep learning technology into smart city services, and propose a new smart city strategy that safely shares spatial and temporal data in cities and converges learning data of various cities.

A Study on Prediction of Linear Relations Between Variables According to Working Characteristics Using Correlation Analysis

  • Kim, Seung Jae
    • International Journal of Internet, Broadcasting and Communication
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    • 제14권4호
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    • pp.228-239
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    • 2022
  • Many countries around the world using ICT technologies have various technologies to keep pace with the 4th industrial revolution, and various algorithms and systems have been developed accordingly. Among them, many industries and researchers are investing in unmanned automation systems based on AI. At the time when new technology development and algorithms are developed, decision-making by big data analysis applied to AI systems must be equipped with more sophistication. We apply, Pearson's correlation analysis is applied to six independent variables to find out the job satisfaction that office workers feel according to their job characteristics. First, a correlation coefficient is obtained to find out the degree of correlation for each variable. Second, the presence or absence of correlation for each data is verified through hypothesis testing. Third, after visualization processing using the size of the correlation coefficient, the degree of correlation between data is investigated. Fourth, the degree of correlation between variables will be verified based on the correlation coefficient obtained through the experiment and the results of the hypothesis test

Development of online drone control management information platform (온라인 드론방제 관리 정보 플랫폼 개발)

  • Lim, Jin-Taek;Lee, Sang-Beom
    • Journal of the Institute of Convergence Signal Processing
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    • 제22권4호
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    • pp.193-198
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    • 2021
  • Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

AI Advisor for Response of Disaster Safety in Risk Society (위험사회 재난 안전 분야 대응을 위한 AI 조력자)

  • Lee, Yong-Hak;Kang, Yunhee;Lee, Min-Ho;Park, Seong-Ho;Kang, Myung-Ju
    • Journal of Platform Technology
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    • 제8권3호
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    • pp.22-29
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    • 2020
  • The 4th industrial revolution is progressing by country as a mega trend that leads various technological convergence directions in the social and economic fields from the initial simple manufacturing innovation. The epidemic of infectious diseases such as COVID-19 is shifting digital-centered non-face-to-face business from economic operation, and the use of AI and big data technology for personalized services is essential to spread online. In this paper, we analyze cases focusing on the application of artificial intelligence technology, which is a key technology for the effective implementation of the digital new deal promoted by the government, as well as the major technological characteristics of the 4th industrial revolution and describe the use cases in the field of disaster response. As a disaster response use case, AI assistants suggest appropriate countermeasures according to the status of the reporter in an emergency call. To this end, AI assistants provide speech recognition data-based analysis and disaster classification of converted text for adaptive response.

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Nearest Neighbor-based Pre-processing Scheme for Advanced Skyline Query (최근접 이웃 탐색 기반의 향상된 스카이라인 질의를 위한 전처리 기법)

  • Kim, Ji-Hyun;Lee, SangMin;Jeon, Hyeongjun;Jin, ChangGyun;Kim, JiYunm;Kwon, Jin youngm;Kim, Jongwanm;Oh, Dukshinm
    • Proceedings of the Korea Information Processing Society Conference
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    • 한국정보처리학회 2020년도 춘계학술발표대회
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    • pp.420-423
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    • 2020
  • 스카이라인 질의는 객체의 속성을 기준으로 사용자의 선호에 적합한 대상을 탐색하는 기법이다. 기존 스카이라인 질의는 일괄처리 방식으로 탐색 결과를 반환하지만 대화형 앱이나 모바일 환경과 같이 잦은 위치이동 발생 시 일괄처리 방식으로 스카이라인 질의 결과를 신속하게 받기 어렵다. 최근접 이웃(Nearest Neighbor) 알고리즘은 사용자와 상호 작용이 필요한 대화형 앱에서 실시간으로 선호 객체를 탐색하여 사용자에게 전달함으로써 객체의 반환 속도를 향상시켰다. 그러나 최근접 이웃 알고리즘은 객체 탐색 과정에서 반복적인 비교 연산을 수행하여 불필요한 탐색 시간이 소요된다. 본 논문은 대화형 앱에서 신속한 스카이라인 결과를 산출하고자 연산 대상 객체의 범위를 축소함으로써 최근접 이웃 스카이라인 질의 알고리즘의 성능을 향상시킨 전처리 기법을 제안한다. 데이터 객체는 최대 40,000 개의 실험에서 제안 기법은 최근접 이웃 알고리즘보다 50% 빠른 성능을 나타내어 본 연구의 가용성이 증명되었다.

Innovation and Challenges of Urban Creative Products in Digital Media Art - Tourist cities in China for example

  • Ma Xiaoyu;Lee Jaewoo
    • International Journal of Advanced Culture Technology
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    • 제12권1호
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    • pp.175-181
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    • 2024
  • The paper examines the impact of digital media art on urban creative products, analyzing opportunities and challenges in the digital era. It emphasizes the development of urban cultural and creative products, highlighting their significance and future growth potential. The digital media era provides unprecedented innovation opportunities, utilizing advanced tools for efficient design, production, and marketing. Trends like personalization, customization, AI, and big data offer new expressions and market prospects. Cultural products evolve in design, marketing, and sales channels due to digital media, with tools like social media and e-commerce platforms opening new promotion avenues. Case studies illustrate digital media's role in driving innovation and enhancing user experiences. The paper addresses challenges in market competition, copyright, and technological renewal, while recognizing opportunities from AI and big data. The creative industries must adapt and innovate to remain relevant. Looking ahead, urban creative products will evolve under digitalization, relying on digital means to attract consumers and enhance brand value. Cultural products, beyond economic entities, disseminate urban culture and creative spirit. In the digital era, urban creative products demonstrate potential and necessity, prompting a reevaluation of digital technology's role. Through continuous innovation, this field contributes to cultural and economic levels, impacting urban characteristics and heritage. Urban creative products play an increasingly vital role in the global cultural and creative economy.

A Study on the Metadata Schema for the Collection of Sensor Data in Weapon Systems (무기체계 CBM+ 적용 및 확대를 위한 무기체계 센서데이터 수집용 메타데이터 스키마 연구)

  • Jinyoung Kim;Hyoung-seop Shim;Jiseong Son;Yun-Young Hwang
    • Journal of Internet Computing and Services
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    • 제24권6호
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    • pp.161-169
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    • 2023
  • Due to the Fourth Industrial Revolution, innovation in various technologies such as artificial intelligence (AI), big data (Big Data), and cloud (Cloud) is accelerating, and data is considered an important asset. With the innovation of these technologies, various efforts are being made to lead technological innovation in the field of defense science and technology. In Korea, the government also announced the "Defense Innovation 4.0 Plan," which consists of five key points and 16 tasks to foster advanced science and technology forces in March 2023. The plan also includes the establishment of a Condition-Based Maintenance system (CBM+) to improve the operability and availability of weapons systems and reduce defense costs. Condition Based Maintenance (CBM) aims to secure the reliability and availability of the weapon system and analyze changes in equipment's state information to identify them as signs of failure and defects, and CBM+ is a concept that adds Remaining Useful Life prediction technology to the existing CBM concept [1]. In order to establish a CBM+ system for the weapon system, sensors are installed and sensor data are required to obtain condition information of the weapon system. In this paper, we propose a sensor data metadata schema to efficiently and effectively manage sensor data collected from sensors installed in various weapons systems.

A Study on AI Evolution Trend based on Topic Frame Modeling (인공지능발달 토픽 프레임 연구 -계열화(seriation)와 통합화(skeumorph)의 사회구성주의 중심으로-)

  • Kweon, Sang-Hee;Cha, Hyeon-Ju
    • The Journal of the Korea Contents Association
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    • 제20권7호
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    • pp.66-85
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    • 2020
  • The purpose of this study is to explain and predict trends the AI development process based on AI technology patents (total) and AI reporting frames in major newspapers. To that end, a summary of South Korean and U.S. technology patents filed over the past nine years and the AI (Artificial Intelligence) news text of major domestic newspapers were analyzed. In this study, Topic Modeling and Time Series Return Analysis using Big Data were used, and additional network agenda correlation and regression analysis techniques were used. First, the results of this study were confirmed in the order of artificial intelligence and algorithm 5G (hot AI technology) in the AI technical patent summary, and in the news report, AI industrial application and data analysis market application were confirmed in the order, indicating the trend of reporting on AI's social culture. Second, as a result of the time series regression analysis, the social and cultural use of AI and the start of industrial application were derived from the rising trend topics. The downward trend was centered on system and hardware technology. Third, QAP analysis using correlation and regression relationship showed a high correlation between AI technology patents and news reporting frames. Through this, AI technology patents and news reporting frames have tended to be socially constructed by the determinants of media discourse in AI development.

A Study on the Data Collection and Analysis System for Learning Experiences in Learner-Centered Customized Education (학습자 중심의 맞춤형 교육을 위한 학습 경험 데이터 수집 및 분석 체계 연구)

  • Sang-woo Kim;Myung-suk Lee
    • Journal of Practical Engineering Education
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    • 제16권2호
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    • pp.159-165
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    • 2024
  • This study investigates the comprehensive system for collecting intelligent learning activity data tailored to learner-centered personalized education. We compared and analyzed the characteristics of xAPI, Caliper analytics, and cmi5, which are learning activity data collection standards, and established a system that allows not only standardized data but also non-standardized learning activity data to be stored as big data for artificial intelligence learning analysis. As a result, the system was structured into five stages: defining data types, standardizing learning data using xAPI, storing big data, conducting learning analysis (statistical and AI-based), and providing learner-tailored services. The aim was to establish a foundation for analyzing learning data using artificial intelligence technology. In future research, we will divide the entire system into three stages, implement and execute it, and correct and supplement any shortcomings in the design.

A Study on the Protection and Utilization of Personal Information for the Operation of Artificial Intelligence and Big Data in the Fourth Industrial Revolution (4차 산업혁명기 인공지능과 빅데이터 운용을 위한 개인정보 보호와 이용에 관한 연구)

  • Choi, Won Sang;Lee, Jong Yong;Shin, Jin
    • Convergence Security Journal
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    • 제19권5호
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    • pp.63-73
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    • 2019
  • In the 4th Industrial Revolution, information is collected and analyzed from people and objects through the rapid development of ICT. It is possible to create value. However, there are many legal and institutional restrictions on the collection of information aimed at people.Therefore, in-depth research on the protection and use of personal information in the rapidly changing cyber security environment is needed. The purpose of this study is to protect and utilize personal information for the operation of AI (Artificial Intelligence) and big data during the 4th Industrial Revolution. It is to seek a paradigm shift. The organization of the research for this is: Chapter 1 examines the meaning of personal information during the 4th Industrial Revolution, Chapter 2 presents the framework for the review and analysis of prior research. In Chapter 3, after analyzing policies for the protection and utilization of personal information in major countries, Chapter 4 looks at the paradigm shift in personal information protection during the 4th Industrial Revolution and how to respond. Chapter 5 made some policy suggestions for the protection and utilization of personal information.