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DNA (Data, Network, AI) 기반 지능형 정보 기술

DNA (Data, Network, AI) Based Intelligent Information Technology

  • 윤주상 (동의대학교 산업ICT기술공학전공) ;
  • 한연희 (한국기술교육대학교 미래융합공학전공)
  • 발행 : 2020.11.30

초록

4차 산업혁명 시대에 다양한 분야에서 ICT 기술 간 융합에 대한 요구가 증가하고 있다. 이에 마쳐 데이터, 네트워크, 인공지능 기술이 결합한 새로운 용어인 DNA(Data, Network, AI)가 사용 중이다. DNA는 지능형 응용 및 서비스 개발에 있어 잠재적 기술력을 가지고 있다. 이에 본 논문에서는 DNA 기술 기반의 논리적 포그 네트워크 기반의 서비스 이미지 배치 기술, 산업용 무선 센서 네트워크에서의 기계학습 기반 이동성 기술, 뇌신호 주파수 특성을 이용한 CNN 기반 BCI 성능 예측 기술, 소스코드 주제를 이용한 인공신경망 기반 경고 분류 방법 기술, 챗봇 환경에서 데이터 시각화 인터랙션을 위한 자연어처리 기술에 대한 심사 완료된 논문들을 소개한다.

In the era of the 4th industrial revolution, the demand for convergence between ICT technologies is increasing in various fields. Accordingly, a new term that combines data, network, and artificial intelligence technology, DNA (Data, Network, AI) is in use. and has recently become a hot topic. DNA has various potential technology to be able to develop intelligent application in the real world. Therefore, this paper introduces the reviewed papers on the service image placement mechanism based on the logical fog network, the mobility support scheme based on machine learning for Industrial wireless sensor network, the prediction of the following BCI performance by means of spectral EEG characteristics, the warning classification method based on artificial neural network using topics of source code and natural language processing model for data visualization interaction with chatbot, related on DNA technology.

키워드

참고문헌

  1. Zeus Kerravala, "The Success of Artificial Intelligence and Machine Learning: Requires an Architectural Approach to Infrastructure," CISCO, August 2018.
  2. Jonghwa Choi and Sanghyun Ahn, "Service Image Placement Mechanism Based on the Logical Fog Network," KIPS Transactions on Computer and Communication Systems, Vol.9, No.11, pp.250-255, 2020. https://doi.org/10.3745/KTCCS.2020.9.11.250
  3. Sangdae Kim, Cheonyong Kim, Hyunchong Cho, Kwansoo Jung, and Seungmin Oh, "Mobility Support Scheme Based on Machine Learning in Industrial Wireless Sensor Network," KIPS Transactions on Computer and Communication Systems, Vol.9, No.11, pp.256-264, 2020. https://doi.org/10.3745/KTCCS.2020.9.11.256
  4. Jae-Hwan Kang, Sung-Hee Kim, Joosang Youn, and Junsuk Kim, "Prediction of the Following BCI Performance by Means of Spectral EEG Characteristics in the Prior Resting State," KIPS Transactions on Computer and Communication Systems, Vol.9, No.11, pp.265-272, 2020. https://doi.org/10.3745/KTCCS.2020.9.11.265
  5. Jung-Been Lee, "Warning Classification Method Based On Artificial Neural Network Using Topics of Source Code," KIPS Transactions on Computer and Communication Systems, Vol.9, No.11, pp.273-280, 2020. https://doi.org/10.3745/KTCCS.2020.9.11.273
  6. Sang Heon Oh, Su Jin Hur, and Sung-Hee Kim, "Natural Language Processing Model for Data Visualization Interaction in Chatbot Environment," KIPS Transactions on Computer and Communication Systems, Vol.9, No.11, pp.281-290, 2020. https://doi.org/10.3745/KTCCS.2020.9.11.281