• Title/Summary/Keyword: Edge AI

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A Study on the Introduction of Livestock U-healthcare (가축 U-Healthcare 도입방안 연구)

  • Koo, Jee-Hee;Jung, Tae-Woong;Ahn, Ji-Yeon;Lee, Sang-Rak
    • Journal of Animal Environmental Science
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    • v.18 no.2
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    • pp.85-90
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    • 2012
  • In Korea, livestock has grown into the most value-added business in the agricultural and forest industry. But due to the recent outbreak of deadly infectious diseases such as foot-and-mount disease and avian influenza (AI), the demand for IT-enabled cutting-edge management system is getting stronger. As for humans, pilot projects and researches concerning U-healthcare have been carried out since early 2000. So this study explored the current progress of U-healthcare introduction, and suggested the strategies to develop technologies of collecting, processing, and utilizing information; to apply elements for a service model development and prioritization; to provide policy and institutional support. Therefore it is expected to vitalize the livestock U-healthcare in the future through continuous study based on these results.

A Study on Effective Team Learning Support in Non-Face-To-Face Convergence Subjects (비대면 수업 융합교과의 효과적인 팀학습 지원에 관한 연구)

  • Jeon, Ju Hyun
    • Journal of Engineering Education Research
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    • v.24 no.6
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    • pp.79-85
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    • 2021
  • In a future society where cutting-edge science technology such as artificial intelligence becomes commonplace, the demand for talented people with basic knowledge of mathematics and science is expected to increase continuously, and the educational infrastructure suitable for the characteristics of future generations is still insufficient. In particular, in the case of students taking convergence courses including practical training, there was a problem in communication with the instructor. In this study, we looked at the current status of distance learning at domestic universities that came suddenly due to the global pandemic of COVID-19. In addition, a case study of the use of technology was conducted to facilitate the interaction between instructors and learners through case analysis of distance classes in convergence subjects. Therefore, this study aims to introduce the case of developing lecture contents for smooth convergence education in a non-face-to-face educational environment targeting the developed AI convergence courses and applying them to the education of enrolled students.

Implementation of Lane Departure Warning System using Lightweight Deep Learning based on VGG-13 (VGG-13 기반의 경량화된 딥러닝 기법을 이용한 차선 이탈 경고 시스템 구현)

  • Kang, Hyunwoo
    • Journal of Korea Multimedia Society
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    • v.24 no.7
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    • pp.860-867
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    • 2021
  • Lane detection is important technology for implementing ADAS or autonomous driving. Although edge detection has been typically used for the lane detection however, false detections occur frequently. To improve this problem, a deep learning based lane detection algorithm is proposed in this paper. This algorithm is mounted on an ARM-based embedded system to implement a LDW(lane departure warning). Since the embedded environment lacks computing power, the VGG-11, a lightweight model based on VGG-13, has been proposed. In order to evaluate the performance of the LDW, the test was conducted according to the test scenario of NHTSA.

Zero Accident, Connected Autonomous Driving Vehicle (사고제로, 커넥티드 자율이동체)

  • Choi, J.D.;Min, K.W.;Kim, J.H.;Seo, B.S.;Kim, D.H.;Yoo, D.S.;Cho, J.I.
    • Electronics and Telecommunications Trends
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    • v.36 no.1
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    • pp.22-31
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    • 2021
  • In this thesis, we examine the development status of autonomous mobility services using various artificial intelligence algorithms and propose a solution by combining edge and cloud computing to overcome technical difficulties. A fully autonomous vehicle with enhanced safety and ethics can be implemented using the proposed solution. In addition, for the future of 2035, we present a new concept that enables two- and three-dimensional movement via cooperation between ecofriendly, low-noise, and modular fully autonomous vehicles. The zero-error autonomous driving system will safely and conveniently transport people, goods, and services without time and space constraints and contribute to the autonomous mobility services that are free from movement in connection with various mobility.

Technology Trends and Research Direction of 6G Mobile Core Network (6G 모바일 코어 네트워크 기술 동향 및 연구 방향)

  • Ko, N.S.;Park, N.I.;Kim, S.M.
    • Electronics and Telecommunications Trends
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    • v.36 no.4
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    • pp.1-12
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    • 2021
  • The competition to lead the next generation of mobile technologies, 6G, is underway while the deployment of 5G has not been implemented worldwide. ITU-R plans to develop technical requirements and standards after completing the 6G Vision by 2023. It can be considered too early to have a concrete view of the 6G core network architecture from this timeline. However, major stakeholders have started making their presence felt by publishing their views. From updated analysis on the technology and service trends proposed, we present a list of research directions on 6G core network from several perspectives: distribution of network functions to nearer edge locations; future fixed-mobile convergence, including low earth orbit satellites; highly-precise QoS guarantee; supporting an extremely wide variety of service requirements; AI-native automation and intelligence; and aligning with the evolution of radio access network.

Bankruptcy Prediction with Explainable Artificial Intelligence for Early-Stage Business Models

  • Tuguldur Enkhtuya;Dae-Ki Kang
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.3
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    • pp.58-65
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    • 2023
  • Bankruptcy is a significant risk for start-up companies, but with the help of cutting-edge artificial intelligence technology, we can now predict bankruptcy with detailed explanations. In this paper, we implemented the Category Boosting algorithm following data cleaning and editing using OpenRefine. We further explained our model using the Shapash library, incorporating domain knowledge. By leveraging the 5C's credit domain knowledge, financial analysts in banks or investors can utilize the detailed results provided by our model to enhance their decision-making processes, even without extensive knowledge about AI. This empowers investors to identify potential bankruptcy risks in their business models, enabling them to make necessary improvements or reconsider their ventures before proceeding. As a result, our model serves as a "glass-box" model, allowing end-users to understand which specific financial indicators contribute to the prediction of bankruptcy. This transparency enhances trust and provides valuable insights for decision-makers in mitigating bankruptcy risks.

A Study on the Green Smart School Integrated Platform (그린 스마트 스쿨 통합 플랫폼에 관한 연구)

  • Lee, Chaegyu;Oh, Seokju;Jeong, Jongpil
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.286-287
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    • 2022
  • 정부의 한국판 그린뉴딜 정책 발표와 함께 주요 과제 중 하나인 그린 스마트 스쿨의 관심도가 점점 커지고 있다. 이에 따라 성공적인 그린 스마트 스쿨 구축을 위한 솔루션이 필요해지고 있다. 본 논문은 체계화 되지 않은 그린 스마트 스쿨의 전체 시스템 관점에서 문제를 해결하기 위한 Cloud-Edge와 AI를 적용한 그린 스마트 스쿨 통합 플랫폼을 제안한다.

TrapMI: Protecting Training Data to Evade Model Inversion Attack on Split Learning (TrapMI: 분할 학습에서 모델 전도 공격을 회피할 수 있는 훈련 데이터 보호 방법)

  • Hyun-Sik Na;Dae-Seon Choi
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.234-236
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    • 2023
  • Edge AI 환경에서의 DNNs 학습 방법 중 하나인 분할 학습은 모델 전도 공격으로 인해 입력 데이터의 프라이버시가 노출될 수 있다. 본 논문에서는 분할 학습 환경에서의 모델 전도 공격에 대한 기존 방어 기술들의 한계점을 회피할 수 있는 TrapMI 기술을 제안하고, 이를 통해 입력 이미지를 원 본 데이터 세트의 도메인에서 특정 타겟 이미지 도메인으로 이동시킴으로써 이미지 복원의 가능성을 최소화시킨다. 추가적으로, 테스트 과정에서 타겟 이미지의 정보를 알 수 없는 제약을 회피하기 위해 AutoGenerator를 구축한 후 실험을 통해 원본 데이터 보호 성능을 검증한다.

DNN Hybrid Scheduling Algorithm in Smart Camera Edge Cluster (스마트 카메라 엣지 클러스터에서 DNN 하이브리드 스케줄링 알고리즘)

  • Chan-Min Lee;Min-Seok Seo;Ju-Seong Park;Min-Gyu Jin;Hyung-Bin Park;Su-Kyoung Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.84-85
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    • 2023
  • 본 논문에서는 엣지 컴퓨팅에서 다수의 스마트 카메라를 클러스터링하여 협업하며 로드 밸런싱을 수행하는 알고리즘을 제안하고, Kubernetes 환경에서 시뮬레이션을 통해 여러 가지 상황에서 성능을 검증하여 엣지 컴퓨팅에서의 AI 연산을 보다 효율적으로 수행할 수 있는 방법을 제시한다.

Smart Factory Activation Plan through Analysis of Smart Factory Promotion Status and Introduction Plan Data

  • Seong-Hoon Lee
    • International journal of advanced smart convergence
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    • v.13 no.2
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    • pp.229-234
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    • 2024
  • A smart factory is defined as a cutting-edge, intelligent factory that integrates all production processes from product planning to sales with information and communication technology. Through these factories, each company produces customized products with minimal cost and time. The smart factory promotion project in Korea has produced positive results even in difficult environments such as the COVID-19 situation. Through the transition to a smart manufacturing production system, the competitiveness of small and medium-sized businesses has been greatly strengthened, including increased productivity and reduced costs. This study was based on surveyed data conducted by organizations related to smart factory promotion in 2020. Significant contents and major characteristics that emerged from the surveyed data were inferred and described. Since the meaningful contents reflect the reality of the company, more efficient promotion of smart factories will be possible in the future.