• Title/Summary/Keyword: Intelligent cloud

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Analyzing Characteristics of the Smart City Governance (스마트시티 거버넌스 특성 분석)

  • LEE, Sang-Ho;LEEM, Youn-Taik
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.2
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    • pp.86-97
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    • 2016
  • This study aims to analyze the characteristics of the smart city governance through the multi-layer governance model, which includes administrative governance(AG), technological governance(TG), and global governance(GG). The results of the smart city governance are as follows. Multi-layered governance was modeled to enable cross-checking of each element of the propelling process and types of governance. AG has transitioned from a public partnership to a public-private people partnership(pppp) through a public-private partnership(ppp). TG has the characteristics of information communication technologies(ICTs) - eco technologies(EcoTs) - Spatial technology convergence including physical center, information software platforms such as the CCTV convergence center, and virtualization such as the cloud data center. GG aims at developing killer applications and ICTs-embedded space with intelligent buildings such as a smart city special zone to enable overseas exports. The smart city roadshow and forum have been developed as a platform for overseas exports with competition as well as cooperation.

Combined Artificial Bee Colony for Data Clustering (융합 인공벌군집 데이터 클러스터링 방법)

  • Kang, Bum-Su;Kim, Sung-Soo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.203-210
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    • 2017
  • Data clustering is one of the most difficult and challenging problems and can be formally considered as a particular kind of NP-hard grouping problems. The K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, it has high possibility to trap in local optimum and high variation of solutions with different initials for the large data set. Therefore, we need study efficient computational intelligence method to find the global optimal solution in data clustering problem within limited computational time. The objective of this paper is to propose a combined artificial bee colony (CABC) with K-means for initialization and finalization to find optimal solution that is effective on data clustering optimization problem. The artificial bee colony (ABC) is an algorithm motivated by the intelligent behavior exhibited by honeybees when searching for food. The performance of ABC is better than or similar to other population-based algorithms with the added advantage of employing fewer control parameters. Our proposed CABC method is able to provide near optimal solution within reasonable time to balance the converged and diversified searches. In this paper, the experiment and analysis of clustering problems demonstrate that CABC is a competitive approach comparing to previous partitioning approaches in satisfactory results with respect to solution quality. We validate the performance of CABC using Iris, Wine, Glass, Vowel, and Cloud UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KABCK (K-means+ABC+K-means) is better than ABCK (ABC+K-means), KABC (K-means+ABC), ABC, and K-means in our simulations.

Group key management protocol adopt to cloud computing environment (클라우드 컴퓨팅 환경에 적합한 그룹 키 관리 프로토콜)

  • Kim, Yong-Tae;Park, Gil-Cheol
    • Journal of Digital Convergence
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    • v.12 no.3
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    • pp.237-242
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    • 2014
  • Recently, wind energy is expanding to combination of computing to forecast of wind power generation as well as intelligent of wind powerturbine. Wind power is rise and fall depending on weather conditions and difficult to predict the output for efficient power production. Wind power is need to reliably linked technology in order to efficient power generation. In this paper, distributed power generation forecasts to enhance the predicted and actual power generation in order to minimize the difference between the power of distributed power short-term prediction model is designed. The proposed model for prediction of short-term combining the physical models and statistical models were produced in a physical model of the predicted value predicted by the lattice points within the branch prediction to extract the value of a physical model by applying the estimated value of a statistical model for estimating power generation final gas phase produces a predicted value. Also, the proposed model in real-time National Weather Service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

6G in the sky: On-demand intelligence at the edge of 3D networks (Invited paper)

  • Strinati, Emilio Calvanese;Barbarossa, Sergio;Choi, Taesang;Pietrabissa, Antonio;Giuseppi, Alessandro;De Santis, Emanuele;Vidal, Josep;Becvar, Zdenek;Haustein, Thomas;Cassiau, Nicolas;Costanzo, Francesca;Kim, Junhyeong;Kim, Ilgyu
    • ETRI Journal
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    • v.42 no.5
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    • pp.643-657
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    • 2020
  • Sixth generation will exploit satellite, aerial, and terrestrial platforms jointly to improve radio access capability and unlock the support of on-demand edge cloud services in three-dimensional (3D) space, by incorporating mobile edge computing (MEC) functionalities on aerial platforms and low-orbit satellites. This will extend the MEC support to devices and network elements in the sky and forge a space-borne MEC, enabling intelligent, personalized, and distributed on-demand services. End users will experience the impression of being surrounded by a distributed computer, fulfilling their requests with apparently zero latency. In this paper, we consider an architecture that provides communication, computation, and caching (C3) services on demand, anytime, and everywhere in 3D space, integrating conventional ground (terrestrial) base stations and flying (non-terrestrial) nodes. Given the complexity of the overall network, the C3 resources and management of aerial devices need to be jointly orchestrated via artificial intelligence-based algorithms, exploiting virtualized network functions dynamically deployed in a distributed manner across terrestrial and non-terrestrial nodes.

A Repository Utilization System to optimize maintenance of IIoT-based main point Utilities (IIoT 기반한 핵심유틸리티의 유지보수 최적화를 위한 공동 활용 시스템)

  • Lee, Byung-Ok;Lee, Kun-Woo;Kim, Young-Gon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.89-94
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    • 2021
  • Recently, manufacturing companies are introducing many intelligent production processes that apply IIoT/ICT to improve competitiveness, and a system that maintains availability, improves productivity, and optimizes management costs is needed as a preventive measure using environmental data generated from air ejectors. Therefore, in this study, a dedicated control board was developed and LoRa communication module was applied to remotely control it to collect and manage information about compressors from cloud servers and to ensure that all operators and administrators utilize common data in real time. This dramatically reduced M/S steps, increased system operational availability, and reduced local server operational burden. It dramatically reduced maintenance latency by sharing system failure conditions and dramatically improved cost and space problems by providing real-time status detection through wired and mobile utilization by maintenance personnel.

Plans to Improve Smart Village and Its Challenges (스마트 빌리지, 그 계획과 도전)

  • Eom, Seong-Jun;Kim, Sang-Bum;Cho, Suk-Yeong;An, Phil-Gyun
    • Journal of Agricultural Extension & Community Development
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    • v.27 no.4
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    • pp.173-184
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    • 2020
  • Is the Fourth Industrial Revolution a revolution for cities only? Through the Fourth Industrial Revolution, Korea has entered quickly in the influence area of intelligent information technology such as IoT, AI, Big data, Cloud, ICT, Digital twin. However, as the information gap between the rural zone and the urban zone worsens, a policy was needed to reduce such a gap. Therefore, this research analyzed EU's smart village project, and investigated the problem and improvement of the actual smart village through the interview and field study with the person in charge of the actual smart village project in Korea. Based on the analytic result, 5 plans were deduced to improve Korea's smart village project. First, make the realistic adjustment of project period to assure the sustainability of smart village; second, make the new establishment of the department in charge of smart village project; third, construct the system of integrating and cooperating the policy that can embrace all the rural zone and the urban zone; the fourth, expand the application area of customized ICT technology according to the new rural policy environment; and finally introduce the residents' capacity development project through the rural guidance project.

DeepBlock: Web-based Deep Learning Education Platform (딥블록: 웹 기반 딥러닝 교육용 플랫폼)

  • Cho, Jinsung;Kim, Geunmo;Go, Hyunmin;Kim, Sungmin;Kim, Jisub;Kim, Bongjae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.3
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    • pp.43-50
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    • 2021
  • Recently, researches and projects of companies based on artificial intelligence have been actively carried out. Various services and systems are being grafted with artificial intelligence technology. They become more intelligent. Accordingly, interest in deep learning, one of the techniques of artificial intelligence, and people who want to learn it have increased. In order to learn deep learning, deep learning theory with a lot of knowledge such as computer programming and mathematics is required. That is a high barrier to entry to beginners. Therefore, in this study, we designed and implemented a web-based deep learning platform called DeepBlock, which enables beginners to implement basic models of deep learning such as DNN and CNN without considering programming and mathematics. The proposed DeepBlock can be used for the education of students or beginners interested in deep learning.

An Enhancement of The Enterprise Security for Access Control based on Zero Trust (제로 트러스트 기반 접근제어를 위한 기업 보안 강화 연구)

  • Lee, Seon-A;Kim, Beomseok;Lee, Hyein;Park, Wonhyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.2
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    • pp.265-270
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    • 2022
  • With the advent of the Fourth Industrial Revolution, the paradigm of finance is also changing. As remote work becomes more active due to cloud computing and coronavirus, the work environment changes and attack techniques are becoming intelligent and advanced, companies should accept new security models to further strengthen their current security systems. Zero trust security increases security by monitoring all networks and allowing strict authentication and minimal access rights for access requesters with the core concept of doubting and not trusting everything. In addition, the use of NAC and EDR for identification subjects and data to strengthen access control of the zero trust-based security system, and strict identity authentication through MFA will be explained. Therefore, this paper introduces a zero-trust security solution that strengthens existing security systems and presents the direction and validity to be introduced in the financial sector.

A Study on the Development Issues of Digital Health Care Medical Information (디지털 헬스케어 의료정보의 발전과제에 관한 연구)

  • Moon, Yong
    • Industry Promotion Research
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    • v.7 no.3
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    • pp.17-26
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    • 2022
  • As the well-being mindset to keep our minds and bodies free and healthy more than anything else in the society we live in is spreading, the meaning of health care has become a key part of the 4th industrial revolution such as big data, IoT, AI, and block chain. The advancement of the advanced medical information service industry is being promoted by utilizing convergence technology. In digital healthcare, the development of intelligent information technology such as artificial intelligence, big data, and cloud is being promoted as a digital transformation of the traditional medical and healthcare industry. In addition, due to rapid development in the convergence of science and technology environment, various issues such as health, medical care, welfare, etc., have been gradually expanded due to social change. Therefore, in this study, first, the general meaning and current status of digital health care medical information is examined, and then, developmental tasks to activate digital health care medical information are analyzed and reviewed. The purpose of this article is to improve usability to fully pursue our human freedom.

A Study on Hangul Handwriting Generation and Classification Mode for Intelligent OCR System (지능형 OCR 시스템을 위한 한글 필기체 생성 및 분류 모델에 관한 연구)

  • Jin-Seong Baek;Ji-Yun Seo;Sang-Joong Jung;Do-Un Jeong
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.222-227
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    • 2022
  • In this paper, we implemented a Korean text generation and classification model based on a deep learning algorithm that can be applied to various industries. It consists of two implemented GAN-based Korean handwriting generation models and CNN-based Korean handwriting classification models. The GAN model consists of a generator model for generating fake Korean handwriting data and a discriminator model for discriminating fake handwritten data. In the case of the CNN model, the model was trained using the 'PHD08' dataset, and the learning result was 92.45. It was confirmed that Korean handwriting was classified with % accuracy. As a result of evaluating the performance of the classification model by integrating the Korean cursive data generated through the implemented GAN model and the training dataset of the existing CNN model, it was confirmed that the classification performance was 96.86%, which was superior to the existing classification performance.