• Title/Summary/Keyword: 스마트팩토리

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Smoothing DRR: A fair scheduler and a regulator at the same time (Smoothing DRR: 스케줄링과 레귤레이션을 동시에 수행하는 서버)

  • Joung, Jinoo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.63-68
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    • 2019
  • Emerging applications such as Smart factory, in-car network, wide area power network require strict bounds on the end-to-end network delays. Flow-based scheduler in traditional Integrated Services (IntServ) architecture could be possible solution, yet its complexity prohibits practical implementation. Sub-optimal class-based scheduler cannot provide guaranteed delay since the burst increases rapidly as nodes are passed by. Therefore a leaky-bucket type regulator placed next to the scheduler is being considered widely. This paper proposes a simple server that achieves both fair scheduling and traffic regulation at the same time. The performance of the proposed server is investigated, and it is shown that a few msec delay bound can be achieved even in large scale networks.

Big Data-based Medical Clinical Results Analysis (빅데이터 기반 의료 임상 결과 분석)

  • Hwang, Seung-Yeon;Park, Ji-Hun;Youn, Ha-Young;Kwak, Kwang-Jin;Park, Jeong-Min;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.187-195
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    • 2019
  • Recently, it has become possible to collect, store, process, and analyze data generated in various fields by the development of the technology related to the big data. These big data technologies are used for clinical results analysis and the optimization of clinical trial design will reduce the costs associated with health care. Therefore, in this paper, we are going to analyze clinical results and present guidelines that can reduce the period and cost of clinical trials. First, we use Sqoop to collect clinical results data from relational databases and store in HDFS, and use Hive, a processing tool based on Hadoop, to process data. Finally we use R, a big data analysis tool that is widely used in various fields such as public sector or business, to analyze associations.

A Study on Life Change and Leisure Satisfaction by Reduction of Working Hours of Office Workers (직장인의 근로시간 단축에 따른 생활변화와 여가만족도에 관한 연구)

  • Choi, Tae-Wol;Lim, Sang-Ho
    • Industry Promotion Research
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    • v.6 no.2
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    • pp.47-53
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    • 2021
  • This study is a study on the change of life and leisure satisfaction caused by the reduction of working hours of office workers, summarizing the results of the analysis as follows: First, the change in the working hours of office workers was found to be men (42.4 percent), but women (54.7 percent) had a high increase in personal satisfaction, monthly income of 2 to 3 million won 96.1 percent, and personal satisfaction increased in small and medium-sized cities and towns. Second, leisure satisfaction due to shorter working hours was somewhat high in monthly income of 3 million won to 4 million won (43.6%) and more than 6 million won (39.1%), but there was no change in leisure satisfaction by gender, age, academic background, number of family members, marital status, worker status and region. The revitalization of leisure is a very important task in personal life, but it is meaningful in that it provided implications for socializing leisure as leisure satisfaction is positively spreading in life changes.

BLE-based Indoor Positioning System design using Neural Network (신경망을 이용한 BLE 기반 실내 측위 시스템 설계)

  • Shin, Kwang-Seong;Lee, Heekwon;Youm, Sungkwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.1
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    • pp.75-80
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    • 2021
  • Positioning technology is performing important functions in augmented reality, smart factory, and autonomous driving. Among the positioning techniques, the positioning method using beacons has been considered a challenging task due to the deviation of the RSSI value. In this study, the position of a moving object is predicted by training a neural network that takes the RSSI value of the receiver as an input and the distance as the target value. To do this, the measured distance versus RSSI was collected. A neural network was introduced to create synthetic data from the collected actual data. Based on this neural network, the RSSI value versus distance was predicted. The real value of RSSI was obtained as a neural network for generating synthetic data, and based on this value, the coordinates of the object were estimated by learning a neural network that tracks the location of a terminal in a virtual environment.

A Study on Futsal Video Analysis System Using Object Tracking (객체 추적을 이용한 풋살 영상 분석 시스템에 관한 연구)

  • Jung, Halim;Kwon, Hangil;Lee, Gilhyeong;Jung, Soogyung;Ko, Dongbeom;Jeon, GwangIl;Park, Jeongmin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.3
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    • pp.201-210
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    • 2021
  • This paper introduces the futsal video analysis system consisting of an analysis program using object tracking technology and a web server that visualizes and provides analyzed data. In this paper, small and medium-sized organizations and amateur players are unable to provide game analysis services, so they propose a system that can solve this problem through this paper. Existing analytical systems use special devices or high-cost cameras, making them difficult for users to use. Thus, in this paper, a system is designed and developed to analyze the competitors' competitions and visualize the data using flat images only. Track an object and calculate the accumulated values to obtain the distance per pixel of the object and extract speed-related data and distance-based data based on it. Converts extracted data to graphs and images through a visualization library, making it convenient to use through web pages. Through this analysis system, we improve the problems of the existing analysis system and make data-based scientific and efficient analysis available.

A Study on Development of Indoor Object Tracking System Using N-to-N Broadcasting System (N-to-N 브로드캐스팅 시스템을 활용한 실내 객체 위치추적 시스템 개발에 관한 연구)

  • Song, In seo;Choi, Min seok;Han, Hyun jeong;Jeong, Hyeon gi;Park, Tae hyeon;Joeng, Sang won;Kwon, Jang woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.192-207
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    • 2020
  • In industrial fields like big factories, efficient management of resources is critical in terms of time and expense. So, inefficient management of resources leads to additional costs. Nevertheless, in many cases, there is no proper system to manage resources. This study proposes a system to manage and track large-scale resources efficiently. We attached Bluetooth 5.0-based beacons to our target resources to track them in real time, and by saving their transportation data we can understand flows of resources. Also, we applied a diagonal survey method to estimate the location of beacons so we are able to build an efficient and accurate system. As a result, We achieve 47% more accurate results than traditional trilateration method.

A Study on Ball Tracking Algorithm to Analyze Amateur Futsal Data (아마추어 풋살 데이터 분석을 위한 공 추적 알고리즘 연구)

  • Jung, Soogyung;Kwon, Hangil;Lee, Gilhyeong;Jung, Halim;Ko, Dongbeom;Jeon, Gwangil;Park, Jeongmin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.4
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    • pp.189-198
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    • 2021
  • This paper introduces the ball tracking system using image processing. The recent growth of the amateur futsal market has also raised requests for an analysis of amateur players' performance. Sports game analysis services for feedback and growth to athletes or teams are provided in various ways in various sports fields. However, the cost and spatial constraints of sports analysis services make it difficult for providing analysis services to amateur athletes. In this paper, we study and develop a ball tracking algorithm for analyzing futsal game based on the match filming service previously provided in the amateur futsal field. This allows the analysis of the match based on existing services.

A Predictive System for Equipment Fault Diagnosis based on Machine Learning in Smart Factory (스마트 팩토리에서 머신 러닝 기반 설비 장애진단 예측 시스템)

  • Chow, Jaehyung;Lee, Jaeoh
    • KNOM Review
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    • v.24 no.1
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    • pp.13-19
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    • 2021
  • In recent, there is research to maximize production by preventing failures/accidents in advance through fault diagnosis/prediction and factory automation in the industrial field. Cloud technology for accumulating a large amount of data, big data technology for data processing, and Artificial Intelligence(AI) technology for easy data analysis are promising candidate technologies for accomplishing this. Also, recently, due to the development of fault diagnosis/prediction, the equipment maintenance method is also developing from Time Based Maintenance(TBM), being a method of regularly maintaining equipment, to the TBM of combining Condition Based Maintenance(CBM), being a method of maintenance according to the condition of the equipment. For CBM-based maintenance, it is necessary to define and analyze the condition of the facility. Therefore, we propose a machine learning-based system and data model for diagnosing the fault in this paper. And based on this, we will present a case of predicting the fault occurrence in advance.

Abnormal System Operation Detection by Comparing QR Code-Encoded Power Consumption Patterns in Software Execution Control Flow (QR 코드로 인코딩된 소프트웨어 실행 제어 흐름 전력 소비 패턴 기반 시스템 이상 동작 감지)

  • Kang, Myeong-jin;Park, Daejin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.11
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    • pp.1581-1587
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    • 2021
  • As embedded system are used widely and variously, multi-edge system, which multiple edges gather and perform complex operations together, is actively operating. In a multi-edge system, it often occurs that an abnormal operation at one edge is transferred to another edge or the entire system goes down. It is necessary to determine and control edge anomalies in order to prevent system down, but this can be a heavy burden on the resource-limited edge. As a solution to this, we use power consumption data to check the state of the edge device and transmit it based on a QRcode to check and control errors at the server. The architecture proposed in this paper is implemented using 'chip-whisperer' to measure the power consumption of the edge and 'Raspberry Pi 3' to implement the server. As a result, the proposed architecture server showed successful data transmission and error determination without additional load appearing at the edge.

Digital Twin Model Design And Implementation Using UBS Process Data (UBS공정 데이터를 활용한 디지털트윈 모델 설계 및 구현)

  • Park, Seon-Hui;Bae, Jong-Hwan;Ko, Ho-Jeong
    • Journal of Internet of Things and Convergence
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    • v.8 no.3
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    • pp.63-68
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    • 2022
  • Due to COVID-19, many paradigm shifts in existing manufacturing facilities and the expansion of non-face-to-face services are accelerating worldwide. A representative technology is digital twin technology. Such digital twin technology, which existed only conceptually in the past, has recently become feasible with the construction of a 5G-based network. Accordingly, this paper designed and implemented a part of the USB process to enable digital twins based on OPC UA communication, which is a standard interlocking structure, between real object objects and virtual reality-based USB process in accordance with this paradigm change. By reflecting the physical characteristics of real objects together, it is possible to simulate real-time synchronization of these with real objects. In the future, this can be applied to various industrial fields, and it is expected that it will be possible to reduce costs for decision-making and prevent dangerous accidents.