• Title/Summary/Keyword: 산업용 사물인터넷

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Energy-Efficient MEC Offloading Decision Algorithm in Industrial IoT Environments (산업용 IoT 환경에서 MEC 기반의 에너지 효율적인 오프로딩 결정 알고리즘)

  • Koo, Seolwon;Lim, YuJin
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.11
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    • pp.291-296
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    • 2021
  • The development of the Internet of Things(IoT) requires large computational resources for tasks from numerous devices. Mobile Edge Computing(MEC) has attracted a lot of attention in the IoT environment because it provides computational resources geographically close to the devices. Task offloading to MEC servers is efficient for devices with limited battery life and computational capability. In this paper, we assumed an industrial IoT environment requiring high reliability. The complexity of optimization problem in industrial IoT environment with many devices and multiple MEC servers is very high. To solve this problem, the problem is divided into two. After selecting the MEC server considering the queue status of the MEC server, we propose an offloading decision algorithm that optimizes reliability and energy consumption using genetic algorithm. Through experiments, we analyze the performance of the proposed algorithm in terms of energy consumption and reliability.

가속도 센서와 홀 센서를 활용한 블루투스 비콘 디바이스에 관한 연구

  • Kwon, Dong-Hyun;Lim, Ji-yong;Oh, Am-suk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.549-550
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    • 2016
  • 사물인터넷 기술은 이미 지능형 정보처리를 필요로 하는 여러 융합 서비스의 주요 기술로 이용되고 있으며 그 중요성은 나날이 부각되고 있다. 특히 사물인터넷의 핵심 기술 중 하나인 저전력 블루투스 기반 무선통신 장치인 비콘이 주목받고 있다. 비콘은 애플의 아이비콘을 시작으로 다양한 산업분야에서 활용되고 있으며, 최근에는 비콘의 기본 기능을 넘어서 특정 환경 및 조건에서 사용하고자 하는 요구가 늘어나고 있다. 이를 위해 본 논문에서는 가속도 센서와 홀 센서를 활용한 비콘 디바이스를 제안한다. 제안한 비콘 디바이스는 센서를 통한 이동 감지를 통해 특정 상황에서의 제어가 가능할 것으로 기대한다.

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Comparison & Analysis of Drones in Major Countries based on Self-Driving in IoT Environment (사물인터넷 환경에서 자율주행 기반의 주요국 드론 특성 비교/분석)

  • Lee, Dong-Woo;Cho, Kwangmoon;Lee, Seong-Hoon
    • Journal of Internet of Things and Convergence
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    • v.6 no.2
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    • pp.31-36
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    • 2020
  • The remarkable change in the automobile industry, which is a traditional industrial field, is now evolving into a form of moving toward autonomous functions rather than humans due to various convenience functions and automatic driving or autonomous driving technologies if the person was central when driving the car. This situation is expanding to various industries such as the aviation industry and the drone market, as well as the robot market. The drone market in the aviation industry is being used in various fields due to the unmanned nature of drone operation. Among them, military drones are secret and due to the specificity of technology, details are not disclosed, but as a collection of advanced technologies, they have played a key role in drone development. In this study, the current status of China and the European Union, including the United States, which are major competitors in the drone field, was investigated, and the technologies of major countries were compared and analyzed through the characteristics and operational specifications of the drones currently in operation.

Artificial Intelligence Service Robot Market Trend (인공지능 서비스 로봇 시장의 동향)

  • Hwang, Eui-Chul
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.01a
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    • pp.111-112
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    • 2021
  • 로봇은 인공지능(AI) 기술을 비롯해 빅데이터, 센서기술, 클라우드 등 다양한 신 분야의 축적된 기술력과 노하우를 필요로 한다. 코로나 19 여파로 비대면 서비스에 대한 수요가 증가하고 정보통신기술이 발전되고 있는 가운데 청소용, 잔디 깎기, 가사용, 동반자, 엔터테인먼트 및 레저용, 노약자 및 장애인 지원 로봇 등 우리생활 주변에서도 서비스 로봇이 빠르게 도입되고 있다. 본 논문에서는 최근 3년간(2018.1~2020.12) 중앙지, 경제지 등 54개 언론사 기사를 빅카인즈와 데이터랩을 이용하여 서비스 로봇&인공지능을 키워드로 관계도 분석, 키워드 트렌드, 연관어 분석을 하였다. 연관어 키워드 빈도수로는 인공지능(534), LG전자(157), 드론(112), 자율주행(101), 빅데이터(81), 로보티즈(61), 사물인터넷(34) 순으로 서비스 로봇의 성장은 인공지능을 비롯한 4차 산업혁명 관련 기술과 연관성이 매우 컸다. 2016년~2020년 기간에 산업용 로봇은 1.89배 증가했으며, 서비스 로봇은 5.21배 증가하여 서비스 로봇의 수요가 다양한 분야에서 확산됨을 확인할 수 있었다.

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Machine Learning Based APT Detection Techniques for Industrial Internet of Things (산업용 사물인터넷을 위한 머신러닝 기반 APT 탐지 기법)

  • Joo, Soyoung;Kim, So-Yeon;Kim, So-Hui;Lee, Il-Gu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.449-451
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    • 2021
  • Cyber-attacks targeting endpoints have developed sophisticatedly into targeted and intelligent attacks, Advanced Persistent Threat (APT) targeting the Industrial Internet of Things (IIoT) has increased accordingly. Machine learning-based Endpoint Detection and Response (EDR) solutions combine and complement rule-based conventional security tools to effectively defend against APT attacks are gaining attention. However, universal EDR solutions have a high false positive rate, and needs high-level analysts to monitor and analyze a tremendous amount of alerts. Therefore, the process of optimizing machine learning-based EDR solutions that consider the characteristics and vulnerabilities of IIoT environment is essential. In this study, we analyze the flow and impact of IIoT targeted APT cases and compare the method of machine learning-based APT detection EDR solutions.

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Implementation of IoT using Raspberry Pi and Bluetooth Serial Communication (라즈베리파이와 블루투스 시리얼 통신을 활용한 IoT 구현)

  • Choi, Jun-hyeong;Choi, Byeong-yoon;Lee, Sung-jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.202-204
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    • 2021
  • The Internet of Things (IoT) is a term first used by Kevin Ashton, director of MIT's Auto ID Center, in 1999, and refers to the connection of things to the Internet. Bluetooth, one of the wireless networks, is a technology developed as an industry standard for personal short-range wireless communication first developed by Ericsson in 1994. Since the Raspberry Pi has Bluetooth built-in, a wireless network is possible. This paper implements a module for the Internet of Things by implementing serial communication in the Bluetooth built-in Raspberry Pi 3 B+. There was a problem that Bluetooth communication was impossible between raspberries, so the discovery function was activated and serial communication was added to successfully link the communication.

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PROFINET-based Data Collection IIoT Device Development Method (PROFINET 기반 데이터 수집을 위한 IIoT 장치 개발 방안)

  • Kim, Seong-Chang;Kim, Jin-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.92-93
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    • 2022
  • As the importance of smart factories is emphasized, the use of industrial Ethernet-based devices is expected to increase to build smart factories. PROFINET is an industrial Ethernet protocol developed by SIEMENS, and a number of smart factories are currently being built as PROFINET-based products. Accordingly, in order to develop and utilize various industrial IoT-based services, an IIoT device capable of collecting various sensor data and information from PROFINET-based manufacturing equipment and transmitting data to an edge computer is required.

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An Insight Study on Keyword of IoT Utilizing Big Data Analysis (빅데이터 분석을 활용한 사물인터넷 키워드에 관한 조망)

  • Nam, Soo-Tai;Kim, Do-Goan;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.146-147
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    • 2017
  • Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

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Implementation of a Sensor Network in a Welding Workplace Based on IoT for Smart Shipyards (스마트 조선소를 위한 사물인터넷 기반 용접 작업장 센서네트워크 구축)

  • Kim, Hyun Sik;Lee, Gi Seung;Kang, Seog Geun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.433-439
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    • 2021
  • In this paper, we propose a method to implement an IoT-based sensor network for each workplace of a shipyard. Here, at the most common welding workplace in shipyards, the shipbuilding blocks are used as a communication medium to transmit information such as the worker's location, welding progress, and working hour to a server using LoRa and powerline communication. To achieve the data communication, inductive couplers and hybrid modems have been manufactured and installed on wire feeders and pin jigs to establish a sensor network. As a result of field test, the proposed system shows a success rate of data transmission and a rate of successful recognition of worker's location of about 98% or more. In addition, the process management system platform can record and display the work process data generated at the field in real time. The proposed system can be a starting point for enhancing the competitiveness of Korean shipbuilding industry through the establishment of a smart shipyard.

A Design on The Zone Master Platform based on IIoT communication for Smart Factory Digital Twin (스마트 팩토리 디지털 트윈(Digital Twin)을 위한 IIoT 통신 기반 ZMP(Zone Master Platform) 설계)

  • Park, Seon-Hui;Bae, Jong-Hwan
    • Journal of Internet of Things and Convergence
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    • v.6 no.4
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    • pp.81-87
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    • 2020
  • This paper creates a standard node for acquiring sensor data from various industrial sensors (IoT/non-IoT) for the establishment of Smart Factory Digital Twin, and provides inter-compatible data by linking zones by group/process to secure data stability and to ensure the digital twin (Digital Twin) of Smart Factory. The process of the Zone Master platform contains interface specifications to define sensor objects and how sensor interactions between independent systems are performed and carries out individual policies for unique data exchange rules. The interface for execution control of the Zone Master Platform processor provides system management, declaration management for public-subscribe, object management for registering and communicating status information of sensor objects, ownership management for property ownership sharing, time management for data synchronization, and data distribution management for Route information on data exchange.