• 제목/요약/키워드: IoT Framework

검색결과 184건 처리시간 0.18초

IoT 환경에서 모바일 엣지 컴퓨팅을 통한 디바이스간 타스크 관리 프레임워크 (Green Device to Device Task Management Framework by Mobile Edge Computing in IoT Environment)

  • 고광만;;;김순곤
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2018년도 춘계학술발표대회
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    • pp.85-87
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    • 2018
  • Motivating by two promising technique of 5G, namely D2D and Edge computing, and the above mentioned problem of the current joint studies, We believe that more study is needed on the benefits of joining these two techniques in a single framework by more precisely taking into account the energy needed to computation, sending data, receiving data and as a result achieving more realistic energy efficiency in 5G cellular networks.

Design of Remote Management System for Smart Factory

  • Hwang, Heejoung
    • International Journal of Internet, Broadcasting and Communication
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    • 제12권4호
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    • pp.109-121
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    • 2020
  • As a decrease in labor became a serious issue in the manufacturing industry, smart factory technology, which combines IT and the manufacturing business, began to attract attention as a solution. In this study, we have designed and implemented a real-time remote management system for smart factories, which is connected to an IoT sensor and gateway, for plastic manufacturing plants. By implementing the REST API in which an IoT sensor and smart gateway can communicate, the system enabled the data measured from the IoT sensor and equipment status data to the real-time monitoring system through the gateway. Also, a web-based management dashboard enabled remote monitoring and control of the equipment and raw material processing status. A comparative analysis experiment was conducted on the suggested system for the difference in processing speed based on equipment and measurement data number change. The experiment confirmed that saving equipment measurement data using cache mechanisim offered faster processing speed. Through the result our works can provide the basic framework to factory which need implement remote management system.

IoT 환경에서의 개인정보보호 프레임워크 (A Framework for Personal Information Protection in Internet of Things Study on Contents Technology)

  • 이야리;김정숙
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2014년도 추계 종합학술대회 논문집
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    • pp.277-278
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    • 2014
  • 사물인터넷(IoT)은 '개방형 환경에서 인터넷을 기반으로 사람, 사물, 데이터 및 프로세스를 서로 연결하여 정보를 교류하고 상호 소통하는 지능형 인프라'로서 홈 가전, 교통 물류, 건설, 에너지, 헬스케어, 사회안전 등 여러 분야에서 새로운 상품을 개발하고 공급해 창조경제의 핵심동력 가운데 하나가 될 것으로 기대된다. 그러나 네트워크, 서비스, 플랫폼/디바이스 등 기반 환경에서 다양한 개인정보 침해에 대한 위협이 존재하며 개인정보 보호와 기술 활용이라는 이슈에 관한 논의는 아직 초기 단계에 있다. 따라서 본 연구에서는 IoT 환경에서 정보주체의 민감한 개인정보에 대한 안전한 보호 정책 적용과 효율적 정보기술 활용 및 제공이 가능한 개인정보보호 프레임워크를 제안하고자 한다.

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IoT를 채용한 스마트 창고관리 시스템 설계 제안 (A Proposition for Smart Warehouse Management System (SWMS) through IoT)

  • 김준영;전병우;홍대근;서석환
    • 시스템엔지니어링학술지
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    • 제11권2호
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    • pp.85-93
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    • 2015
  • Warehouse Management System (WMS) is a key control for Material Handling System (MHS) and Inventory Control System (ICS). How to design and implement for WMS is crucial factor for achieving the key performance index for Manufacturing Industry. In particular, iron and steel making industry, where the volume and weight is large and hence FIFO (First Input First Out) is not working, how to design WMS is a key factor. In this paper, we systematically define the problem of WMS via developing StR (Stakeholders' Requirements) or ORD (Operational Requirement Documents), SyR (System Requirement), and SA (System Architecture) based on the emerging technologies. In particular, IoT (Internet of Things), CPS (Cyber Physical System) concepts and enabling technologies haves been incorporated in developing Smart WMS. The deliverables of the research can provide a conceptual framework for developing the next generation industrial WMS.

빅데이터, 비즈니스 애널리틱스, IoT: 경영의 새로운 도전과 기회 (Big Data, Business Analytics, and IoT: The Opportunities and Challenges for Business)

  • 장영재
    • 한국정보시스템학회지:정보시스템연구
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    • 제24권4호
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    • pp.139-152
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    • 2015
  • With the advancement of the Internet/IT technologies and the increased computation power, massive data can be collected, stored, and processed these days. The availability of large databases has brought forth a new era in which companies are hard pressed to find innovative ways to utilize immense amounts of data at their disposal. Indeed, data has opened a new age of business operations and management. There are already many cases of innovative businesses reaping success thanks to scientific decisions based on data analysis and mathematical algorithms. Big Data is a new paradigm in itself. In this article, Big Data is viewed as a new perspective rather than a new technology. This value centric definition of Big Data provides a new insight and opportunities. Moreover, the Business Analytics, which is the framework of creating tangible results in management, is introduced. Then the Internet of Things (IoT), another innovative concept of data collection and networking, is presented and how this new concept can be interpreted with Big Data in terms of the value centric perspective. The challenges and opportunities with these new concepts are also discussed.

A Robust and Adaptive Trust Management System for Guaranteeing the Availability in the Internet of Things Environments

  • Wu, Xu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권5호
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    • pp.2396-2413
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    • 2018
  • Trust management is one of the most challenging issues for the highly heterogeneous Internet of Things (IoT). In the context of the IoT, it is difficult to evaluate the node's trustworthiness in the same trust model when a node provides different services. Guaranteeing the availability of the trust management service is another significant challenge because of the dynamic nature of IoT environments. With these issues in mind, this paper propose a robust and adaptive trust management system for the IoT that is able to measure the trustworthiness of nodes based on feedbacks collected from participants in a specific context and ensure the availability of trust management services. The main contributions of our system are: 1) Proposing a partly decentralized trust management framework, which improves the resiliency of the trust mechanism; 2) Proposing an adaptive trust evaluation scheme and a three-dimensional context representation makes trust evaluation more accurate and specific; 3) Enhancing the adaptive trust evaluation scheme by incorporating a bad behavior factor in trust estimation, which efficiently distinguishes misleading feedbacks from On-Off attacks. Simulation results show the good performance of the proposed system and especially show effectiveness against On-Off attacks compared to other trust mechanisms.

사물인터넷과 미디어기업의 혁신 (Internet of Things and Innovative Media Firms)

  • 문상현
    • 한국융합학회논문지
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    • 제10권6호
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    • pp.157-164
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    • 2019
  • 본 논문은 새로운 디지털 기술로서 사물인터넷이 미디어기업 혁신에 어떻게 기여할 수 있으며 이를 위해 필요한 정책은 무엇인지 검토한다. 사물인터넷은 미디어기업의 상품/서비스, 생산공정과 비즈니스모델 혁신을 도움으로써 새로운 수익창출과 경쟁력 제고를 가능케 할 수 있다. 상호작용성과 몰입감을 높여 콘텐츠 완성도는 물론 소비경험을 제고시킴으로써 콘텐츠 경쟁력을 강화하고, 데이터가 핵심경쟁력으로 부상하는 시장 환경에서 타깃광고 등을 통해 수익모델을 개선하는데 기여할 수 있다. 미디어기업과 소비자 모두 사물인터넷을 통한 혁신의 혜택을 누리기 위해서는 혁신친화적 생태계가 구축되어야 한다. 가장 중요한 것은 사물인터넷에 대한 미디어기업의 인식전환과 적극적 투자이다. 정부 역시 사물인터넷의 혁신적 장점을 최대한 활용할 수 있는 제도적 인프라를 조성해야 한다. 가장 시급한 정책이슈는 개인정보수집과 데이터 활용에 관한 경직된 규제를 개선하고 사이버 보안을 강화하는 것이다.

산업용 사물인터넷에서 포그 컴퓨팅을 위한 인지 IoT 플랫폼 조사연구 (Research study on cognitive IoT platform for fog computing in industrial Internet of Things)

  • 홍성혁
    • 사물인터넷융복합논문지
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    • 제10권1호
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    • pp.69-75
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    • 2024
  • 본 연구에서는 산업용 사물인터넷(IIoT)의 맥락에서 포그 컴퓨팅(Fog Computing, FC)를 위해 특별히 고안된 혁신적인 인지 사물인터넷(Cognitive IoT) 프레임워크를 제안한다. 본 논문에서는 인지 IoT 플랫폼의 복잡한 설계 및 기능적 아키텍처에 초점을 맞추고, 이 아키텍처는 서비스 제공, 인지 의사결정, 분산 모니터링 및 제어와 같은 핵심 구성 요소를 원활하게 통합하는 것을 제안한다. 이 플랫폼의 중요한 측면은 기계 학습(ML) 및 인공 지능(AI)을 통합하는 것으로, 다양한 산업 애플리케이션에서 운영의 유연성과 상호 운용성을 향상시켜 실시간 기계 상태 모니터링에 중점을 둔 예측 유지보수-서비스(Predictive Maintenance-as-a-Service, PdM-as-a-Service) 모델을 통해 제시된다. 이 모델은 실시간 데이터 분석을 활용하여 유지보수 및 관리 작업을 수행함으로써 전통적인 유지보수 접근법을 뛰어넘고, 실증적 결과는 포그 컴퓨팅 환경 내에서 플랫폼의 효과성을 입증하며, 산업용 IoT 애플리케이션 분야에서의 변혁적 잠재력을 보여 IIoT 플랫폼 개발에 기여 하는 연구이다.

Weighted Adaptive Opportunistic Scheduling Framework for Smartphone Sensor Data Collection in IoT

  • M, Thejaswini;Choi, Bong Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권12호
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    • pp.5805-5825
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    • 2019
  • Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.

A Novel Framework Based on CNN-LSTM Neural Network for Prediction of Missing Values in Electricity Consumption Time-Series Datasets

  • Hussain, Syed Nazir;Aziz, Azlan Abd;Hossen, Md. Jakir;Aziz, Nor Azlina Ab;Murthy, G. Ramana;Mustakim, Fajaruddin Bin
    • Journal of Information Processing Systems
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    • 제18권1호
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    • pp.115-129
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    • 2022
  • Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home appliances electricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS) could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, or connection errors. In this paper, a novel framework has been proposed to predict large gaps of missing values from the SHS home appliances electricity consumption time-series datasets. The framework follows a series of steps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutional neural network-long short term memory (CNN-LSTM) neural network used to forecast large missing values gaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM with its single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performance superiority of the CNN-LSTM model over the single CNN and LSTM neural networks.