• Title/Summary/Keyword: Internet-of-things device

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Recommendation System using Baysian Network in IoT Environment (IoT 환경에서의 베이지안 네트워크를 이용한 추천시스템)

  • Jeong, Soo-Yeon;Kim, Young-Kuk
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.125-127
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    • 2016
  • 본 논문에서는 IoT(Internet of Things) Device와 스마트폰을 이용하여 사용자의 상황을 인지하고 상황에 적합한 상품을 추천하는 추천시스템을 제안한다. 기존 추천시스템과 다르게 제안하는 IoT 환경에서의 추천시스템은 IoT Device와 스마트폰에서 얻을 수 있는 날씨, 위치, 사용자 정보 등을 파악하여 추천하는 것으로 다양하고 많은 데이터를 제공하므로 정확도를 높일 수 있다. 베이지안 네트워크(BN, Bayesian Network)는 불확실성을 효율적으로 관리하고 정확도와 실시간성을 높일 수 있는 방법으로, 상품의 특징에 따라 종류를 분류하여 추론하고 선호도가 높은 상품의 종류를 추천하는 시스템을 제안한다.

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Personalized Information Retrieval Method considering Participating Device in Internet of Things (사물인터넷에서 참여 기기를 고려한 개인화 정보 검색 기법)

  • Kwon, Joon Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.16 no.1
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    • pp.21-31
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    • 2020
  • Internet of Things is growing rapidly. As it evolves, the amount of data is increasing significantly. It requires a new personalized information retrieval method. Internet of Things is defined as uniquely identifiable interoperable connected object. The first definition of Internet of Things was from Things oriented perspective. However, previous studies about personalized information retrieval method do not consider Things. To meet user's individual needs, previous studies concentrate on only human, not Things. In this paper, we propose a personalized information retrieval method considering participating device in Internet of Things. It provides personalized information using data type preference for each device. Moreover, it provides personalized results by integrating data type preference for set of devices. This paper describes a new personalized retrieval method and algorithm. It consists of five steps. Then, it presents four scenarios using proposed method. The scenarios show our work is more effective and efficient than existing one.

Study on the MQTT protocol design for the application of the real-time HVAC System

  • Jung, Hun
    • International Journal of Internet, Broadcasting and Communication
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    • v.8 no.1
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    • pp.19-26
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    • 2016
  • In this paper, the existing domestic HVAC systems, devices TCP / IP does not support the most, thereby, not performed remote management, it is necessary to regularly field service, inefficiency and cost bring a burden. This is through a comparison of the IoT-based primary, real-time protocol of what has become a hot topic recently, to be able to control and real-time monitoring through the CCU device in the HVAC system. Compare for this Internet of Things device for real-time monitoring and control of the XMPP, CoAP, MQTT main real-time protocol is used on. Finally, flexibility, light weight, based on MQTT a two-way messaging protocols with reliable message delivery, implements the protocol on the real-time HVAC system in the cloud platform.

Communication Failure Resilient Improvement of Distributed Neural Network Partitioning and Inference Accuracy (통신 실패에 강인한 분산 뉴럴 네트워크 분할 및 추론 정확도 개선 기법)

  • Jeong, Jonghun;Yang, Hoeseok
    • IEMEK Journal of Embedded Systems and Applications
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    • v.16 no.1
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    • pp.9-15
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    • 2021
  • Recently, it is increasingly necessary to run high-end neural network applications with huge computation overhead on top of resource-constrained embedded systems, such as wearable devices. While the huge computational overhead can be alleviated by distributed neural networks running on multiple separate devices, existing distributed neural network techniques suffer from a large traffic between the devices; thus are very vulnerable to communication failures. These drawbacks make the distributed neural network techniques inapplicable to wearable devices, which are connected with each other through unstable and low data rate communication medium like human body communication. Therefore, in this paper, we propose a distributed neural network partitioning technique that is resilient to communication failures. Furthermore, we show that the proposed technique also improves the inference accuracy even in case of no communication failure, thanks to the improved network partitioning. We verify through comparative experiments with a real-life neural network application that the proposed technique outperforms the existing state-of-the-art distributed neural network technique in terms of accuracy and resiliency to communication failures.

Design and Implementation of DNS Name Autoconfiguration for Internet of Things Devices (사물인터넷 디바이스를 위한 DNS 네임 자동설정의 설계 및 구현)

  • Lee, Sejun;Jeong, Jaehoon
    • Journal of KIISE
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    • v.42 no.11
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    • pp.1441-1451
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    • 2015
  • As one of the most spotlighted research areas, these days, the Internet of Things (IoT) aims to provide users with various services through many devices. Since there exist so many devices in IoT environments, it is inefficient to manually configure the domain name system (DNS) names of such devices. Thus, for IPv6-based IoT environments, this paper proposes a scheme called the DNS Name Autoconfiguration (DNSNA) that autoconfigures an IoT device's DNS name and manages it. In the procedure for generating and registering an IoT device's DNS name, the standard protocols of the Internet Engineering Task Force (IETF) are used. Since the proposed scheme resolves an IoT device's DNS name into an IPv6 address in unicast through a DNS server, it generates less traffic than multicast-based mDNS (Multicast DNS) which is a legacy DNS application for the DNS name service in the smart home. Thus, the proposed scheme is more appropriate in multi-hop IoT networks than mDNS. This paper explains the design of the proposed scheme and its service scenarios, such as smart home and smart road. It also explains the implementation and testing of the proposed scheme in the smart grid.