• International journal of advanced smart convergence
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• v.12 no.2
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• pp.173-181
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• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.613-619
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• 2020

Hybrid media access control (MAC) is used in internet of things (IoT) network, because of communication feature concern with data capacity and communication interval between gateway and sensor nodes and the cost efficiency. Hybrid MAC consists of TDMA and CSMA generally. The distance between gateway and sensor node is openly changed in marine IoT network. Therefore, it is needed to control the period of timeslot of hybrid MAC used in marine IoT network. In this paper, the design rule of TDMA timeslot with the variable period depending on communication distance was proposed. It was confirmed from the analysis that 72 times communication between gateway and sensor nodes is possible in LoRa network by using the proposed TDMA variable timeslot scheme.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.743-749
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• 2020

Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.3
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• pp.119-127
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• 2015

In the IoT(Internet of Things) environment, methods that user can access sensor node directly to collect sensing data or manage sensor in a gateway have a limitations. To solve this problem, cloud based sensor network architectures are proposed. In this paper, we proposed CoAP based IoT architecture that a lightweight gateway is used for data gathering instead of using a heavy traditional one and users can request sensing data through IoT applications running in the cloud environment and analyze signaling message cost. By doing so, our system can reduce message cost compared to the traditional gateway based system.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.486-488
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• 2013

In the earth more than half of the space filled with water. In that water most of the part is in the form of oceans. The ocean atmosphere determines climate on the land. Combining the Underwater Acoustic Sensor Network (UWASN) system with Internet Of Things (IoT) is called Internet of Underwater Things (IoUT). Using IoUT we can find the changes in the ocean environment. Underwater sensor nodes are used in UWASN. Underwater sensor nodes are constructive in offshore investigation, disaster anticipation, data gathering, assisted navigation, pollution checking and strategic inspection. By using IoT components such as Database, Server and Internet, ocean data can be broadcasted. This paper introduces IoUT architecture and and explains fish forming application scenario with this IoUT architecture.

• Journal of IKEEE
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• v.22 no.3
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• pp.590-598
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• 2018

Recently, interest in IoT(Internet of Things) technology, which provides Internet services to objects, is increasing. IoT offers a variety of services in home networks, healthcare, and disaster alerts. IoT with LLN(Low Power & Lossy Networks) feature frequently loses sensor node. RPL, the standard routing protocol of IoT, performs global repair when data loss occurs in a sensor node. However, frequent loss of sensor nodes due to lower sensor nodes causes network performance degradation due to frequent full path reset. In this paper, we propose an additional selection method of the storage mode sensor node to solve the network degradation problem due to the frequent path resetting problem even after selecting the storage mode sensor node, and propose a method of equalizing the total path resetting number of each instance.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.7
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• pp.769-774
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• 2015

Sensor network as an infrastructure of IoT(Internet of Things) has reliability issue because sensor nodes have limited memory as well as bounded battery. To improve the reliability of network, this paper proposes a data distribution scheme. The proposed algorithm distributes the data which each sensor node periodically produces into neighbor nodes that have enough memory as well as battery. This distribution process goes on more than 1 hop for overcoming unexpected spatial crash. Through simulation, we have confirmed that the proposed scheme can improve the resilience of IoT without affecting the life time of sensor network.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.6-12
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• 2017

In this paper, we proposed IoT based Smart Health Service using Motion Recognition for Human UX/UI. Until now, sensor networks using M2M-based u-healthcare are using non-IP protocol instead of TCP / IP protocol. However, in order to increase the service utilization and facilitate the management of the IoT-based sensor network, many sensors are required to be connected to the Internet. Therefore, IoT-based smart health service is designed considering network mobility because it is necessary to communicate not only the data measured by sensors but also the Internet. In addition, IoT-based smart health service developed smart health service for motion detection as well as bio information unlike existing healthcare platform. WBAN communications used in u-healthcare typically consist of many networked devices and gateways. The method proposed in this paper can easily cope with dynamic changes even in a wireless environment by using a technology supporting mobility between WBAN sensor nodes, and systematic management is performed through detection of a user's motion.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.109-116
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• 2017

In this paper, we propose an Internet of Things (IoT) platform for ocean observation buoys. The proposed system consists of various sensor modules, a gateway, and a remote monitoring site. In order to integrate sensor modules with various communications interfaces, we propose a controller area network (CAN)-based sensor data packet and a protocol for the gateway. The proposed scheme supports the registration and management of sensor modules so as to make it easier for the buoy system to manage various sensor modules. Also, in order to extend communication coverage between ocean observation buoys and the monitoring site, we implement a multi-hop relay network based on a mesh network that can provide greater communication coverage than conventional buoy systems. In addition, we verify the operation of the implemented multi-hop relay network by measuring the received signal strength indication between buoy nodes and by observing the collected data from the deployed buoy systems via our monitoring site.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.122-127
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• 2016

In this paper, new spectrum sensing schemes based on analog/RF front-end processing are introduced for IoT wireless sensor networks. While the conventional approaches for wireless channel cognition have been issued in signal processing area, the RF spectrum cognition concept makes it feasible to achieve cognitive wireless sensor networks (C-WSNs). The spectrum cognition at RF processing is categorized as four kinds of sensing mechanisms. Two recent reseaches are described as promising candidates for the C-WSN. One senses spectrum by the frequency discriminating receiver, the other senses and detects from the frequency selective super-regenerative receiver. The introduced systems with simple and low-power RF architectures play dual roles of channel sensing and demodulation. simultaneously. Therefore, introduced spectrum sensing receivers can be one of the best candidates for IoT wireless sensor devices in C-WSN environments.