• Journal of the Korean Society of Industry Convergence
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• v.27 no.5
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• pp.1199-1207
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• 2024

Automation systems have gained great attention with the evolution of communications technology. A smart automation is an Internet of Things (IoT) application that employs the Internet to monitor and control appliances using an automation system. Lack of IoT technology adoption, unattractive user interface, restricted wireless transmission range, and expensive costs are the constraints of existing home automation systems. The idea of integrating a large number of devices has a substantial impact on the widespread advancement in the field of autonomous systems. The Internet of Things is being used more and more to create internet-connected gadgets. In addition, a wide range of data and services centered on human connection are accessible through mobile sensing devices powered by the Internet of Things, such as smartphones, tablets, digital cameras, sensors, etc. This study describes the implementation and analysis of a MQTT protocol-based IoT-based home automation system utilizing NodeMCU. This enables customers to use a mobile application over the internet to monitor and manage household appliances from a distance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.981-984
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• 2015

IoT is network evolved one more step than Mobile or Internet based on the existing wire communication and can interconnect all people, things, and virtual space at any time, anywhere. In particular, Internet of Things technology is expected to be converged on medical service such as elderly home care, chronic disease management, and treatment, and then it also contributes to savings and service quality of in the medical field and leads the paradigm or innovation of healthcare industry. In this study, we analyzed the IoT technology and application cases of medical service based on the IoT at home and abroad.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.400-403
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• 2021

As IoT technology becomes popular, more and more data is being generated, and the diversity of data is also increasing. In particular, in smart factory or Home IoT systems, data processing is very important because various data is collected and processed in real time through sensors. In this paper, we present a method for collecting, analyzing, and monitoring various data generated by sensors in IoT environment through Raspberry Pi. We also validate its usefulness by demonstrating that the above processed data can be operated in conjunction with smart mirror and mobile application.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.1-9
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• 2021

In this paper, we propose an IoT-based traffic safety pedestrian system for the elderly by factor analysis. The proposed system performs a factor analysis of the elderly safety variables and uses the analysis results to provide an optimal path for the elderly. In order to verify the performance of this system, we experimented with performance measurements on elderly pedestrian paths. As a result, we confirm that it provides a better safety path than mobile navigation.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.404-420
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• 2021

In this paper, an automatic system of locating the indoor area with weak or no mobile signal was proposed and demonstrated experimentally by using the Internet of Things (IoT) technology. Nowadays, the technicians of mobile services providers need to go along with numerous heavy equipment to measure and record the mobile signal strength at outside environment. Recently, there are systems proposed to do such measurement at outdoor area by using the IoT technology automatically. However, these works could not be applied in the indoor area since there are difficulties to do the indoor mapping and positioning. In this work, the Bluetooth Low Energy (BLE) was used to tackle these two difficulties. After a proper placement of BLE in the testing site, while the technician walk around with a handheld analyzer, the data can be obtained accordingly for further analysis in the proposed system which includes the construction of floor plan, detection of mobile signal strength and suggestion of indoor base stations. The gift wrapping and centroid algorithms were used during the analysis. The experimental results showed that the proposed system successfully demonstrated the indoor mapping, positioning of weak mobile signal area and suggestion of indoor base stations for the normal rectangular rooms with an area of 100 m² on single floor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2119-2124
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• 2016

The Internet of things (IoT) needs to be an event-driven approach for efficient related time response and processing. The growth of mobile devices in Internet of Things (IoT) leads to a number of intelligent buildings related IoT applications. For instance, home automation controlling system uses client system such web apps on smartphone or web service to access the home server by sending control commands. The gateway based RESTful technology responsible for handling clients'requests attests an internet latency in case a large number of clients' requests submit toward the gateway increases. In this paper, we propose the design tasks of the IoT gateway for handling concurrency events. The gateway based event-driven architecture is designed for building IoT gateway using node.js on one side and communication protocol based message-oriented middleware known as XMPP to handle communications of intelligent building control devices connected to the gateway through a centralized hub.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.17-23
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• 2022

NB-IoT and LTE Cat.M1 based on LPWA(Low Power Wide Area) are commercialized and serviced by mobile carriers. As the demand for IoT devices is increased, the number of subscribers to these services is also increasing. In the beginning of service, there was no issue that eNB capacity for NB-IoT and LTE Cat.M1. However, as the number of subscribers increases, there is an issue that the eNB capacity for these service is insufficient. Active UE capacity issue may cause overload by continuous increase and temporary increase. In this paper, we propose a solution to solve the problem of LTE RRC(Radio Resource Control) Active UE capacity shortage and base station overload caused by the increase of NB-IoT and LTE Cat.M1 UE in same eNB. The proposed solution can increase a cell capacity without cell division and additional eNB, and can also improve the service quality of these UEs.

• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.45-51
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• 2018

In this paper, we propose a Designed and Developed home router management system. Through the fourth industrial revolution and development of IoT technology, now people can experience a wide range of IoT related services at their workplace or daily lives. At the industrial site, IoT devices are used to improve productivity such as factory automation, and at home, IoT technology is used to control home appliances from a remote distance. Usually IoT device is integrated and controlled by the router. Home router connects different IoT devices together at home, however when security issues arise, it can invade personal privacy. Even though these threats exist, the perception for home router security is still insufficient. In this paper, we have designed and developed home router management system using DEVS methodology to promote the safe use of home router. Through the DEVS methodology, we have designed the system and developed the mobile application. This management system enables users to set up security options for home router easily.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.189-194
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• 2020

Recently, various clustering techniques have been studied to efficiently handle data generated by heterogeneous IoT devices. However, existing clustering techniques are not suitable for mobile IoT devices because they focus on statically dividing networks. This paper proposes a probabilistic deep learning-based dynamic clustering model for collecting and analyzing information on IoT devices using edge networks. The proposed model establishes a subnet by applying the frequency of the attribute values collected probabilistically to deep learning. The established subnets are used to group information extracted from seeds into hierarchical structures and improve the speed and accuracy of dynamic clustering for IoT devices. The performance evaluation results showed that the proposed model had an average 13.8 percent improvement in data processing time compared to the existing model, and the server's overhead was 10.5 percent lower on average than the existing model. The accuracy of extracting IoT information from servers has improved by 8.7% on average from previous models.