• Advanced Industrial SCIence
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• v.2 no.3
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• pp.8-14
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• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.77-84
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• 2024

Over the past few years, IoT edges have begun to emerge based on new low-latency communication protocols such as 5G. However, IoT edges, despite their enormous advantages, pose new complementary threats, requiring new security solutions to address them. In this paper, we propose a cloud environment-based IoT edge architecture model that complements IoT systems. The proposed model acts on machine learning to prevent security threats in advance with network traffic data extracted from IoT edge devices. In addition, the proposed model ensures load and security in the access network (edge) by allocating some of the security data at the local node. The proposed model further reduces the load on the access network (edge) and secures the vulnerable part by allocating some functions of data processing and management to the local node among IoT edge environments. The proposed model virtualizes various IoT functions as a name service, and deploys hardware functions and sufficient computational resources to local nodes as needed.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.51-58
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• 2016

Recently, with various developments made to smart-phones and other digital devices in the IoT environment, modern people tend to pursue comfort in their own lifestyles. These environment has helped us to obtain any information or data in despite of location and time. But it has caused them to be overly reliant on digital devices in doing any kind of daily work, trusting the digital devices more than oneself. As a result of this over reliance, modern people's memorizing and calculating ability have deteriorated critically. This symptom is known as the Digital Dementia. In this paper, we study the phenomenon of digital dementia caused by smart-phones, and we suggest a method of developing "memorize the phone number" game applications in IoT environment to the problem of digital dementia. Test results show that, through the use of application, not only the users were able to have fun memorizing the numbers, but also, to show improvement in their memorizing ability. Thus, we expect that the application suggested above will help in preventing digital dementia and maintain brain health.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.35-44
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• 2020

In this study, we propose a reliable command placement recognition algorithm using tangible commands blocks developed for our coding puzzle platform, and present its performance measurement results on an Augmented Reality testbed environment. As a result, it can recognize up to 30 tangible blocks simultaneously and their placements within 5 seconds reliably. It is successfully ported to an existing coding puzzle mobile app and can operate an IoT attached robot via bluetooth connected mobile app.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.526-528
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• 2022

In this study, through the capstone design project, an IoT based piano training system was developed after identifying problems in piano learning. The piano training system recognizes sheet music through image processing technology and checks whether the correct keyboard is struck through FFT transformation during piano practicing. By providing a visual effect and score display function using a rhythm game, it was possible to arouse interest in boring piano practice and increase the effect of piano learning.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.59-66
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• 2022

In this paper, by applying IoT technology to the Ultimate game, which is one of the games using Flyingdisc, the process of the game is traced based on the players and the flyingdisc, and a comprehensive relationship analysis between players is performed on the results of the game. A WiFi module with built-in GPS is attached in the players and flyingdisc. The player's ID, latitude/longitude values received from GPS and time are stored in the database in realtime during the game. Process informations of the game is also stored in the database at the same time using mobile Ultimate game App. Based on this informations after the game is over, we developed a system that can perform comprehensive analysis of the game contents. By using the informations stored in the database, the player-based game process and the flyingdisc-based scoring process are visualized in the virtual playground. Various game result informations for players are graphically analyzed using Python.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.991-1000
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• 2019

The flying-disc game has started since 1940. It has been spreading rapidly in Korea since 2007, mainly in elementary schools. Additionally, as sports science has been developed, research on flying discs has been continued to build a monitoring system for technological improvement and efficiency. In this paper, we acquire information on the user's flying-disc using 9-axis motion sensor and GPS. Then we propose a method for wireless transmission using Bluetooth 5.0. Specifically, the HW platform was designed and implemented not only to monitor a real-time data but also to compare and analyze rotational speed, flight trajectory, and a count of disc rotation through post-processing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.89-94
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• 2018

This paper investigated the design method of the smart sensor for implementing IoT (Internet of Things) service. The power supply of sensor consistently acquisting data is based on the energy harvesting technology and designed with piezoelectric transducer not affected by surrounding circumstances. The wireless communication interface for the transmission of data is designed with BLE (Bluetooth Low Energy). BLE is highly adequate wireless communication technology for low power consumption and short distance wireless communication. The main application of BLE is beacon whose usage range is extended from O2O (Online to Offline) service, navigator based on indoor positioning technology, and anti-theft/lost child prevention service to mobile game. This paper studied the method to extend wireless coverage for complementing the short wireless transmission distance of BLE. The wireless sensor network based on CATV network is proposed for the easy construction of BLE sensor network and extended wireless coverage.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.79-83
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• 2024

Digital Twin technology is rapidly transforming various industries by providing comprehensive virtual models that replicate physical objects or processes. In the context of agriculture, digital twin can be a game-changer. This technology can help in creating precise simulations of farming scenarios, thereby enabling farmers to make data-driven decisions and optimize farm operations. The potential benefits include improved crop yields, resource efficiency, and environmental sustainability. However, the implementation of digital twin technology in agriculture poses challenges, such as data management issues and the need for robust IoT infrastructure. Despite these hurdles, the future of digital twin in agriculture looks promising, with ongoing research and developments aimed at overcoming these obstacles.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.7-15
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• 2024

6G network technology represents the next generation of communications, supporting high-speed connectivity, ultra-low latency, and integration with cutting-edge technologies, such as the Internet of Things (IoT), virtual reality, and autonomous vehicles. These advancements promise to drive transformative changes in digital society. However, as technology progresses, the demand for efficient data transmission and energy management between smart devices and network equipment also intensifies. A significant challenge within 6G networks is the optimization of interactions between satellites and smart devices. This study addresses this issue by introducing a new game theory-based technique aimed at minimizing system-wide energy consumption and latency. The proposed technique reduces the processing load on smart devices and optimizes the offloading decision ratio to effectively utilize the resources of Low-Earth Orbit (LEO) satellites. Simulation results demonstrate that the proposed technique achieves a 30% reduction in energy consumption and a 40% improvement in latency compared to existing methods, thereby significantly enhancing performance.