• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.61-67
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• 2024

In order to monitor the growth environment of new varieties of crops, it is necessary to build the agricultural production infrastructure and strengthen the agricultural resource management system using popular smart sensor tag technology. In addition, the infrastructure for improving high-quality new varieties of crops using IoT technology and the monitoring system must be strengthened. In other words, widespread smart sensor (RFID UHF Sensor Tag) technology for environmental monitoring required for improving new crop varieties is desperately needed in the smart farm environment. Therefore, in this paper, we implemented an integrated sensor that can implement smart tag functions based on heterogeneous integrated sensors. In addition, we developed a technology that can manage crops in real time through the implemented smart integrated tag and smartphone linkage. For this purpose, an integrated antenna capable of RFID and Bluetooth communication was constructed. In addition, a communication method that allows information to be collected directly from the smartphone through the Bluetooth function was used.

• Smart Media Journal
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• v.13 no.1
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• pp.18-23
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• 2024

Power efficiency management in smart farms is important due to its link to climate change. As climate change negatively impacts agriculture, future agriculture is expected to utilize smart farms to minimize climate impacts, but smart farms' power consumption may exacerbate the climate crisis due to the current electricity production system. Therefore, it is essential to efficiently manage and optimize the power usage of smart farms. In this study, we propose a system that monitors the power usage of smart farm equipment in real time and predicts the power usage one hour later using GRU. CT sensors are installed to collect power usage data, which are analyzed to detect and prevent abnormal patterns, and combined with IoT technology to efficiently manage and monitor the overall power usage. This helps to optimize power usage, improve energy efficiency, and reduce carbon emissions. The system is expected to improve not only the energy management of smart farms, but also the overall efficiency of energy use.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.277-284
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• 2021

Recently, the smart home environment is expected to be a platform that collects, integrates, and utilizes various data through convergence with wireless information and communication technology. In fact, the number of smart devices with various sensors is increasing inside smart homes. The amount of data that needs to be processed by the increased number of smart devices is also increasing, and big data processing systems are actively being introduced to handle it effectively. However, traditional big data processing systems have all requests directed to cluster drivers before they are allocated to distributed nodes, leading to reduced cluster-wide performance sharing as cluster drivers managing segmentation tasks become bottlenecks. In particular, there is a greater delay rate on smart home devices that constantly request small data processing. Thus, in this paper, we design a Apriori-based big data system for effective data processing in smart home environments where frequent requests occur at the same time. According to the performance evaluation results of the proposed system, the data processing time was reduced by up to 38.6% from at least 19.2% compared to the existing system. The reason for this result is related to the type of data being measured. Because the amount of data collected in a smart home environment is large, the use of cache servers plays a major role in data processing, and association analysis with Apriori algorithms stores highly relevant sensor data in the cache.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.174-175
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• 2023

21세기가 도래함에 따라 새로운 도시의 형태인 스마트시티는 다양한 기기들이 네트워크 상에 서로 연결되어 이용자에게 편리함을 제공한다. 하지만 사이버 공격 기법 또한 고도화되고 있다. 많은 IoT 기기들이 상호작용함에 따라 사이버 공격을 당하면 도시 전체가 피해를 입을 수 있다. 이에 따라 본 논문에서는 스마트시티에서 일어날 수 있는 보안 사고에 대해 분석하고 이를 대응하기 위한 제로트러스트 도입 전략에 대해 연구하고자 한다.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.177-183
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• 2019

We intend to improve the sustainability of rural villages by investigating the element technologies and platforms necessary for building smart villages. There are so many investment smart city platforms and solutions in many cities. but there are relatively few investments in rural or small cities. This situation can not only increase the urban problem due to the increase of population to the city, but also deepen the digital gap of citizens. So far, studies on smart village have been investigated in fragments. We will examine the cases applied to smart village as a whole and study the open smart village platform that analyzes the overall data storage and management of the village after the smart village was finally established. First, we will look at the overseas trends of smart village and second, we will study the smart village platform that efficiently manages smart village through the technology necessary for smart village.

• Smart Media Journal
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• v.13 no.2
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• pp.85-94
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• 2024

Artificial Intelligence of Things (AIoT), which combines AI and the Internet of Things (IoT), has recently gained popularity. Deep neural networks (DNNs) have achieved great success in many applications. Deploying complex AI models on embedded boards, nevertheless, may be challenging due to computational limitations or intelligent model complexity. This paper focuses on an AIoT-based system for smart sewing automation using edge devices. Our technique included developing a detection model and a decision tree for a sufficient testing scenario. YOLOv5 set the stage for our defective sewing stitches detection model, to detect anomalies and classify the sewing patterns. According to the experimental testing, the proposed approach achieved a perfect score with accuracy and F1score of 1.0, False Positive Rate (FPR), False Negative Rate (FNR) of 0, and a speed of 0.07 seconds with file size 2.43MB.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.203-212
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• 2019

Along with the recent fourth industrial revolution, the world's manufacturing powerhouses are pushing for national strategies to revive the sluggish manufacturing industry. Moon Jae-in, the government is in accordance with the trend, called 'advancement of science and technology is leading the fourth round of the Industrial Revolution' strategy. Intelligent information technology such as IoT, Cloud, Big Data, Mobile, and AI, which are key technologies that lead the fourth industrial revolution, is promoting the emergence of new industries such as robots and 3D printing and the smarting of existing major manufacturing industries. Advances in technologies such as smart factories have enabled IoT-based sensing technology to measure various data that could not be collected before, and data generated by each process has also exploded. Thus, this paper uses data generators to generate virtual data that can occur in smart factories, and uses them to analyze the cause of the defect in real time and to predict the replacement cycle of the facility.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.672-680
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• 2019

This paper proposes "A Smart Farm Environment Optimization and Yield Prediction Platform based on IoT and Deep Learning" which gathers bio-sensor data from farms, diagnoses the diseases of growing crops, and predicts the year's harvest. The platform collects all the information currently available such as weather and soil microbes, optimizes the farm environment so that the crops can grow well, diagnoses the crop's diseases by using the leaves of the crops being grown on the farm, and predicts this year's harvest by using all the information on the farm. The result shows that the average accuracy of the AEOM is about 15% higher than that of the RF and about 8% higher than the GBD. Although data increases, the accuracy is reduced less than that of the RF or GBD. The linear regression shows that the slope of accuracy is -3.641E-4 for the ReLU, -4.0710E-4 for the Sigmoid, and -7.4534E-4 for the step function. Therefore, as the amount of test data increases, the ReLU is more accurate than the other two activation functions. This paper is a platform for managing the entire farm and, if introduced to actual farms, will greatly contribute to the development of smart farms in Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.503-504
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• 2017

Recently, economic growth in the world has increased interest in healthy life, and the smart health care industry is growing. In the field of smart healthcare, wearable-type biometric information measurement technology has been highlighted due to the importance of IoT technology. The purpose of this study is to develop a wearable heart - rate monitoring system that can be applied to wearable health care and glove - type monitoring that enables convenient monitoring of heart rate during activity. For this purpose, a glove - type wearable health care system was developed and its performance was evaluated. Experimental results showed that the heartbeat monitoring was possible even in the presence of actual daily activities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.8057-8063
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• 2015

It is expected that internet of things can be used for various fields such as smart home, smart building and smart city as the representative case of ICT that sensor, communication and interface technologies operate organically and the researches of the technologies regarding internet of things are being carried out in each countries worldwide. However, many problems rise against internet of things continuously in respect of security. Among them, the problem of privacy is the one that should be solved definitely regarding internet of things. If user data does not remain during the process of user authentication, such the privacy problem can be solved. In this paper, we propose the framework of user authentication based on OAuth that is suitable for the environment of internet of things that can solve privacy problem and analyze its security.