• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.287-295
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• 2017

Recently, MTC (Machine Type Communication) is known as an important part to support IoT (Internet of Things) applications. MTC provides network connectivities between MTC devices without human intervention. In MTC, a large number of devices try to access over communication resource with a short period of time. Due to the limited communication resource, resource contention becomes severe and it brings about access failures of devices. To solve the problem, it needs to regulate device accesses. In this paper, we present an efficient access management scheme. We measure the number of devices which try to access in a certain time period and predict the change of the number of devices in the next time period. Using the predicted change, we control the number of devices which try to access. To verify our scheme, we conduct experiments in terms of success probability, failure probability, collision probability and access delay.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.73-81
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• 2020

HCCL stands for Heterogenous Container Class Library. HCCL is a library that allows heterogeneous types of data to be stored in a container as a single record and to be constructed as a list of the records to be stored in database. With HCCL, encryption/decryption can be done based on the unified data type. Recently, IoT sensor which is embedded in smartphone enables developers to provide various convenient services to users. However, it is also true that infringement of personal information may occur in the process of transmitting sensor information to API and users need to be prepared for this situation in some sense. In this study, we developed a data model that enhances existing security using SEED cryptographic algorithms while managing information of sensors based on HCCL. Due to the fact that the Android environment does not provide permission management function for sensors, this study decided whether or not to encrypt sensor information based on the user's choice so that the user can determine the creation and storage of safe data. For verification of this work, we have presented the performance evaluation by comparing with the situation of storing the sensor data in plaintext.

• Information and Communications Magazine
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• v.32 no.11
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• pp.12-20
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• 2015

최근 의학 기술이 눈부시게 발전함에 따라 사람들은 수명이 연장되고 삶의 질 향상에 많은 관심을 가지게 되었다. 더욱이 혁신적인 디지털 기술 발전과 함께 다양한 웨어러블 기기와 수많은 헬스케어 어플리케이션이 출시되고 있으며, 이들은 어떻게 하면 개인의 성향이나 체질에 잘 맞는 맞춤형 (개인화) 서비스를 제공할 수 있을 것인가에 관심을 두고 진화하고 있다. 따라서 IoT 환경의 일상생활에서 입력되는 센서 데이터의 수집, 처리, 가공 기술, 일상 행위 및 라이프 스타일 인지, 지식 획득 및 관리 기술, 개인화 추천서비스 제공, 프라이버시 및 보안을 통합적으로 지원할 수 있는 프레임워크 개발에 대한 요구가 증대되고 있다. 이에 본 고에서는 저자가 개발중인 개인 맞춤 건강 및 웰니스 서비스를 제공하는 마이닝 마인즈 프레임워크를 소개한다. 마이닝 마인즈는 현존하는 최신 기술의 집약체로 개인화, 큐레이션, 빅 데이터 처리, 클라우드 컴퓨팅의 활용, 다양한 센서 정보의 수집과 분석, 진화형 지식의 생성과 관리, UI/UX를 통한 습관화 유도 등 다양한 요소를 포함한다. 그리고 건강 및 웰니스 프레임워크 요구사항 분석을 통해 마이닝 마인즈가 이러한 요구를 충족시킬 수 있으며, 개발된 프로토타입을 통해 개인화 서비스의 발전 가능성을 입증하고 향후 나아가야 할 방향을 제시한다.

• Journal of KIBIM
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• v.14 no.4
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• pp.35-44
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• 2024

Embedded sensors in structures such as in roads play a critical role in monitoring structural degradation and ensure safety and longevity of structures. However, while initial positioning of these sensors is straightforward, accurately locating buried sensors becomes a challenge especially as road surfaces degrade over time. When sensors require maintenance, such as battery replacements, malfunction repairs, or damage fixes, the accuracy of their location is crucial to prevent unnecessary costs and road destruction, wasted labor hours, and compromised data integrity. This paper addresses this issue by proposing the BIM-based framework to accurately model and record the precise coordinates of sensors in using Revit-Dynamo approach. The BIM system not only documents sensor locations at the time of installation but also continuously updates this information as the road surface evolves. By using Dynamo automation, sensor data - including latitudes, longitudes, and elevation - is efficiently imported and managed within the BIM model, minimizing errors and enhancing operational efficiency. The study's approach shifts maintenance practices from a reactive to a proactive model, allowing for timely interventions based on accurate sensor location data. Furthermore, this paper explores the scalability of the approach for other infrastructure types and lays the groundwork for future technological enhancements, such as AI and IoT integration for predictive maintenance.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.409-415
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• 2016

Recently several techniques for disaster prevention based on IoT(Internet of Things) are being developed. In this paper, a new smart pattern classification method for electric loads is proposed. CT(Current Transformer) data are extracted from electric loads, and then the sampled CT data are converted using FFT and MFCC. FFT and FMCC data are used for the input data of neural networks. Experiments were conducted using FFT and MFCC data for 7 kinds of electric loads. Experiments results indicate the superiority of MFCC in comparison to FFT.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.249-254
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• 2019

According to the recent expansion of the network environment, the spread of smart devices is continuously increasing. With the spread of smart devices such as smart phones, smart pads and wearables, changes are taking place in smart technologies and IT convergence technologies. The development of smart technology is a key element of the 4th industrial technology. The Fourth Industrial Revolution expanded the new service-based industry by adding intelligence to residential, industrial and production environments using IT convergence and smart devices. Research on providing various services using smart technologies, such as smart home, smart factory, smart farm, and smart healthcare, is being conducted in variety. In particular, There is a sharp rise in smart homes due to the proliferation of IoT devices and the growth of sensor technology, control technology, applications, data management, and cloud services. Smart home services using smart technology provide residents with convenient, beneficial services and environments. Smart home service has complemented the existing home network service, but there still are flaws to be modified. In other words, the spread of smart devices, the development of service provider-oriented services, and the interlocking of services have limitations in providing services in consideration of user environment and user state. In order to solve this problem, this study proposes a smart home service system that considers the situation of the elderly.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.83-92
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• 2022

In this paper, we designed an algorithm that can control the state of PM by learning the chain failure pattern of PHM based air conditioning facility. It is an inevitable spread of PM due to the downtime caused by the failure of the air conditioning facility. The algorithm developed by us is to establish a PM management system through PHM, and it is an algorithm that maintains a constant stabilization state through learning the stop/operation pattern of the air conditioner and manages PM based on this. As a result of the simulating at a subway station for the performance qualification of the algorithm, it was verified that the concentration of PM reduces by 30% on average. In the case of stations with many passengers using the subway, the concentration of PM exceeded the Ministry of Environment Standards(100 ㎍/m³), but it was verified that the concentration of PM was improved at all stations where the simulation was conducted. In the future research is to expand the system to comprehensively manage not only PM but also pollutants such as CO₂, CO, and NO₂ in subway stations.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.577-578
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• 2020

본 연구의 목적은 흰점박이꽃무지 사육농가 및 사육환경에 대해 일반농가의 실태를 조사·분석하여 식용곤충 사육시설에 대한 기초 연구자료를 수집하기 위한 것이다. 전국에 곤충사육 농가로 등록한 업체 중에서 흰점박이꽃무지를 사육하는 농가 17농가를 대상으로 설문조사를 실시하여 농장운영 및 시설·장치 현황 등을 조사하였으며, 주요 결과는 다음과 같다. 일반적으로 곤충사육 농가는 대부분 농가형으로 운영되고 있지만, 생산업, 유통업 및 가공업 등으로 신고하여 곤충사육 농가에서 직접 생산, 가공 및 제품 개발 등을 하고 있는 것으로 나타났다. 그리고 대부분의 곤충사육 농가는 판넬 형식의 건축물 내에서 냉·난방기를 가동하여 곤충의 생육환경을 조성하고 있으며, 필요에 따라 IoT 기반의 사양관리 장치 및 운영관리 시스템을 활용하고 있는 것으로 파악되었는데, 식용곤충 대량생산을 위한 사양관리 장치 및 생산 기반시설 구축은 여전히 부족한 상황으로 개선이 필요해 보인다.