• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.992-995
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• 2015

In this paper, we developed the computer room environments and infrastructure management systems to operate various networking devices and the infrastructure in the room, stably. The developed systems are composed of the computer room environment management system and the computing infrastructure management system. The computer room environment management system performs the role which the temperature and humidity detection node periodically detects the temperature and humidity and transmits the information to the remote intelligent server. The computing infrastructure management system enables the computer room's manager to check the information and maintenance history of the computing devices with a smart device supporting NFC(Near Field Communication).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.969-972
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• 2015

Many studies have been carried out in order to develop a frequency efficient communication system than the current communication system for satisfying the increasing demands of wireless data services in mobile communication systems. If a communication system dramatically improving the frequency utilization efficiency is not developed, service providers must maintain more number of base station equipments to meet the increasing demands of wireless data service. Service provider needs a system or method to reduce maintenance costs. Demands of wireless data service are changed according to time of day, location and so on. Power consumption can be reduced if the supplied power of communication systems is controlled by wireless data traffics. This paper describes the design and implementation of power management system of mobile communication base station's equipment based on smart grid. The proposed power management system controls the supplied power to the mobile communication infrastructures depending on the demand of wireless data. Field test results of the implemented system show the proposed system saves 26% of the power consumption in the base stations.

• The Journal of Bigdata
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• v.8 no.2
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• pp.73-82
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• 2023

With 78% of current fisheries workers being elderly, there's a pressing need to address labor shortages. Consequently, active research on smart aquaculture technologies, centered on object detection and tracking algorithms, is underway. These technologies allow for fish size analysis and behavior pattern forecasting, facilitating the development of real-time monitoring and automated systems. Our study utilized video data from cameras outside aquaculture facilities and implemented fish detection and tracking algorithms. We aimed to tackle high maintenance costs due to underwater conditions and camera corrosion from ammonia and pH levels. We evaluated the performance of a real-time system using YOLOv7 for fish detection and the SORT algorithm for movement tracking. YOLOv7 results demonstrated a trade-off between Recall and Precision, minimizing false detections from lighting, water currents, and shadows. Effective tracking was ascertained through re-identification. This research holds promise for enhancing smart aquaculture's operational efficiency and improving fishery facility management.

• Annual Conference of KIPS
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• 2013.05a
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• pp.121-122
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• 2013

스마트폰 시장의 급격한 성장으로 기업 업무들이 모바일 환경으로 이전되는 추세와 함께 다양한 모바일 운영체제들의 등장으로 개발 환경의 파편화가 발생하였고 이는 응용 프로그램의 개발 및 유지 보수를 저해하는 요소로 작용하였다. 이러한 문제를 해결하기 위한 모바일 환경의 크로스 플랫폼 기술로 하이브리드 앱이라는 방법론이 제시되었다. 하지만 하이브리드 앱이 가지고 있는 성능적 제약과 기능적 제약으로 시장에서의 주력 기술로 사용되지 못하고 있다. 이러한 단점들을 극복하기 위해 네이티브 환경의 장점을 활용할 수 있도록 하는 범용실행엔진, 자동변환 저작엔진 등의 시도들이 있다. 이 논문에서는 해당 문제를 또 다른 방법으로 접근한 개방형 모바일 클라우드 플랫폼을 소개한다. 모바일 클라우드 환경을 구성하여 모바일 사용자들에게 단말의 하드웨어나 운영체제와는 무관하게 다양한 모바일 환경을 제공할 수 있고 기존 모바일 환경에 비해 고성능의 컴퓨팅을 제공할 수 있게 하는 동작 메커니즘과 기술 특징을 설명한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.236-239
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• 2022

증강현실로 날씨, 뉴스 요약 등이 제공되거나 AI 비서 기능을 제공하는 스마트 미러(smart mirror)가 개발되고 있다. 본 작품에서는 IoT 통합제어, 뉴스 요약 및 날씨 정보 제공 등의 서비스를 하나의 웹 플랫폼으로 구축하고 이를 손가락 제스쳐 및 음성 명령으로 제어하는 것을 제안하고 구현하였다. 본 작품에서는 음성 인식을 통해 IoT 서비스를 직관적으로 이용할 수 있게끔 설계하여 사용자의 편의성을 높였으며, 디바이스를 직접 터치하는 방식이 아닌 finger gesture로 제어하는 방식을 채택해, 디바이스 유지 보수 및 위생 문제를 해결하였다. 단순 IoT 통합 제어 기능뿐만 아니라 다양한 컨텐츠 및 기능을 제공함으로써 통합 플랫폼의 기능을 수행할 수 있도록 하였다. 뉴스 홈페이지에서 Crawling한 뉴스를 text rank 알고리즘을 이용. 자동으로 요약하는 기능과, 사용자의 IP를 기반으로 위도와 경도를 추론, 해당 지역의 일기 예보 정보를 표현해 주는 등 단순 IoT 제어 플랫폼이 아닌, 통합 플랫폼의 기능을 다하도록 설계하였다. 이처럼 다양한 정보를 압축해서 사용자가 편하게 볼 수 있도록 제공하며, 직관적인 two track 제어 방식을 채택. 사용 대상의 편의성을 증대시켜 본 프로젝트는 기존 프로젝트보다 사용자에게 더 나은 사용 경험을 제공할 것이다.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.48-54
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• 2018

With the 4th industry era, smart factories are emerging. In the era of multi-product small scale production, unmanned transportation vehicles are rapidly increasing in utilization of unmanned transportation vehicles that carry and arrange goods in the work space. The conventional unmanned vehicle detected its position by using the guided line method and the position based method for indoor location recognition and movement. This method has disadvantages of initial high cost and maintenance / maintenance. In this paper, to solve the disadvantages, the method of predicting the direct path of the unmanned vehicle through the Kalman filter is verified using the white LED marker of the warehouse and the position data and the image data of the white LED marker recognition image. Through this, the reliability of the linear movement which occupies the most part in the lattice structure is secured. It is also expected that the reliance on additional position sensors will also be reduced.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.6
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• pp.517-524
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• 2017

The objective of this research is to improve the efficiency of data collection from many machine components on smart factory floors using IoT(Internet of things) techniques and cloud platform, and to make it easy to update outdated diagnostic schemes through online deployment methods from cloud resources. The short-term analysis is implemented by a micro-controller, and it includes machine-learning algorithms for inferring snapshot information of the machine components. For long-term analysis, time-series and high-dimension data are used for root cause analysis by combining a cloud platform and multivariate analysis techniques. The diagnostic results are visualized in a web-based display dashboard for an unconstrained user access. The implementation is demonstrated to identify its performance in data acquisition and analysis for rotating machinery.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.939-949
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• 2017

Prognostics and health management(PHM) is actively utilized by industry as an essential technology focusing on accurately monitoring the health state of a system and predicting the remaining useful life(RUL). An effective PHM is expected to reduce maintenance costs as well as improve safety of system by preventing failure in advance. With these advantages, PHM can be applied to the battery system which is a core element to provide electricity for devices with mobility, since battery faults could lead to operational downtime, performance degradation, and even catastrophic loss of human life by unexpected explosion due to non-linear characteristics of battery. In this paper we mainly review a recent progress on various models for predicting RUL of battery with high accuracy satisfying the given confidence interval level. Moreover, performance evaluation metrics for battery prognostics are presented in detail to show the strength of these metrics compared to the traditional ones used in the existing forecasting applications.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.301-308
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• 2021

It is important to develop a digital SOC (Social Overhead Capital) maintenance system for preemptive maintenance in response to the rapid aging of social infrastructures. Abnormal signals induced from structures can be detected quickly and optimal decisions can be made promptly using IoT sensors deployed on the structures. In this study, a digital SOC monitoring system incorporating a multimetric IoT sensor was developed for long-term monitoring, for use in cloud-computing server for automated and powerful data analysis, and for establishing databases to perform : (1) multimetric sensing, (2) long-term operation, and (3) LTE-based direct communication. The developed sensor had three axes of acceleration, and five axes of strain sensing channels for multimetric sensing, and had an event-driven power management system that activated the sensors only when vibration exceeded a predetermined limit, or the timer was triggered. The power management system could reduce power consumption, and an additional solar panel charging could enable long-term operation. Data from the sensors were transmitted to the server in real-time via low-power LTE-CAT M1 communication, which does not require an additional gateway device. Furthermore, the cloud server was developed to receive multi-variable data from the sensor, and perform a displacement fusion algorithm to obtain reference-free structural displacement for ambient structural assessment. The proposed digital SOC system was experimentally validated on a steel railroad and concrete girder bridge.