• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.10
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• pp.43-52
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• 2011

In this paper, we propose the architecture of the policy-based emergency bio data transmission for the smart healthcare service. the medical staff can quickly and accurately monitor the emergency bio data of the remote patient through the proposed architecture. The proposed system consists of three parts: IEEE 11073-based agents and managers performing the aggregation function and transmission function of the bio data; the emergency management server performing the converting function between IEEE 11073 and HL7 and auto-diagnosis function of the policy-based; HL7 medical system based on HL7. Finally, by implementing the proposed system, we shows that the aggregation of the bio data and management of the emergency bio data in the smart healthcare service are possible.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.609-612
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• 2011

국내 해양 환경에 대한 조사 및 분석 연구는 미흡한 편에 있다. 최근 세계적으로 바다가 자원의 보고로 주목 받으면서 해양 모니터링 기술에 대한 연구가 활발히 진행 되고 있다. 특히 해양 환경을 분석하고 이해하기 위해서는 지속적으로 해양 환경 자료를 수집해야 하나 아직 많은 부분에서 제약 사항으로 남아 있다. 자동화된 해양 환경 자료의 수집과 수집된 자료를 분석하여서 해양재해를 예측하면 기름 유출에 의한 해양오염의 피해, 적조에 의한 수산업의 피해, 해양환경 이변에 의한 수산업 및 재해 피해를 최소화하는데 기여할 수 있다. 본 논문은 해양환경 감시 및 분석 시스템의 모델을 제안한다. 제안 시스템은 해양환경 정보를 자동 수집하여 해양환경을 지능적으로 감시한다. 또한 수집된 해양 자료를 분석하여서 해양 재해를 예측한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.10
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• pp.1485-1490
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• 2013

The demonstration project of the electrical grid for Smart grid is progressed, the smart digital appliances AV technology, Smart home energy management technology charging the management function of complex energy for the automation management of air conditioning and heating, humidity and air, the health care technology charging the design of housing for the elderly and disabled and the measurement of individual bio information, and the Smart home security technology dealing with the biometric security and motion sensors, etc. have been studied. The power monitoring terminal which uses a variety of wired and wireless networks and protocol is the target additionally to be considered in addition to the security vulnerabilities that was occurred in the existing terminal. In this research paper, the author analyzes the cryptographic techniques corresponding to the smart meter occurred by the problems that are exposed on the outside which are vulnerable to physical attacks, and intends to propose the design of the security systems for the Smart meter terminal being able to maximize the efficiency of the terminal.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.62-63
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• 2009

A monitoring system of collision risk among multiple ships is newly-designed in order to reduce human error and make vessel traffic control more effective. By using AIS data as ships' navigational information, an estimation algorithm of collision risk among multiple ships is newly-designed. To consider ships' course of now and future, collision risks of multiple ships can be calculated by using fuzzy algorithm. To test the performance of new algorithm, replay simulations are carried out on actual AIS data collected from VTS center of Ulsan harbor in Korea. The AIS data include 25 ships' information for two hours. In this paper, the features of newly-designed estimation algorithm of collision risk and the results of replay simulation are discussed.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.473-478
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• 2015

Recently, automatic video monitoring of individual pigs is emerging as an important issue in the management of group-housed pigs. Although a rich variety of studies have been reported on video monitoring techniques in intensive pig farming, it still requires further elaboration. In particular, when there exist adjoining pigs in a crowd pig room, it is necessary to have a way of separating adjoining pigs from the perspective of an image processing technique. In this paper, we propose an efficient image segmentation solution using both spatio-temporal information and region growing method for the identification of individual pigs in video surveillance systems. The experimental results with the videos obtained from a pig farm located in Sejong illustrated the efficiency of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.542-542
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• 2015

비점오염원은 기상조건과 토지이용에 따라 시간에 따른 오염부하량의 변동폭이 크게 발생하며, 강우초기에 오염물질의 농도가 크게 나타난다. MFFn은 강우지속시간에 따라 다양하게 변화하는 오염물질의 부하량과 유출량을 특정시점에서 강우유출율과 오염물질 유출율을 계산할 수 있으며, 강우가 시작될 때 0, 종료될 때 1의 값을 나타내며, 1보다 크면 초기세척이 있음을 나타낸다. 예를 들면 MFF20에서 평균값이 2.5이면 초기우수유출수의 부피 20%에 오염물질 부하량의 부피 50%를 포함하는 것을 의미한다. 본 연구에서는 논에서의 초기세척비율 정량화하기 위해 영산강수계 논지역(이하, 학야지구)과 섬진강수계 논지역(이하, 적성지구) 각 1개유역을 선정하여 2009년부터 2012년까지 수문 및 수질 모니터링을 수행하였다. 유역면적은 학야지구는 13.69 ha 이며, 적성지구는 8.06ha 이다. 두 지역 모두 외부유입이 없으며, 배수로가 구조물화 되어 있어 관측이 용이한 지점이다. 논에서 강우시유출되는 오염물질을 산정하기 위해서 배수로 말단에 압력식 수위계와 자동채수기를 설치하여 일정간격으로 관측하였으며, 수위별 유량관측을 통해 수위-유량관계곡선식을 산정 후 유량으로 환산하였다. 채취된 수질은 수질공정시험법을 통해 BOD, COD, TOC, T-N, T-P, SS를 분석하였으며, 관측된 유량과 수질자료를 이용하여 부하량을 산정하고, MFFn을 이용하여 초기세척비율을 정량화 하였다. BOD COD, TOC, T-N, T-P, SS 의 논 초기세척비율은 n 값이 10% 때 중앙값이 각각 1.3, 1.18, 1.13, 1.2, 1.13, 1.1 였으며, 13%, 11.8%, 11.3%, 12%, 11.3%, 11% 가 유출되는 것으로 나타났으며, n 값이 20%일 때 1.3, 1.1, 1.1, 1.25, 1.2, 1.2 이였으며, 26%, 22%, 22%, 25%, 24%. 24%가 유출되는 것으로 나타났다. n 값이 30%일 때 1.25, 1.0, 1.0, 1.25, 1.13, 1.3 였으며, 37.5%, 30%, 30%, 37.5%, 33.9%, 39%가 유출되는 것으로 나타났다.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.507-513
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• 2018

The maritime autonomous surface ship is automatically collects and manages various information necessary for the operation to minimize human intervention and safely perform the mission assigned to the ship. And the ship may autonomously operate the partial or entire route to the destination determined by the ship himself. This ship navigation technology allows partially remote control the ship to be operated if necessary. The maritime autonomous surface ship (MASS) should collect and manage signals of various navigation communication equipments and engines mounted on the ship for safe operation. This requires a common platform technology. In this paper, we propose a common platform that is the core of smart ship implementation. Territorial authorities and ships are connected by satellite or terrestrial communication. In such a communication environment, information is exchanged smoothly in real time. This allows the onshore authorities to monitor ships and provide remote control to enable safe vessel navigation at sea.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.11-19
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• 2018

Although many researches related to monitoring and automatic measuring devices for early warning system during slope failure have been carried out in Korea and aboard, most of the researches have installed measuring devices on the slope surface, and there are only few researches about warning systems that can detect and warn before slope failure and disaster occurs. In this study, slope failure simulation experiment was performed by attaching sensors to rock bolts, and initial slope behavior characteristics during slope failure were analyzed. Also, the experiment results were compared and reviewed with varied slope conditions, i.e. shotcrete slope and natural slope, and varied material conditions, i.e. GFRP and steel rock bolt. This study can be used as a basic data in development of warning and alarm system for early evacuation through early detection and warning before slope failure occurs in steep slopes and slope failure vulnerable areas.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• Journal of Mushroom
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• v.15 no.3
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• pp.118-123
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• 2017

This study was carried out to develop the technology to manage the growth of mushrooms, which were cultivated based on long-term information obtained from quantified data. In this study, hardware that monitored and controlled the growth environment of the mushroom cultivation house was developed. An algorithm was also developed to grow mushrooms automatically. Environmental management for the growth of mushrooms was carried out using cultivation sites, computers, and smart phones. To manage the environment of the mushroom cultivation house, the environmental management data from farmers cultivating the highest quality mushrooms in Korea were collected and a growth management database was created. On the basis of the database value, the management environment for the test cultivar (hukthali) was controlled at $0.5^{\circ}C$ with 3-7% relative humidity and 10% carbon dioxide concentration. As a result, it was possible to produce mushrooms that were almost similar to those cultivated in farms with the best available technology.