• Journal of information and communication convergence engineering
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• 제10권1호
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• pp.11-20
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• 2012

In a marine ubiquitous sensor network (USN) system using expensive sensors in the harsh ocean environment, it is very important to discover failures and devise recovery techniques to deal with such failures. Therefore, in order to perform failure modeling, this study analyzes the USN-based real-time water quality monitoring service of the Gaduri Aqua Farms at Songdo Island of Yeosu, South Korea and devises methods of discovery and recovery of failure by classifying the types of failure into system element failure, communication failure, and data failure. In particular, to solve problems from the perspective of data, this study defines data integrity and data consistency for use in identifying data failure. This study, by identifying the exact type of failure through analysis of the cause of failure, proposes criteria for performing relevant recovery. In addition, the experiments have been made to suggest the duration as to how long the data should be stored in the gateway when such a data failure occurs.

• 센서학회지
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• 제23권1호
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• pp.58-65
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• 2014

We developed a low-cost automatic diagnosis system for water quality in cooling towers to measure the concentrations of key ingredients such as $Ca^{2+}$, $Cl^-$, $PO{_4}^{3-}$, and $Fe^{2+}$. $Ca^{2+}$, and $Cl^-$ are the main factors that cause the generation of scale, corrosion, and sludge in water pipes. $PO{_4}^{3-}$ prevents corrosion, sludge and scale by inhibiting the ions (i.e., $Ca^{2+}$, $Cl^-$) from sticking to the pipes. $Fe^{2+}$ is an indicator of pipe corrosion. The proposed system consists of a microprocessor, a specimen container and heater, a precision pump, relays and valves, LED optical sources, and photo detectors. It automatically collects water samples and carries out pretreatment for determining the concentration of each chemical, and then estimates the concentration of each ion using low-cost LED optical sources and detectors. Experimental results showed that the accuracy of the proposed system is sufficiently high for water quality diagnosis and management of cooling towers, demonstrating the possibility of the proposed system's wide usage in real environments.

• 한국컴퓨터정보학회논문지
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• 제21권8호
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• pp.57-64
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• 2016

Initial prevention activities and rapid propagation conditions is the most important to prevent diffusion of water pollution. If water pollutants flow into streams river or main stresm located in environmental conservation area or water intake facilities, we must predict immediately arrival time and the diffusion concentration to the proactive. National Institute of Environmental Research developed water pollution incident response prediction system linking dam and movable weir. the system is mathematical model which is updated daily. Therefore it can quickly predict the arrival time and the diffusion concentration when there are accident of oil spills and hazardous chemicals. Also we equipped with mathematical model and toxicity model of EFDC(Environmental Fluid Dynamics Code) to calculate the arrival time and the diffusion concentration. However these systems offer the services of an offline manner than real-time control services. we have ensured the reliability of data collection and have developed a real-time water quality measurement data transmission device by using the data linkage utilizing a mode bus communication and a commercial SCADA system, in particular, we implemented to be able to do real-time water quality prediction through information infrastructure of the water quality integrated management business created by utilizing the construction of the real-time prediction system that utilizes the data collected, the Open map, the visual representation using charts API and development of integrated management system development based on web maps.

• Journal of Biosystems Engineering
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• 제21권3호
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• pp.336-342
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• 1996

A 4.1MHz$1^H$ Nuclear Magnetic Resonance(NMR) sensor was designed and manufactured to evaluate the internal quality of fruits. The magnet console having 963gauss magnetic field induction was used for the NMR sensor. To optimize and evaluate the NMR sensor, glycerol and sugar-water solutions were used. $^1$H(proton) resonance signals were used to estimate the sugar contents in fruits. Artificial neural network models were developed to predict sugar contents in fruits from the proton resonance signals. The standard errors of prediction(SEP) were 0.565(apple), 0.394(pear) and 0.415(kiwi), respectively. The result implied that it was possible to evaluate apple, pear and kiwi into 3 grades using the NMR sensor.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.305-312
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• 1996

A 4.1MHz 1H Nuclear Magnetic Resonance (NMR) sensor was designed and manufactured to evaluate the internal quality of fruit. The magnet console having 963 gauss magnetic field induction was used for the NMR sensor. To optimize evaluate the NMR sensor, glycerol and sugar-water solutions were used. 1H(proton) resonance signals were use of to estimate the sugar contents in fruits the proton resonance signals and were validated . The standard errors of predictions(SEP) were 0.565(apple) , 0.394(pear) and 0.415(kiwi) respectively. The result implied that is possible to evaluate apple , pear and kiwi into 3 grades using the NMR sensor.

• Journal of Astronomy and Space Sciences
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• 제29권3호
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• pp.295-303
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• 2012

In this study, we compared the precipitable water vapor (PWV) data derived from the radiosonde observation data at Sokcho Observatory and the PWV data at Sokcho Global Positioning System (GPS) Observatory provided by Korea Astronomy and Space Science Institute, for the years of 2006, 2008, 2010, and analyzed the radiosonde seasonal, diurnal bias according to radiosonde sensor types. In the scatter diagram of the daytime and nighttime radiosonde PWV data and the GPS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study. Overall, the tendency that the wet bias of the radiosonde PWV increased as the GPS PWV decreased and the dry bias of the radiosonde PWV increased as the GPS PWV increased. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the nighttime except for 2006 winter, and in comparison for summer, RS92-SGP sensor showed the highest quality.

• Journal of information and communication convergence engineering
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• 제16권4호
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• pp.242-247
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• 2018

The data of K-Water waterworks is collected from various sensors and used as basic data for the operation and analysis of various devices. In this way, the importance of the sensor data is very high, but it contains misleading data due to the characteristics of the sensor in the external environment. However, the cleansing method for the missing data is concentrated on the prediction of the missing data, so the research on the detection and prediction method of the missing data is poor. This is a study to detect wrong data by converting collected data into quintiles and patterning them. It is confirmed that the accuracy of detecting false data intentionally generated from real data is higher than that of the conventional method in all cases. Future research we will prove the proposed system's efficiency and accuracy in various environments.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 봄 학술논문 발표대회
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• pp.61-62
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• 2022

The unit quantity is an important factor influencing the durability, workability, and quality of concrete. Methods for measuring the unit quantity include a high frequency heating method, a unit volume mass method, a capacitance method, and a microwave method. However, these methods have disadvantages of poor measurement method, time required, and accuracy, and a relatively experimental method compensating for these disadvantages was used to measure the unit quantity using a high frequency main sensor (FDR) capable of simple and fast measurement. In addition, the unit quantity was evaluated by analyzing the measurement data through deep learning.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1097-1100
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• 2003

Data Loggers for environmental monitoring are mostly dispersion in installation and systems located at long distance from monitoring system. And, it requests mostly flexible functions and high performances. that can fit to various sensor inputs, sensor interfaces and conditions or system working. In this research, we developed the micro controller based Data Logger with minimum hardware construction that allows the higher flexibility of application. Finally, we developed software function for water quality monitoring and tested in real system launched at Han river.

• 한국엔터테인먼트산업학회논문지
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• 제15권3호
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• pp.289-295
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• 2021

오늘날 인간의 삶의 질에 가장 중요하게 미치는 요인은 환경에서 기인된다고 생각된다. 기후변화와 지구 온난화 현상에 따른 폭우, 대설, 지진 등으로 장마, 태풍, 벌채면 붕괴, 미세먼지 등의 발생 빈도가 증가하여 피해 규모가 해마다 커짐에 따라 환경 분석 및 감시 시스템의 중요성은 날로 커지고 있다. 환경의 문제들 중 물(수질)에 의해 발생하는 문제는 그 비중이 매우 높은 바, 도시화, 산업화로 수질 오염사고 발생 때 피해 규모가 대형화 되었으며 사람들 사이에 물 안전망에 대한 우려가 증가하고 있다. 최근 5년간 4대강 유역에서 수질 오염 사고 359건(한강 129, 낙동강 51, 금강 25, 섬진강 및 영산강 19, 기타 85)이 발생하였으며, 이로 인해 물 공급 정지 및 오염된 수돗물 공급 등 사회 전반에 걸처 환경에 직간접적인 피해를 야기하였다. 따라서, 현재 4대강 중심의 수질(물) 관리 시스템에서 중소하천, 지류/지천, 저수지 등으로 수질 모니터링 대상을 확대 함 으로서수질 환경의 불확실성을 최소화할 수 있는 빅데이터 기반 수질 환경 관리 전략체계의 구축이 요구된다. 본 논문에서는 기존의 오랜 기간 축적하여 온 수질 정보 빅데이터를 이용한 인공신경망 미들웨어 구축을 통하여 유용한 수질 분석 정보를 제시 할 수 있는 수질 모니터링 미들웨어 구축방안을 제시하고자 한다.