• Journal of Korean Society of Water and Wastewater
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• 제31권3호
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• pp.197-204
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• 2017

This study was carried out to apply the UAV(Unmanned Aerial Vehicle) coupled with Multispectral sensor for the algae bloom monitoring in river. The study acquired remote sensing data using UAV on the midstream area of Gum River, one of four major rivers in South Korea. Normalized difference vegetation index (NDVI) is used for monitoring algae change. This study conducted water sampling and analysis in the field for correlating with NDVI values. Among the samples analyzed, the chlorophyll concentration exhibited strong and significant linear relationships with NDVI, and thus NDVI was chosen for algae bloom index to identify emergence aspect of phytoplankton in river. Aerial remote sensing technology can provide more accurate, flexible, cheaper, and faster monitoring methods of detecting and predicting eutrophication and therefore cyanobacteria bloom in water reservoirs compared to currently used technology. As a result, there was high level of correlation in chlorophyll-a and NDVI. It is expected that when this remote water quality and pollution monitoring technology is applied in the field, it would be able to improve capabilities to deal with the river water quality and pollution at the early stage.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.126-129
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• 2006

The marine environment is under considerable threat from intentional or accidental oil spills, ballast water discharged, dredging and infilling for coastal development, and uncontrolled sewage and industrial wastewater discharges. Monitoring spills and illegal oil discharges is an important component in ensuring compliance with marine protection legislation and general protection of the coastal environments. For the monitoring task an image processing system is needed that can efficiently perform the detection and the tracking of oil spills and in this direction a significant amount of research work has taken place mainly with the use of radar (SAR) remote sensing data. In this paper the level set image segmentation technique was tested for the detection of oil spills. Level set allow the evolving curve to change topology (break and merge) and therefore boundaries of particularly intricate shapes can be extracted. Experimental results demonstrated that the level set segmentation can be used for the efficient detection and monitoring of oil spills, since the method coped with abrupt shape’s deformations and splits.

• Journal of Korea Water Resources Association
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• 제39권4호
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• pp.299-311
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• 2006

In this paper it is outlined the methodology of estimating the parameters of water balance analysis method for calculating recharge, using ground water level rises in monitoring well when values of specific yield of aquifer are not available. This methodology is applied for two monitoring wells of the case study area in northern area of the Jeiu Island. A water balance of soil layer of plant rooting zone is computed on a daily basis in the following manner. Diect runoff is estimated by using SCS method. Potential evapotranspiration calculated with Penman-Monteith equation is multiplied by crop coefficients($K_c$) and water stress coefficient to compute actual evapotranspiration(AET). Daily runoff and AET is subtracted from the rainfall plus the soil water storage of the previous day. Soil water remaining above soil water retention capacity(SWRC) is assumed to be recharge. Parameters such as the SCS curve number, SWRC and Kc are estimated from a linear relationship between water level rise and recharge for rainfall events. The upper threshold value of specific yield($n_m$) at the monitoring well location is derived from the relationship between rainfall and the resulting water level rise. The specific yield($n_c$) and the coefficient of determination ($R^2$) are calculated from a linear relationship between observed water level rise and calculated recharge for the different simulations. A set of parameter values with maximum value of $R^2$ is selected among parameter values with calculated specific yield($n_c$) less than the upper threshold value of specific yield($n_m$). Results applied for two monitoring wells show that the 81% of variance of the observed water level rises are explained by calculated recharge with the estimated parameters. It is shown that the data of groundwater level is useful in estimating the parameter of water balance analysis method for calculating recharge.

• Journal of Soil and Groundwater Environment
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• 제10권2호
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• pp.12-19
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• 2005

Jeju island is one of the highest rainfall areas in the Korean peninsular. However, variation in rainfall amount is much great with years, which resulted in substantial variation in annual groundwater recharge and sustainable yield. Therefore, to cope with groundwater hazard including sea water intrusion and water level decline in accordance with successive extreme drought, Jeju province established a stepwise action system, in which management of representative monitoring wells and corresponding actions to water level conditions was enforced. In this study, rainfall and groundwater monitoring data were analyzed to determine management groundwater level on Jeju island. First, rainfall data for last 30 years were analyzed, which yielded a lower limit of rainfall at a confidence level of 99% as a basis rainfall. Only when the rainfall less than the basis rainfall was sustained over 3 months, the water levels were targeted for the analysis. For the water level data selected using the above criteria, the lower limit of 99% confidence interval was determined as a reference groundwater level. Finally, some ratios of reference groundwater level was determined as stepwise management groundwater level on Jeju island.

• Journal of Soil and Groundwater Environment
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• 제17권4호
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• pp.51-62
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• 2012

Effects of climate change on groundwater system requires understanding the groundwater system in temporal and spatial scales through the long-term monitoring. In this study, the spatio-temporal variations of groundwater were analyzed through the continuous observation of water level, electrical conductivity (EC) and water temperature with automatic data-loggers and sampling in a Gwangneung catchment, Korea, for the four years from 2008 to 2011. Groundwater monitoring were performed at the nest-type wells, MW1 and MW2, located in upsteam and downstream of the catchment, respectively. During the survey period, both the total amount of annual precipitation and the frequency of concentrated rainfall have increased resulting in the elevation of runoff. Water level of MW1 showed no significant fluctuations even during the rainy season, indicating the confined groundwater system. In contrast, that of MW2 showed clear seasonal changes, indicating the unconfined system. The lag-time of temperature at both wells ranged from one to three months depending on the screened depths. Results of chemical analyses indicated that major water compositions were maintained constantly, except for the EC decreases due to the dilution effect. Values of the stable-isotope ratios for oxygen and deuterium were higher at MW2 than MW1, implying the confined system at the upstream area could be locally developed.

• Journal of Microbiology and Biotechnology
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• 제15권1호
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• pp.192-196
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• 2005

Abstract Oligotrophic microbial fuel cells (MFCs) were tested for the continuous monitoring of low biochemical oxygen demand (BOD) by using artificial wastewater, containing glucose and glutamate, as check solution. Ten times diluted trace mineral solution was used to minimize the background current level, which is generated from the oxidation of nitrilotriacetate used as a chelating agent. The feeding rate of 0.53 ml/min could increase the sensitivity from 0.16 to 0.43 ${\mu}$A/(mg BOD/l) at 0.15 ml/min. The dynamic linear range of the calibration curve was between 2.0 and 10.0 mg BOD/l, and the response time to the change of 2 mg BOD/l was about 60 min. The current signal from an oligotroph-type MFCs increased with the increase in salts concentration, and the salt effect could be eliminated by 50 mM phosphate buffer.

• Proceedings of the KSR Conference
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• 한국철도학회 2005년도 춘계학술대회 논문집
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• pp.530-535
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• 2005

To monitor the flood level under heavy rainfall and the scour at railroad bridge, the system, which can effectively collect, store and transmit the data, is developed and applied to the field. The results in this study are as follows. 1) Monitoring for water level and scour depth is well done in view of the recording velocity and the accuracy of data which are measured. 2) This system is based on the web, internet and it is able to collect the realtime data and to analyze the risk. 3) When water level excesses the limit of danger level of a river on which railroad bridge is located, or when scour depth and angle of inclination of pier is increased, the scenario for early warning signal which sends to managers at central traffic control and drivers of trains is automatically made. It is judged that this system secures the safety of railroad and protects lives of train passengers as the warning signal sends to running train in advance at risky situation of railroad bridge under heavy rainfall.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1666-1668
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• 2004

By wireless transmission data, there is high possibility to get distortion and lose by noise and barrier on wireless. If the data check damaged and lost at receiver, can't make it clear and can't judge whether this data is right or not. Therefore, by wireless transmission data need the data error check algorithm in order to decrease the data's distortion and lose and to monitoring the transmission data as real time. This study consists of RF station for wireless transmission, Water Level Meter station for water level measurement and Error check algorithm for error check of transmission data. This study is also that investigation and search for error check algorithm in order to wireless digital data transmission in condition of the least data's damage and lose. Designed transmitter and receiver with one - chip micro process to protect to swell the volume of circuit. Had designed RF transmitter - receiver station simply by means of ATMEL one - chip micro process in the systems. Used 10mW of the best RF power and 448MHz-449MHz on frequency band which can get permission to use by Frequency Law made by Korean government

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.723-730
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• 2019

Acquiring instrumentation signals generated from nuclear power plants (NPPs) is essential to maintain nuclear reactor integrity or to mitigate an abnormal state under normal operating conditions or severe accident circumstances. However, various safety-critical instrumentation signals from NPPs cannot be accurately measured on account of instrument degradation or failure under severe accident circumstances. Reactor vessel (RV) water level, which is an accident monitoring variable directly related to reactor cooling and prevention of core exposure, was predicted by applying a few signals to deep neural networks (DNNs) during severe accidents in NPPs. Signal data were obtained by simulating the postulated loss-of-coolant accidents at hot- and cold-legs, and steam generator tube rupture using modular accident analysis program code as actual NPP accidents rarely happen. To optimize the DNN model for RV water level prediction, a genetic algorithm was used to select the numbers of hidden layers and nodes. The proposed DNN model had a small root mean square error for RV water level prediction, and performed better than the cascaded fuzzy neural network model of the previous study. Consequently, the DNN model is considered to perform well enough to provide supporting information on the RV water level to operators.

• International journal of advanced smart convergence
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• 제9권1호
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• pp.63-69
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• 2020

The rapid development in modern industrialization pollutant the water and atmospheric air across the globe that have a major impact on the human and livings health. In worldwide, every country government increasing the importance to improve the outdoor air pollution monitoring and control to provide quality of life and prevent the citizens and livings life from hazard disease. We proposed the environmental dust level detection method for outdoor facilities using sensor fusion technology to measure precise micro-dust level and monitor in realtime. In this proposed approach use the camera sensor and commercial dust level sensor data to predict the micro-dust level with data fusion method. The camera sensor based dust level detection uses the optical flow based machine learning method to detect the dust level and then fused with commercial dust level sensor data to predict the precise micro-dust level of the outdoor facilities and send the dust level informations to the outdoor air pollution monitoring system. The proposed method implemented on raspberry pi based open-source hardware with Internet-of-Things (IoT) framework and evaluated the performance of the system in realtime. The experimental results confirm that the proposed micro-dust level detection is precise and reliable in sensing the air dust and pollution, which helps to indicate the change in the air pollution more precisely than the commercial sensor based method in some extent.