• Journal of Korean Society on Water Environment
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• v.26 no.4
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• pp.700-706
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• 2010

Along the 4 major rivers in korea, there are automatic water quality monitoring (AWQM) stations to immediately respond to any pollution incident. Real-time data (temperature, DO, pH, EC and TOC) collected at each station were statistically treated to exclude outliers and keep valid data using Dixon's test and Discordance test. These applied methods were compared in terms of the number of the outliers sorted out. There was no significant difference between these methods. On the other hand, more outliers were sorted out from EC and TOC data, comparing with other water quality items. EC data did not show partly any variation for a long time at H station. If measured signal does not exceed ${\pm}0.001mS/cm$ from the sectional mean, the signal should be treated as normal data. Therefore, another routine was added to the data screening system, some data which were removed as outlier were restored.

• Proceedings of the KSRS Conference
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• v.2
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• pp.598-601
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• 2006

Satellite imagery may contain large regions covered with atmospheric aerosol. A high-resolution satellite imagery affected by non-homogenous aerosol cover should be processed for land cover study and perform the radiometric calibration that will allow its future application for Korea Multi-Purpose Satellite (KOMPSAT) data. In this study, aerosol signal was separated from high resolution satellite data based on the reflectance separation method. Since aerosol removal has a good sensitivity over bright surface such as man-made targets, aerosol optical thickness (AOT) retrieval algorithm could be used. AOT retrieval using Look-up table (LUT) approach for utilizing the transformed image to radiometrically compensate visible band imagery is processed and tested in the correction of satellite scenery. Moderate Resolution Imaging Spectroradiometer (MODIS), EO-1/HYPERION data have been used for aerosol correction and AOT retrieval with different spatial resolution. Results show that an application of the aerosol detection for HYPERION data yields successive aerosol separation from imagery and AOT maps are consistent with MODIS AOT map.

• Journal of Environmental Science International
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• v.21 no.12
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• pp.1449-1454
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• 2012

The ion selective microelectrodes (ISME) have been applied to observe the continuous profiles of NO3-N and NH4-N in bulk solutions or biofilms. In order to evaluate the performance and applicability of ion concentration measuring system, the characteristics, such as slope of calibration curve, detection limit and potentiometric selectivity coefficient were investigated. The slopes of calibration curve showed high degree of correspondence for each target ion concentrations. And the detection limits of nitrate and ammonia ion selective microelectrode were 10-4.7 M and 10-4.4 M, respectively. These ion selective microelectrodes were proved that their own performance could be maintained for 16 days after making. NO3-N and NH4-N selective microelectrodes were also adapted to detect the continuous ion profiles of cilia media packed MLE (Modified Ludzack-Ettinger) process. And the monitored nitrate and ammonia ion profiles with the ion selective microelectrode were stable and well corresponded to the results with conventional ion chromatograph. However, the electric potential was unstable until 8 hr because of the unknown noise. The tip shape and performance of the ion selective microelectrode was stably kept over 2 days continuous monitoring.

• Smart Structures and Systems
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• v.13 no.5
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• pp.849-868
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• 2014

An indirect approach is explored for structural health bridge monitoring allowing for wide, yet cost-effective, bridge stock coverage. The detection capability of the approach is tested in a laboratory setting for three different reversible proxy types of damage scenarios: changes in the support conditions (rotational restraint), additional damping, and an added mass at the midspan. A set of frequency features is used in conjunction with a support vector machine classifier on data measured from a passing vehicle at the wheel and suspension levels, and directly from the bridge structure for comparison. For each type of damage, four levels of severity were explored. The results show that for each damage type, the classification accuracy based on data measured from the passing vehicle is, on average, as good as or better than the classification accuracy based on data measured from the bridge. Classification accuracy showed a steady trend for low (1-1.75 m/s) and high vehicle speeds (2-2.75 m/s), with a decrease of about 7% for the latter. These results show promise towards a highly mobile structural health bridge monitoring system for wide and cost-effective bridge stock coverage.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.11-16
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• 2019

Wireless sensor network is important for precision farming to monitor the growth environment of crops in open field, but radio signals are susceptible to different types of interference such as weather and physical objects. This paper designs and implements an environmental monitoring and weather forecast acquisition systems for smart field irrigation based on LoRa(Long Range) and then applies it to a test bed. And we evaluate the network reliability in terms of packet transmission success rate by comparing its condition on two criteria; the existence of obstacle or rain. The results show that much rain falls can affect on packet loss in LoRa field networks with obstacles.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.350-357
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• 2017

Purpose: In-situ monitoring of water quality is fundamental to most environmental applications. The high cost and long delays of conventional laboratory methods used to determine water quality, including on-site sampling and chemical analysis, have limited their use in efficiently managing water sources while preventing environmental pollution. The objective of this study was to develop an on-site water monitoring system consisting mainly of an Arduino board and a sensor array of multiple ion selective electrodes (ISEs) to measure the concentration of $NO_3$ ions. Methods: The developed system includes a combination of three ISEs, double-junction reference electrode, solution container, sampling system consisting of three pumps and solenoid valves, signal processing circuit, and an Arduino board for data acquisition and system control. Prior to each sample measurement, a two-point normalization method was applied for a sensitivity adjustment followed by an offset adjustment to minimize the potential drift that could occur during continuous measurement and standardize the response of multiple electrodes. To investigate its utility in on-site nitrate monitoring, the prototype was tested in a facility where drinking water was collected from a water supply source. Results: Differences in the electric potentials of the $NO_3$ ISEs between 10 and $100mg{\cdot}L^{-1}$ $NO_3$ concentration levels were nearly constant with negative sensitivities of 58 to 62 mV during the period of sample measurement, which is representative of a stable electrode response. The $NO_3$ concentrations determined by the ISEs were almost comparable to those obtained with standard instruments within 15% relative errors. Conclusions: The use of the developed on-site nitrate monitoring system based on automatic sampling and two-point normalization was feasible for detecting abrupt changes in nitrate concentration at various water supply sites, showing a maximum difference of $4.2mg{\cdot}L^{-1}$ from an actual concentration of $14mg{\cdot}L^{-1}$.

• Korean Journal of Ecology and Environment
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• v.40 no.2
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• pp.193-200
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• 2007

The objective of this study was to estimate uncertainty of online TOC analyzer in water quality monitoring system. A procedure for the estimation of measurement uncertainty of total organic compounds (TOC) based on the ISO approach is presented. It is based on a mathematical model that involves 4 input parameters (standardization, sensitivity, solute effect and representativeness). In this study, a major problem in estimating the uncertainty of online TOC analyzer was the solute effect. It was strongly depends on organic materials. So homogeneity of the sample is the most important consideration. Modified concentration and combined standard uncertainty was $4.71{\pm}0.36$ mg $L^{-1}$ by model modified in this study.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.366-375
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• 2022

The monitoring of electricity consumption using Internet of Things (IoT) technology is attracting attention as a technology to reduce operation costs of smart farms. In this study, we propose a method to apply a real-time electrical consumption monitoring system (the e-Gauge system) and utilization of the collected data real-time while a melon-producing smart farm is in operation. For this purpose, the electrical consumption data for the individual smart-farm facilities such as boilers, nutrient distribution systems, automatic controllers, circulation fans, boiler controllers, and other IoT-related utilities were collected during three months of melon cultivation period. By using the monitoring results, the electrical energy consumption pattern was analyzed as an example, and necessary considerations needed to optimally utilize the measurement data were suggested. This paper will be useful in lowering the technological implementation barriers for new researchers to build a electrical consumption monitoring system and reducing trial and errors in the usage of the generated data.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.3
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• pp.137-144
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• 2015

The purpose of this study is to develop an warning system to detect real-time water quality abnormality using a multivariate statistical approach. In this study, we applied principal component analysis among multivariate data analyses which was used for the correlation between water quality parameters considering the real-time algorithm to determine abnormality in water quality. We applied our approach to real field data and showed the utilization of algorithm for the real-time monitoring to find water quality abnormality. In addition, our approach with Korea Meterological Adminstration database identified heavy rain data due to climate change is one of the most important factors to explain water quality abnormality.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.2
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• pp.81-89
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• 2006

The purpose of this study was to evaluate the applicability of small RC(radio controlled) helicopter and single lens reflect camera as SFAP(Small Format Aerial Photography) aquisition system to monitor the vegetation coverage of wetland. The system used to take pictures of small artificial wetland were a common optical camera(Nikon F80 with manual lens whose focal length was 28mm) attached to the bottom of a RC helicopter with a 50 cubic inch size glow engine. Three hundreds pictures were taken at the altitude of 50m above the ground, from 23rd June to 7th September 2005. Four from the images were selected and scanned to digital images whose dimension were 2048${\times}$1357 pixels. Those images were processed and rectified with GCP(Ground Control Poins) and digital map, and then classified by the supervised- classification module of image processing program PG-steamer Version 2.2. The major findings were as follows ; 1. The final images processed had very high spatial resolution so that the objects bigger than 30mm like lotus(Nelumbo nucifera), rock and deck were easily identified. 2. The dominant plants of the monitoring site were Monochoria ragianlis, Typha latifolia, Beckmannia syzigachne etc. Because those species have narrow and long leaves and form irregular biomass, the individuals were hardly identifiable, but the distribution of population were easily identifiable depending on the color difference. 3. The area covered by vegetation was rapidly increased during the first month of monitoring. At the beginning of the monitoring 23th June 2005, The rate of area covered by vegetation were only 34%, but after 27 and 60 days it increased to 74%, and the 86% respectively.