• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.53-58
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• 2003

This study was carried out to design, construct, and test a greenhouse monitoring system fur the environment and status of control devices in a greenhouse from a remote site using internet. The measuring items selected out of many environmental factors were temperature, humidity, solar radiation, CO$_2$, SOx, NOx concentration, EC, pH of nutrient solution, the state of control devices, and the image of greenhouse. The developed greenhouse monitoring system was composed of the network system and the measuring module. The network system consists of the three kinds of monitors named the Croup Monitor. the Client Monitor and the Server Monitor. The results of the study are summarized as follows. 1. The measuring module named the House Monitor. which is used to watch the state of the control device and the environment of the greenhouse, was developed to a embedded monitoring module using one chip microprocessor 2. For all measuring items. the House Monitor showed a satisfactory accuracy within the range of ${\pm}$0.3%FS. The House Monitors were connected to the Croup Monitor by communication method of RS-485 type and could operate under power and communication fault condition within 10 hours. The Croup Monitor was developed to receive and display measurement data received from the House Monitors and to control the greenhouse environmental devices. 3. The images of the plants inside greenhouse were captured by PC camera and sent to the Group Monitor. The greenhouse manager was able to monitor the growth state of plants inside greenhouse without visiting individual greenhouses. 4. Remote monitoring the greenhouse environment and status of control devices was implemented in a client/server environment. The client monitor of the greenhouse manager at a remote site or other greenhouse manager was able to monitor the greenhouse environment and the state of control devices from the Server Monitor using internet.

• Journal of Biosystems Engineering
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• v.25 no.4
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• pp.293-300
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• 2000

Automated greenhouse production system often require crop growth monitoring involving accurate quantification of plant physiological properties. Conventional methods are usually burdensome, inaccurate, and harmful to crops. A thermal image analysis system can accomplish rapid and accurate measurements of physiological-property changes of stressed crops. In this research a thermal imaging system was used to measure the leaf-temperature changes of several crops according to nutrient stresses. Thermal images were obtained from lettuce, cucumber, and pepper plants. Plants were placed in growth chamber to provide relatively constant growth environment. Results showed that there were significant differences in the temperature of stressed plants and non-stressed plants. In a case of the both N deficiency and excess, the leaf temperatures of cucumber were $2^{\circ}C$ lower than controlled temperature. The leaf temperature of cucumber was $2^{\circ}C$ lower than controlled temperature only when it was under N excess stress. For the potassium deficiency or excess stress, the leaf temperaures of cucumber and hot pepper were $2^{\circ}C$ lower than controls, respectively. The phosphorous deficiency stress dropped the leaf temperatures of cucumber and hot pepper $2^{\circ}C$ and $1.5^{\circ}C$ below than controls. However, the leaf temperature of lettuce did not change. It was possible to detect the changes in leaf temperature by infrared thermography when subjected to nutrition stress. Since the changes in leaf temperatures were different each other for plants and kinds of stresses, however, it is necessary to add a nutrient measurement system to a plant-growth monitoring system using thermography.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.409-421
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• 2017

Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to select optimal vegetation indices and regression model for estimating of rice growth using UAV images. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110 and Cannon IXUS camera during farming season in 2016 on the experiment field of National Institute of Crop Science. Before heading stage of rice, there were strong relationships between rice growth parameters (plant height, dry weight and LAI (Leaf Area Index)) and NDVI (Normalized Difference Vegetation Index) using natural exponential function ($R{\geq}0.97$). After heading stage, there were strong relationships between rice dry weight and NDVI, gNDVI (green NDVI), RVI (Ratio Vegetation Index), CI-G (Chlorophyll Index-Green) using quadratic function ($R{\leq}-0.98$). There were no apparent relationships between rice growth parameters and vegetation indices using only Red-Green-Blue band images.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.263-269
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• 2003

This research examined the capabilities of KOMPSAT-1 EOC images for the application of urban environment, including the urban changes of the study areas. This research is constructed in three stages: Firstly, for the application of change detection techniques, which utilizes multi-temporal remotely sensed data, the data normalization process is carried out. Secondly, the change detection method is applied for the systematic monitoring of land-use changes. Lastly, using the results of the previous stages, the land-use map is updated. Consequently, the patterns of land-use changes are monitored by the proposed scheme. In this research, using the multi-temporal KOMPSAT-1 EOC images and land-use maps, monitoring of urban growth was carried out with the application of land-use changes, and the potential and scope of the application of the EOC images were also examined.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.2
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• pp.52-62
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• 2010

This study was carried out in the Tropical Plant Resources Research Center of Korea National Arboretum to determine the optimum edaphic environment for the growth of tropical and subtropical plants. The physicochemical properties of artificial substrates and the growth characteristics of tropical and subtropical plants were investigated. Subtropical plants exhibited a high growth rate when cultivated in a substrate of Dry Zone that had physical properties similar to those of arid native soil. Mediterranean plants showed a low growth rate when grown in a substrate of Subtropical Zone that required changes in acidity. The substrate of Tropical Zone had high organic matter and mineral contents and therefore had good physical properties:this substrate has a good environment for the stimulation of the growth of tropical plants. Our results indicate that the chemical properties such as pH and mineral contents of most artificial substrates need to be more urgently improved than their physical properties in order to ensure better growth of tropical and subtropical plants. Initial management strategies for the construction of new tropical greenhouses were formulated, and data from monitoring studies will be continuously gathered and incorporated in the manual to keep it updated.

• Korean Journal of Environment and Ecology
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• v.29 no.2
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• pp.279-291
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• 2015

This study analyzed the growth characteristics of multi-layer planted trees through their growth analysis and attempted to present a management strategy. The subject of research is the Citizen's Forest Area of Seoul Forest Park located in Seoul City. Field surveys were conducted three times over eight years from 2005 when the Seoul Forest Park was created through 2013. Labels were attached to all trees in the target area, and their species, height and DBH were investigated. To identify the growth differences by trees in each area, a detailed tree location map was drawn up for use in the analysis. To check soil health, soil organic matter, soil pH and soil microbial activities were analyzed. It turned out that the growth of the multi-layer planted trees in the target area of research was higher than that of the trees in existing urban parks, and that it was similar to that of trees in natural forests. Through a field survey in the area with a remarkably low growth, high-density planting problem, soil was found to have excess-moisture and there was the problem of Pueraria lobata covering. As a result of the analysis of the soil, it was found that its organic content in the soil was lower; soil pH was higher; and microbial activities in the soil were lower when compared to that of natural forests.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.36-43
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• 2008

To develop the continuous water quality monitoring system using the daphnid Daphnia sp., the growth of test animal, sensitivity, and behaviour response of toxicants were observed. Growth of test animal significantly increased with increasing the food density under the 90~105 mg/L ($CaCO_3$) hardness, except the concentration of food (Chrollela sp.) was exceeded than optimal food supply. Behaviour responses of test animals were continuously analyzed by changes of fractal dimension value (FDV). The FDV sharply decreased after exposure to the concentrations of 0.13 mg/L copper, 0.06 mg/L lead, and 0.38 mg/L cadmium. In these concentrations, mortality and abnormal behaviour of daphnids exhibited within ca. 1.0-h after exposure. Comparison of 24-h $LC_{50}$ values with other zooplankton species indicated that sensitivity of the Daphnia sp. was higher than most zooplankton for lead, and brain shrimp, rotifer, and water flea (Ceriodaphnia dubia, D. magna) for copper, and brain shrimp, water flea (D. lumholzi), and amphipod for cadmium. Based on the above experimental results, significant relationship between toxicity and behaviour response of Daphnia sp. was supported the high potential of water quality monitoring system. Consequently, behavioural monitoring method in this study suggests a good estimation tool for detection of the discharged toxicants in water body and for ecotoxicological assessment aquatic organisms.

• Environmental Engineering Research
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• v.10 no.6
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• pp.283-293
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• 2005

Characteristics of sulfur-based autotrophic denitrification in a semi-continuous type reactor and the kinetic parameters were studied. Enriched autotrophic denitrifying culture was used for the reactor operation. Biomass growth on sulfur particles and in the liquid medium was monitored using the DAPI staining method. From the result of ion concentration changes and the biomass growth, maximum specific growth rate, ${\mu}_{max}$, and the half velocity constant, $K_M$, were estimated as $0.61\;d^{-1}$ and 3.66 mg/L, respectively. Growth yield coefficient, Y values for electron acceptor and donor were found as 0.49 gVSS/g N and 0.16 gVSS/g S. The biomass showed specific denitrification rate, ranging 0.86-1.13 gN/g VSS-d. A half-order equation was found to best simulate the denitrification process in the packed bed reactor operated in the semi-continuous mode.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.226-245
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• 2019

To understand the dynamics of radial growth of trees and micro-climate at a site of Korean fir (Abies koreana Wilson) forest on high-altitude area of Mt. Hallasan National Park, Jeju Island, Korea, high precision dendrometers were installed on the stems of Korean fir trees, and the sensors for measuring micro-climate of the forest at 10 minutes interval were also installed at the forest. Data from the sensors were sent to nodes, collected to a gateway wireless, and transmitted to a data server using mobile phone communication system. By analyzing the radial growth data for the trees during the growing season in 2016, we can estimate that the radial growth of Korean fir trees initiated in late April to early May and ceased in late August to early September, which indicates that period for the radial growth was about 4 months in 2016. It is interesting to observe that the daily ambient temperature and the daily soil temperature at the depth of 20 cm coincided with the values of about 10 ℃ when the radial growth of the trees initiated in 2016. When the radial growth ceased, the values of the ambient temperature went down below about 15 ℃ and 16 ℃, respectively. While the ambient temperature and the soil temperature are evaluated to be the good indicators for the initiation and the cessation of radial growth, it becomes clear that radii of tree stems showed diurnal growth patterns affected by diurnal change of ambient temperature. In addition, the wetting and drying of the surface of the tree stems affected by precipitation became the additional factors that affect the expansion and shrinkage of the tree stems at the forest site. While it is interesting to note that the interrelationships among the micro-climatic factors at the forest site were well explained through this study, it should be recognized that the precision monitoring made possible with the application of high resolution sensors in the measurement of the radial increment combined with the observation of 10 minutes interval with aids of information and communication technology in the ecosystem observation.

• Smart Structures and Systems
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• v.24 no.6
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• pp.723-732
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• 2019

Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.