• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.27-33
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• 2023

Demands for eco-friendly food materials are increasing rapidly because of increased interest in well-being and health care, deterioration of air quality due to fine dust, and various soil and water pollution. Aquaponics is a system that can solve various problems such as economic activities, environmental problems, and safe food provision of the elderly population. However, techniques for deriving the optimal growth environment should be preceded. In this paper, we intend to design an intelligent plant growth measurement system that considers the characteristics of existing aquaponics. In particular, we would like to propose a module configuration plan for learning data and judgment systems when providing a uniform growth environment, focusing on designing systems suitable for production sites that do not have high-performance processing resources among intelligent aquaponics production management modules. It is believed that the proposed system can effectively perform deep learning with small analysis resources.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.1-17
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• 2020

This study evaluated a debris landform distribution potential area map in the southwest region of the Korean peninsula. A GIS spatial integration technique and logistic regression method were used to produce a distribution potential area map. Seven topographic and environmental factors were considered for analysis and 28 different data set were combined and used to get most effective results. Moreover, in an accuracy assessment, the extracted results of the Distribution Potential area were evaluated by conducting a cross-validation module. Block stream showed the highest accuracy in the combination No. 6, and that DEM (digital elevation model) and TWI (topographic wetness index) have relatively high influences on the production of the Block stream Distribution Potential area map. Talus showed the highest accuracy in the combination No. 13. We also found that slope, TWI and geology have relatively high influences on the production of the Talus Distribution Potential area map. In addition, fieldwork confirmed the accuracy of the input data that were used in this study, and the slope and geology were also similar. It was also determined that these input data were relatively accurate. In the case of angularity, the block stream was composed of sub-rounded and sub-angular systems and Talus showed differences according to the terrain formation. Although the results of the rebound strain measurement using a Schmidt's hammer did not shown any difference in topographic conditions, it is determined that the rebound strain results reflected the underlying geological setting.

• Transactions of the Korean hydrogen and new energy society
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• v.35 no.3
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• pp.324-335
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• 2024

The container package type sealed water electrolysis production system installs mechanical balance of plant and electrical balance of plant as an integrated unit to enable independent operation within the package module. The auxiliary equipment required to operate the water electrolysis system must be integrated to reduce the installation area and shorten the installation time. At this time, as leak risk factors are placed in a dense space, when a hydrogen gas leak accident occurs, it can have a mutual influence on other adjacent facilities, so it contains various risk factors. In this study, when a gas leak occurs in a container packaged water electrolysis system, possible sources of leakage in the system according to the KS C IEC 60079-10-1:2015 and KGS GC101 standards were identified, and the leak rate and leak characteristics were calculated. did. The hazardous area and its range were calculated according to ventilation and dilution characteristics. In order to optimize ventilation characteristics, design of experiment was used to analyze the influence to evaluate the adequacy of ventilation, and overseas ventilation standards were analyzed and compared. In addition, the optimal ventilation structure and characteristics of the container packaged water electrolysis system were presented according to the results of the experimental design method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.1-14
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• 2015

Climate change caused by elevated greenhouse gases would affect crop production through different pathways in agricultural ecosystems. Because an agricultural ecosystem has complex interactions between societal and economical environment as well as organisms, climate, and soil, adaptation measures in response to climate change on a specific sector could cause undesirable impacts on other sectors inadvertently. An integrated system, which links individual models for components of agricultural ecosystems, would allow to take into account complex interactions existing in a given agricultural ecosystem under climate change and to derive proper adaptation measures in order to improve crop productivity. Most of models for agricultural ecosystems have been used in a separate sector, e.g., prediction of water resources or crop growth. Few of those models have been desiged to be connected to other models as a module of an integrated system. Threfore, it would be crucial to redesign and to refine individual models that have been used for simulation of individual sectors. To improve models for each sector in terms of accuracy and algorithm, it would also be needed to obtain crop growth data through construction of super-sites and satellite sites for long-term monitoring of agricultural ecosystems. It would be advantageous to design a model in a sector from abstraction and inheritance of a simple model, which would facilitate development of modules compatible to the integrated prediction system. Because agricultural production is influenced by social and economical sectors considerably, construction of an integreated system that simulates agricultural production as well as economical activities including trade and demand is merited for prediction of crop production under climate change.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.329-331
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• 2018

In this paper, we propose a monitoring system that starts with the supply of raw materials for threading, is processed into a lathe machine, and checks for defects of the product are automatically performed by the robot with Smart Factory technology through assembly and disassembly. Completion check according to the production instruction quantity and production instruction is made by checking the production status according to whether or not the raw material is worn by the displacement sensor, and checking the pitch and the contour of the processed female and male to determine OK and NG. The robotic system acts as a relay for loading and unloading of raw materials, pallet transfer, and overall process, and it acts as an intermediary for organically driving. The location information of the threaded products is collected by using the non-contact wireless tag and the energy saving system Production efficiency and utilization rate were checked. The environmental sensor collects the air-conditioning environment data (temperature, humidity), measures the temperature and humidity accurately, and checks the quality of product processing. It monitors and monitors the driving hazard level environment (overheating, humidity) of the product. Controls for CNC and robot module PLC as a heterogeneous system.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.65-72
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• 2014

To improve the productivity of manufacturing company, the analysis of loss in shop floor has to be conducted and validated. This paper introduces the downtime tracking module using the pre-developed shop floor information acquisition system. To collect the downtime, it utilized shop floor monitoring information, user-registered downtime event, equipment diagnosis algorithm and operator's input. Also, it provided the user interface for the analysis of downtime. From the results of a pilot study, the usability of developed system was validated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.2
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• pp.32-38
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• 2013

In recent years, anti-PID (Potential Induced Degradation) technologies have been studied and developed at various stages throughout the solar value chain from solar cells to systems in an effort to enhance long-term reliability of the photovoltaics (PV) system. Such technologies and applications must bring in profits economically for both manufacturers of solar cell/module and investors of PV systems, simultaneously for the development of the PV industry. In this study two selected anti-PID technologies, ES (modification of emitter structure) and ARC (modification of anti-reflective coating) were compared based on the economic features of both a cell maker with 60MW production capacity and an investor of 1MW PV power plant. As a result of this study, it is shown that ARC anti-PID technology can ensure more profits over ES technology for both the cell manufacturer and the investor of PV power plant.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• Wind and Structures
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• v.18 no.2
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• pp.195-213
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• 2014

Recently, the horizontal axis rotor performance optimizer (HARP_Opt) tool was developed in the National Renewable Energy Laboratory, USA. This innovative tool is becoming more popular in the wind turbine industry and in the field of academic research. HARP_Optwas developed on the basis of two fundamental modules, namely, WT_Perf, a performance evaluator computer code using the blade element momentum theory; and a genetic algorithm module, which is used as an optimizer. A pattern search algorithm was more recently incorporated to enhance the optimization capability, especially the calculation time and consistency of the solutions. The blade optimization is an aspect that is highly dependent on experience and requires significant consideration on rotor control strategies, wind data, and generator type. In this study, the effects of rotor control strategies including fixed speed and fixed pitch, variable speed and fixed pitch, fixed speed and variable pitch, and variable speed and variable pitch algorithms on optimal blade shapes and rotor performance are investigated using optimized blade designs. The effects of environmental wind data and the objective functions used for optimization are also quantitatively evaluated using the HARP_Opt tool. Performance indices such as annual energy production, thrust, torque, and roof-flap moment forces are compared.