• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.146-146
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• 2020

최근 하천의 유사 중 소류사량을 계측하기 위해 사용된 기존의 물리적 소류사 샘플러를 이용한 직접계측방법은 홍수 시에 깊은 수위와 빠른 유속, 계측 절차상의 위험성 때문에 현장관측이 매우 어려운 한계를 극복하기 위해 현업에서는 소류사량을 간접적으로 추정하는 이론식에 의한 방법이 광범위하게 활용되고 있으나 이 방법 또한 추정이론식의 적용지역, 적용방법에 따라 결과가 수십배 이상 큰 차이를 나타나 실제 활용성에 대한 문제점이 있다. 이러한 기존의 소류사량 측정 방법의 문제점을 보완하기 위해 소류사량을 간접계측하는 방법이 활발히 제안되고 있다. 대표적인 방법으로 하상 이동 시 소류사의 충돌음을 음향센서로 계측하여 신호처리를 통해 소류사량을 추정하는 계측기기인 하이드로폰이 있다. 그러나 국외의 소류사량 간접계측 장치는 소류사량의 운송량이 많을 경우 음향신호 중접으로 인해 펄스 수의 감소, 감지 가능한 입경크기의 제한 등의 문제가 있다. 또한 국내의 백무평(2018)이 제안한 소류사 분석 방법인 대역통과방법(B-P Method)는 소류사량 추정에 있어서 기존의 방법과는 달리 주파수 특성을 반영하여 이전 연구들에 비하여 펄스 검출률을 향상시겼지만 이 방법은 극히 낮은 저유속과 작은 입경이라는 실험조건에서 이루어졌다는 제한사항이 있다. 따라서 본 연구는 다양한 입경과 고유속에 대하여 소류사량을 정량화할 수 있는 방법을 제시하기 위해 소류사 입경이 하이드로폰에 충돌할 때 발생하는 단독입자의 충돌음을 계측하기 위한 실외 수로실험장치를 구축하여 계측을 수행하였다. 실험은 현장에서 대표 시료로 분류된 몇 가지 입경에 대해서 유량 변화에 따른 충돌음향과 소류사량 그리고 소류사 입경크기에 따른 하이드로폰에서 인지되는 음향 특성을 계측 및 분석하였다. 연구결과 입경 크기 및 수리조건 변화에 따른 하이드로폰의 충돌음향 특성을 파악하여 단일 입경별 소류사량 추정관계식을 산출하였다. 또한 산출된 추정 관계식의 특성치와 공급 소류사량 간의 관계를 유도해 보았다. 향후 혼합입경에 대한 실험과 추정 관계식 신뢰성 검토 후 추가적으로 다양한 실험조건을 고려하여 실제 하천에 운송되는 소류사량과의 교정관계 확립을 진행한다면 국내 소류사량 데이터 수집을 위한 현장 설치까지 가능할 것으로 사료된다.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.439-449
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• 2023

Recent advancements in data measuring technology have facilitated the installation of various sensors, such as pressure meters and flow meters, to effectively assess the real-time conditions of water distribution systems (WDSs). However, as cities expand extensively, the factors that impact the reliability of measurements have become increasingly diverse. In particular, demand data, one of the most significant hydraulic variable in WDS, is challenging to be measured directly and is prone to missing values, making the development of accurate data generation models more important. Therefore, this paper proposes an adversarially trained autoencoder (ATAE) model based on generative deep learning techniques to accurately estimate demand data in WDSs. The proposed model utilizes two neural networks: a generative network and a discriminative network. The generative network generates demand data using the information provided from the measured pressure data, while the discriminative network evaluates the generated demand outputs and provides feedback to the generator to learn the distinctive features of the data. To validate its performance, the ATAE model is applied to a real distribution system in Austin, Texas, USA. The study analyzes the impact of data uncertainty by calculating the accuracy of ATAE's prediction results for varying levels of uncertainty in the demand and the pressure time series data. Additionally, the model's performance is evaluated by comparing the results for different data collection periods (low, average, and high demand hours) to assess its ability to generate demand data based on water consumption levels.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.118-130
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• 2021

This study designs and validates a greenhouse complex environmental control algorithm with a multi-phase processing scheme that can combine and control actuators according to the degree of change in the greenhouse environment. The composite environmental control system is a system in which the complex environmental controller analyzes the information detected by sensors and operates appropriately actuators to maintain the crop growth environment. A composite environmental controller directs control devices driving actuators through a composite environmental control algorithm, which calculates the values necessary for the operation of the control devices. Most existing algorithms carry out control procedures on a single phase by iteration cycle, which can cause abnormal changes in the greenhouse environment due to errors in output. The proposed algorithm distributes control procedures over multiple phases: environmental control, environmental control, and device operation, and every iteration cycle, detects environmental changes in the environmental control phase first, and then combines control devices that can control the environment in the environmental control phase, and finally, performs the controls to derive the actuators in the device operation phase. The proposed algorithm is designed based on the analysis of the relationship between greenhouse environmental elements and control devices deriving actuators. According to verification analysis, the multi-phase processing scheme provides room to modify or supplement the setting value and enables the control devices to reflect changes in the associated environmental components.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.799-808
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• 2008

The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.

• Smart Media Journal
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• v.12 no.5
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• pp.36-45
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• 2023

Recently, in digital agriculture, the types and utilization of greenhouses based on IoT are spreading, and greenhouses are being modernized, enlarged, and even factoryized using smart technology. However, a specific standardization plan has not been proposed according to the equipment for data collection in the smart greenhouse and the size or shape of the greenhouse. In other words, there is a lack of standard data for facility equipment, such as the type and number of sensors and equipment according to the size of the greenhouse, the type of greenhouse construction film and materials suitable for crops and carbon neutrality. Therefore, in this study, the suitability of the implementation, installation and quantity of IoT equipment for data collection was tested, and some standard technologies were presented through the implementation of data collection and communication methods. In addition, impact strength, tensile, tear, elongation, light transmittance, and lifespan issues for PE, PVC, and EVA, which account for about 90% of existing greenhouses, were presented, and the shape, size, and environmental problems of greenhouses made of films were presented. presented in the text. In this research paper, a standardized carbon-neutral modular smart greenhouse using nano-material film was implemented as a solution to environmental problems such as greenhouse size, farm crop type, greenhouse lifespan, and film, and its performance with existing greenhouses was analyzed and presented. Through this, we propose a modularized greenhouse that can be expanded or reduced freely without distinction in the size of the greenhouse or the shape of farmhouse crops, and the lifespan is extended and standardized. Finally, the average characteristics of greenhouses using existing PE, PVC, and EVA films and the characteristics of greenhouses using new carbon-neutral nanomaterials are compared and reviewed, and a plan to implement an expandable IoT greenhouse that supports carbon neutrality is proposed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.307-315
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• 2023

Korea controls the departure of vessels based on the Maritime Safety Act such that only ships with seaworthiness can navigate in bad weather, but scientific evaluation results and quantitative basis for the designation of ships subject to control are insufficient. Opinions for improvement are being raised for a reasonable departure control operation. The purpose of this study is to evaluate the adequacy of the current departure control standards through actual measurement of tugboats, which are the type of vessels subject to control when a wind and wave advisory is effective, and to present quantitative grounds for improvement of controls. A sensor was installed on the tugboat to measure the ship's three-axis motion and hull acceleration, and the hull motion performance was measured by operating in the sea area with a significant wave height of 3 m. The measured values were compared and analyzed based on seaworthiness evaluation factors and limit value standards. The actual ship was excluded from the current control standard according to tonnage, but as a result of the analysis, the pitch value exceeded the operation standard, and a risk to navigation safety existed. The results of this study suggest the need for additional actual measurement studies that can represent various ship types and specifications and review ship departure control targets.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.27-34
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• 2024

The direct and indirect damages caused by fires in underground utility tunnels have a great impact on society as a whole, so efforts are needed to prevent and manage them in advance. To this end, research is ongoing to prevent disasters such as fire flooding by applying digital twin technology to underground utility tunnels. A network is required to transmit the sensed signals from each sensor to the platform. In essence, it is necessary to analyze the application of wireless networks in the underground utility tunnel environments because the tunnel lacks the reception range of external wireless communication systems. Within the underground utility tunnels, electromagnetic interference caused by transmission and distribution cables, and diffuse reflection of signals from internal structures, obstacles, and metallic pipes such as water pipes can cause distortion or size reduction of wireless signals. To ensure real-time connectivity for remote surveillance and monitoring tasks through sensing, it is necessary to measure and analyze the wireless coverage in underground utility tunnels. Therefore, in order to build a wireless network environment in the underground utility tunnels. this study minimized the shaded area and measured the actual cavity environment so that there is no problem in connecting to the wireless environment inside the underground utility tunnels. We analyzed the data transmission rate, signal strength, and signal-to-noise ratio for each section of the terrain of the underground utility tunnels. The obtained results provide an appropriate wireless planning approach for installing wireless networks in underground utility tunnels.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.484-499
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• 2024

Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.

• Journal of Bio-Environment Control
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• v.13 no.4
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• pp.217-225
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• 2004

This study was performed to provide the basic knowledge about the mushroom cultivation facilities. Classified current status of cultivation facilities in Gyeongnam province was investigated by questionnaire. The structure of Pleurotus eryngii cultivation facilities can be classified into the simple and permanent frame type. The simple frame structures were mostly single-span type, on the other hand, the permanent frame structures were more multi-span than simple structures. And the scale of cultivation facilities was very different regardless of structural type. But as a whole, the length, width and ridge height were prevailing approximately 20.0 m, $6.6\~7.0m$ and $4.6\~5.0m$ range, respectively. The floor area was about $132\~160\;m^2$, and floor was built with concrete to protect mushrooms from various harmful infection. The roof slope of the simple and permanent type showed about $41.5^{\circ}\;and\;18.6\~28.6^{\circ}$, respectively. The width and layer number of growing bed for mushroom cultivation were around $1.2\~1.6m$, 4 layers in common, respectively. Most of year round cultivation facilities were equipped with cooler, heater, humidifier, and ventilating fan. Hot water boiler was the most commonly used heating system, the next was electric heater and then steam boiler. The industrial air conditioner has been widely used for cooling. And humidity was controlled mostly by ultra-wave or centrifuging humidifier. But some farmers has been using nozzle system for auxiliary purpose. More then $90\%$ of the mushroom house had the independent environment control system. The inside temperature was usually controlled by sensor, but humidity and $CO_2$ concentration was controlled by timer for each growing stage. The capacity of medium bottle was generally 850 cc and 1100cc, some farms used 800 cc, 950 co and 1,250 cc. Most of mushroom producted has been usually shipped to both circulating company and joint market.