• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.511-511
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• 2023

기후변화로 동절기 기온 저하에 따른 수도계량기의 동파는 지속적으로 심화되고 있으며, 이는 계량기 교체 비용, 누수, 누수량 동결에 의한 2차 피해, 단수 등 사회적 문제를 야기한다. 이와같은 문제를 해결하고자 구조적 대책으로 개별 가정에서 동파 방지형 계량기를 설치할 수 있으나 이를 위한 비용발생이 상당하고, 비구조적 대책으로는 기상청의 동파 지도 알림 서비스를 활용하여 사전적으로 대응하고자 하나, 기상청자료는 대기 온도를 중심으로 제공하고 있기 때문에 해당서비스만으로는 계량기의 동파를 예측하는데 필요한 추가적인 다양한 변수를 활용하는데 한계가 있다. 최근 정부와 공공부문에서 22개 지역, 110개소 이상의 수도계량기함내 IoT 온도센서를 시범 설치하여 계량기 함내의 상태 등을 확인할 수 있는 사업을 수행했다. 전국적인 계량기 상태의 예측과 진단을 위해서는 추가적인 센서 설치가 필요할 것이나, IoT센서 설치 비용 등의 문제로 추가 설치가 더딘 실정이다. 본 연구에서는 겨울 동파 예방을 위해 실제 온도센서를 기반으로 가상센서를 구축하고, 이를 혼합한 하이브리드 방식으로 동파위험 기준에 따라 전국 동파위험 지도를 구축하였다. 가상센서 개발을 위해 독립변수로 위경도, 고도, 음·양지, 보온재 여부 및 기상정보(기온, 강수량, 풍속, 습도)를 활용하고, 종속변수로 실제 센서의 온도를 사용하여 기계학습 모델을 개발하였다. 지역 특성에 따라 정확한 모델을 구축하기 위해 위치정보 및 보온재여부 등의 변수를 활용하여 K-means 방법으로 군집화 하였으며, 각 군집별로 3가지의 기계학습 회귀모델을 적용하였다. 최적의 군집 수를 검토한 결과 4개가 적정한 것으로 판단되었다. 군집의 특성은 지역별 구분과 유사한 패턴을 보이며, 모든 군집에서 Gradient Boosting 회귀모델을 적용하는 것이 적합한 것으로 나타났다. 본 연구에서 개발한 모델을 바탕으로 조건에 따라 동파 예측 알람서비스에 실무적으로 활용할 수 있도록 양호·주의·위험·매우위험 총 4개의 기준을 설정하였다. 실제 본 연구에서 개발된 알고리즘을 국가상수도정보 시스템에 반영하여 테스트 수행중에 있으며, 향후 지속 검증을 할 예정에 있다. 이를 통해 동파 예방 및 피해 최소화, 물절약 등 직간접적 편익이 기대된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.263-272
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• 2022

As a result of climate change, the heatwave and urban heat island phenomena have become more common, and the frequency of heatwaves is expected to increase by two to six times by the year 2050. In particular, the heat sensation index felt by workers at construction sites during a heatwave is very high, and the sensation index becomes even higher if the urban heat island phenomenon is considered. The construction site environment and the situations of construction workers vulnerable to heat are not improving, and it is now imperative to respond effectively to reduce such damage. In this study, satellite imagery, land surface temperatures (LST), and long short-term memory (LSTM) were applied to analyze areas above 33 ℃, with the most vulnerable areas with increased synergistic damage from heat waves and the urban heat island phenomena then predicted. It is expected that the prediction results will ensure the safety of construction workers and will serve as the basis for a construction site early-warning system.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• Wind and Structures
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• v.36 no.3
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• pp.201-213
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• 2023

In this study, the effect of sea surface temperature (SST) on the distribution of vertical wind speed in the atmospheric boundary layer of coastal areas was analyzed. In general, coastal areas are known to be more susceptible to various meteorological factors than inland areas due to interannual changes in sea surface temperature. Therefore, the purpose of this study is to analyze the relationship between sea surface temperature (ERA5) and wind resource data based on the meteorological mast of Høvsøre, the test bed area of the onshore wind farm in the coastal area of Denmark. In addition, the possibility of coastal disasters caused by abnormal vertical wind shear due to changes in sea surface temperature was also analyzed. According to the analysis of the correlation between the wind resource data at met mast and the sea surface temperature by ERA5, the wind speed from the sea and the vertical wind shear are stronger than from the inland, and are vulnerable to seasonal sea surface temperature fluctuations. In particular, the abnormal vertical wind shear, in which only the lower wind speed was strengthened and appeared in the form of a nose, mainly appeared in winter when the atmosphere was near-neutral or stable, and all occurred when the wind blows from the sea. This phenomenon usually occurred when there was a sudden change in sea surface temperature within a short period of time.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.199-208
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• 2023

The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.23-32
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• 2024

This study utilized minimum number of demographic variables and first-semester GPA of students to predict the final academic status of students at a vocational college in Seoul. The results from XGBoost and LightGBM models revealed that these variables significantly impacted the prediction of students' dismissal. This suggests that early academic performance could be an important indicator of potential academic dropout. Additionally, the possibility that academic years required to award an associate degree at the vocational college could influence the final academic status was confirmed, indicating that the duration of study is a crucial factor in students' decisions to discontinue their studies. The study attempted to model without relying on psychological, social, or economic factors, focusing solely on academic achievement. This is expected to aid in the development of an early warning system for preventing academic dropout in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.713-723
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• 2019

Due to the climate change and various rainfall pattern, it is difficult to estimate a rainfall criterion which cause inundation for urban drainage districts. It is necessary to examine the result of inundation analysis by considering the detailed topography of the watershed, drainage system, and various rainfall scenarios. In this study, various rainfall scenarios were considered with the probabilistic rainfall and Huff's time distribution method in order to identify the rainfall characteristics affecting the inundation of the Hyoja drainage basin. Flood analysis was performed with SWMM and two-dimensional inundation analysis model and the parameters of SWMM were optimized with flood trace map and GA (Genetic Algorithm). By linking SWMM and two-dimensional flood analysis model, the fitness ratio between the existing flood trace and simulated inundation map turned out to be 73.6 %. The occurrence of inundation according to each rainfall scenario was identified, and the rainfall criterion could be estimated through the logistic regression method. By reflecting the results of one/two dimensional flood analysis, and AWS/ASOS data during 2010~2018, the rainfall criteria for inundation occurrence were estimated as 72.04 mm, 146.83 mm, 203.06 mm in 1, 2 and 3 hr of rainfall duration repectively. The rainfall criterion could be re-estimated through input of continuously observed rainfall data. The methodology presented in this study is expected to provide a quantitative rainfall criterion for urban drainage area, and the basic data for flood warning and evacuation plan.

• Particle and aerosol research
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• v.16 no.3
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• pp.65-72
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• 2020

In this study, the indoor fine dust concentration in an office of the Korea Knowledge Industry Center was measured for about 80 hours when the concentration of atmospheric PM_2.5 was very high. The effect of the operation of the air cleaner and the forced ventilation system on the indoor PM_2.5 was investigated, and the particle size distribution of the indoor and outdoor particles was analyzed. When forced ventilator and air purifiers were partially used, the indoor PM_2.5 concentrations were maintained between 27.7 ㎍/㎥ and 32.9 ㎍/㎥ when the atmospheric PM_2.5 was 127.7 ㎍/㎥ to 141.6 ㎍/㎥ during working hours. It is more effective to operate the air purifier without operating the forced ventilation system when the concentration of the PM_2.5 is high since the PM_2.5 penetrating the installed filter is continuously introduced indoor from the outside.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.442-454
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• 2016

Recently, due to the increment of national income and the living standard of citizens, the leasure business has been dramatically expanded. Among the business, inland water activities such as cruise tour or water taxi have drawn attention from the people. As more people come for a new pleasure, the frequency and the number of services continues to rise yet the safety of people values less recently. In fact, the number of relating accidents also has risen accordingly. In order to prevent such accidents in inland waters, the vessels' real time voyage data, the advanced warning system and the emergency rescuing system are required. In this paper, we have developed navigation guiding application for safety of passengers and vessels in inland waters. Navigation guiding applications not only provide Inland Electronic Navigational Chart(IENC) and vessel information but also allows communication between traffic service center and nearby vessels in case of an emergency situation. In order to implement Navigation guiding applications, developing Inland Electronic Navigational Chart was inevitable. Therefore, IENC of Han River, has developed based on measuring the water depth using multi-beam echo sounder system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.3
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• pp.103-110
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• 2016

Recently, structural health monitoring system(SHMS) has been appled cable bridges as the effective maintenance tool and the management threshold is considered to assess the status of the bridge in SHMS. The threshold is generally determined by the allowable limit based on design specification because there is no method and standard for threshold calculation. In case of the conventional thresholds, it is difficult to recognize the event, abnormal behavior and gradual damage within the threshold. Therefore, this study reviewed the problem of previous methods and proposed the advanced methodologies based on probabilistic approach for threshold calculation which can be applied to practice work. Gumbel distribution is adopted in order to calculate the threshold for caution and warning states considering the expectations for return periods of 50 and 100 years. The thresholds were individually determined for measurement data and data variation to detect the various abnormal behaviors within allowable range. Finally, it has confirmed that the thresholds by the proposed method is detectable the abnormal behavior of real-time measuring data from SHMS.