• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.3
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• pp.325-331
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• 2010

Three-cup anemometers are popular devices for measuring wind speeds in automated weather stations, environmental monitoring systems, and wind turbines. Cup anemometers usually suffer from lack of long-term stability owing to the wear of the bearing systems that support the rotational parts. The bearing systems are susceptible to external pollutants, vibrations, and gusts. Therefore, these anemometers have to be calibrated regularly to maintain the desired characteristics for measuring wind speed. In the present study, a new in-situ calibration system to help reduce cost and save time by calibrating the cup anemometers at the installation site is proposed. A portable in-situ calibrator was fabricated. After the characteristics of this calibrator were verified, it was used to calibrate cup anemometers. Some of the calibration results were compared with the data obtained by wind tunnel testing.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.317-317
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• 2019

기상청에서는 시스템 이용자의 편의와 자료의 활용 증진을 위해 분리되어 있던 수문기상과 가뭄정보를 하나로 통합하여 '수문기상 가뭄정보 시스템(https://hydro.kma.go.kr)을 2017년 8월 1일부터 운영하고 있다. 본 시스템은 일반국민과 물관리 유관기관(회원)을 대상으로 관측, 수문기상 감시 예측, 기상 가뭄분석 전망으로 나눠 정보를 생산하여 서비스가 제공하고 있다. 수문기상 서비스는 관측 강수량(기상청, 유관기관), 기상청 위성 토양수분량 및 증발산량 자료와 레이더 관측 자료(Radar AWS Rainrate, RAR)를 GIS 기반 유역단위별(4대강권, 대권역, 중권역, 표준유역단위)로 관측 정보를 제공하며, UM(3km), 멀티모델앙상블, 레이더(MAPLE), 유역강수지수자료들로 예측 서비스를 제공하고 있다. 또한, 메타정보를 통해 유역별, 관측소별 상세조회가 가능하여 원하는 유역 또는 관측소를 선택 시 GIS지도에 위치가 표시되며 선택 지점의 정보를 손쉽게 확인할 수 있다. 가뭄 정보는 기상 가뭄 예보 정보와 가뭄 감시 정보를 제공하고 있다. 기상 가뭄 예보 정보는 매주 금요일에 발표되고 있는 기상 가뭄 예보 1개월 전망과 매월 10일경 관계부처(행정안전부, 기상청, 환경부, 농림축산식품부) 합동으로 발표하고 있는 가뭄 예 경보 3개월 전망자료를 제공하고 있으며, GIS 기반 행정구역 및 유역별로 나눠 여러 가지 가뭄지수(표준강수지수, 표준강수증발산지수, 강수평년비, 유효가뭄지수)를 활용하여 기상 가뭄 감시 정보를 제공하고 있다. 또한, 가뭄 감시 현황 정보는 다양한 형태(시계열, 가뭄지수 조회 및 다운로드, 분포도 비교)로도 확인할 수 있으며, 강수량분석 통계(누적 강수량, 강수량 순위, 무강수일수) 정보를 제공한다. 그 밖에 관측 자료(강수량 분포도, 토양수분량, 증발산량 등), 월별 언론모니터링 자료 등을 제공하고 있다. 향후 수문기상과 가뭄 재해에 선제적으로 대응하여 안정적인 물관리를 지원하고 자료의 신뢰도를 지속적으로 제고하여 우리나라에 맞는 수문기상 가뭄정보 시스템으로 거듭나도록 노력해 나갈 것이다.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.5
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• pp.595-610
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• 2003

The statistical indexes such as RMSE (Root Mean Square Error), Mean Bias error, and IOA (Index of agreement) are used to evaluate 3 Dimensional wind and temperature fields predicted by operational meteorological model RAMS (Regional Atmospheric Meteorological System) implemented in CARIS (Chemical Accident Response Information System) for the dispersion forecast of hazardous chemicals in case of the chemical accidents in Korea. The operational atmospheric model, RAMS in CARIS are designed to use GDAPS, GTS, and AWS meteorological data obtained from KMA (Korean Meteorological Administration) for the generation of 3-dimensional initial meteorological fields. The predicted meteorological variables such as wind speed, wind direction, temperature, and precipitation amount, during 19 ∼ 23, August 2002, are extracted at the nearest grid point to the meteorological monitoring sites, and validated against the observations located over the Korean peninsula. The results show that Mean bias and Root Mean Square Error are 0.9 (m/s), 1.85 (m/s) for wind speed at 10 m above the ground, respectively, and 1.45 ($^{\circ}C$), 2.82 ($^{\circ}C$) for surface temperature. Of particular interest is the distribution of forecasting error predicted by RAMS with respect to the altitude; relatively smaller error is found in the near-surface atmosphere for wind and temperature fields, while it grows larger as the altitude increases. Overall, some of the overpredictions in comparisons with the observations are detected for wind and temperature fields, whereas relatively small errors are found in the near-surface atmosphere. This discrepancies are partly attributed to the oversimplified spacing of soil, soil contents and initial temperature fields, suggesting some improvement could probably be gained if the sub-grid scale nature of moisture and temperature fields was taken into account. However, IOA values for the wind field (0.62) as well as temperature field (0.78) is greater than the 'good' value criteria (> 0.5) implied by other studies. The good value of IOA along with relatively small wind field error in the near surface atmosphere implies that, on the basis of current meteorological data for initial fields, RAMS has good potentials to be used as a operational meteorological model in predicting the urban or local scale 3-dimensional wind fields for the dispersion forecast in association with hazardous chemical releases in Korea.

• Journal of Environmental Science International
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• v.17 no.9
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• pp.1053-1068
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• 2008

This study aims to produce fundamental database for Environment Impact Assessment by monitoring vertical structure of the atmosphere due to the mountain valley wind in spring season. For this, we observed surface and upper meteorological elements in Sangin-dong, Daegu using the rawinsonde and automatic weather system(AWS). In Sangin-dong, the weather condition was largely affected by mountains when compared to city center. The air temperature was low during the night time and day break, and similar to that of city center during the day time. Relative humidity also showed similar trend; high during the night time and day break and similar to that of city center during the day time. Solar radiation was higher than the city, and the daily maximum temperature was observed later than the city. The synoptic wind during the measurement period was west wind. But during the day time, the west wind was joined by the prevailing wind to become stronger than the night time. During the night time and daybreak, the impact of mountain wind lowered the overall temperature, showing strong geographical influence. The vertical structure of the atmosphere in Dalbi valley, Sangin-dong had a sharp change in air temperature, relative humidity, potential temperature and equivalent potential temperature when measured at the upper part of the mixing layer height. The mixing depth was formed at maximum 1896m above the ground, and in the night time, the inversion layer was formed by radiational cooling and cold mountain wind.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.679-692
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• 2020

We coupled a CFD model to the WRF-Chem model (WRF-CFD model) and investigated the characteristics of flows and carbon monoxide (CO) distributions in a building-congested district. We validated the simulated results against the measured wind speeds, wind directions, and CO concentrations. The WRF-Chem model simulated the winds from southwesterly to southeasterly, overestimating the measured wind speeds. The statistical validation showed that the WRF-CFD model simulated the measured wind speeds more realistically than the WRF-Chem model. The WRF-Chem model significantly underestimated the measured CO concentrations, and the WRF-CFD model improved the CO concentration prediction. Based on the statistical validation results, the WRF-CFD model improved the performance in predicting the CO concentrations by taking complicatedly distributed buildings and mobiles sources of CO into account. At 04 KST on May 22, there was a downdraft around the AQMS, and airflow with a relatively low CO concentration was advected from the upper layer. Resultantly, the CO concentration was lower at the AQMS than the surrounding area. At 15 KST on May 22, there was an updraft around the AQMS. This resulted in a slightly higher CO concentration than the surroundings. The WRF-CFD model transported CO emitted from the mobile sources to the AQMS measurement altitude, well reproducing the measured CO concentration. At 18 KST on May 22, the WRF-CFD model simulated high CO concentrations because of high CO emission, broad updraft area, and an increase in turbulent diffusion cause by wind-shear increase near the ground.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.132-142
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• 2010

Characteristics of meteorological elements were analyzed at Hwagae and Agyang where are the representative areas of Hadong green tea cultivation in Korea. An automatic weather monitoring system (AWS) and a simple data log were employed to measure meteorological data such as temperature, relative humidity, precipitation, and wind direction and speed for 2009. The annual average air temperature of Hwagae and Agyang was 14.5 and 14.2, respectively, showing the warmest month in August ($25.4^{\circ}C$ for Hwagae and $24.9^{\circ}C$ for Agyang) and the coldest month in January ($0.3^{\circ}C$ for Hwagae and $0.2^{\circ}C$ for Agyang). Annual average of daily temperature difference (= daily maximum temperature - daily minimum temperature) was $11.3^{\circ}C$ for Hwagae and $11.1^{\circ}C$ for Agyang. Hwagae and Agyang had 62.7% and 65.3% of the annual average relative humidity, respectively. Annual precipitation was 1387 mm for Hwagae and 1793 mm for Agyang of which were higher of 605mm for Hwagae and 835 mm for Agyang compared to that in 2008. Majority of precipitation occurred between May and August, attributing 77.6% for Hwagae and 76.6% for Agyang to the annual precipitation. The annual total sunshine duration was 2054.3 hrs in Hwagae with the longest monthly sunshine duration in May (235.1 hrs) and the shortest monthly sunshine duration in July (102.5 hrs). Dominant wind direction changed seasonally from northwesterly wind in fall and winter to southeasterly wind in spring and summer. The annual average wind speed was 1.5 m $s^{-1}$ with the highest monthly wind speed of 2.0 m $s^{-1}$ in December and the lowest monthly wind speed of 1.1 m $s^{-1}$ in February. It is expected that continuous observation and assessment of meteorological data will improve our understanding of optimal environmental conditions for green tea cultivation and be used for developing models of green tea cultivation in the Hadong area.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1027-1034
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• 2011

In order to provide the basic information on the agricultural environment in Daegwallyeong Highland, the characters of weather, water, and soil quality were investigated. The meteorological characteristics was monitored by automatic weather system (AWS) at 17 sites. The quality of water for samples were collected monthly at 24 sites depending on landuse style. Soil samples were collected from a forest, grassland, and the major vegetable cultivation areas such as potato, carrot, Chinese cabbage, onion, head lettuce, and welsh onion field. The weather showed the mountain climate, and the average yearly temperature is $6.4^{\circ}C$, the average temperature in January is $-7.6^{\circ}C$ and the average temperature in July is $19.1^{\circ}C$, and the change of temperature on the districts of Daegwallyeong is severe. The yearly record of precipitation shows 1717.2 mm. The water quality of crop field was worse than forest or grassland in Daewallyeong highland. In 2005, annual T-N, T-P, SS distribution of Chinese cabbage field showed 7.4~11.3, 0.061~0.1, and $3.0{\sim}53.0mg\;L^{-1}$. The potato field showed 3.1~7.2, 0.019~0.056 and $0.5{\sim}3.0mg\;L^{-1}$, respectively. Being compared of water quality between potato field and chinese cabbage field, it showed that the water quality of Chinese cabbage field was worse than potato field. On farming, the soil of crop cultivation showed pH 5.6 to 6.8, $18.0{\sim}42.4g\;kg^{-1}$ of OM, $316{\sim}658mg\;kg^{-1}$ of Avail. $P_2O_5$. The content of cations showed $0.41{\sim}0.88cmol_c\;kg^{-1}$ of Exch. K, $3.73{\sim}7.07cmol_c\;kg^{-1}$ of Exch. Ca and $1.17{\sim}1.90cmol_c\;kg^{-1}$ of Exch. Mg.