• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.459-468
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• 2019

Purpose: The cavity exploration of the lower part of the road is carried out to prevent ground-sinking. However, the detected communities cannot be identified by the cavity location and history information, such as repackaging the pavement. Therefore, the field applicability of RFID systems was evaluated in this study to enable anyone to accurately identify information. Method: During temporary recovery, tag recognition distance and recognition rate were measured according to underground burial materials and telecommunication tubes using RFID systems with electronic tag chips attached to the bottom of the rubber cap. Result: The perceived distance and perceived rate of depth for each position of the electron tag did not significantly affect the depth up to 15cm, but it did have some effect if the depth was 20cm. In addition, water effects from nearby underground facilities and rainfall are relatively small, and the effects of wind will need to be considered during the weather conditions of the road. Conclusion: The RFID tags for field application of the pavement management system store various information such as location and size of cavity, identification date, cause of occurrence, and surrounding underground facilities to maximize cavity management effect with a system that can be computerized and mobile utilization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.393-399
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• 2021

In this study, experiments were conducted to estimate the PM concentrations by learning the nighttime CCTV images of various PM concentrations environments. In the case of daytime images, there have been many related studies, and the various texture and brightness information of images is well expressed, so the information affecting learning is clear. However, nighttime images contain less information than daytime images, and studies using only nighttime images are rare. Therefore, we conducted an experiment combining nighttime images with non-uniform characteristics due to light sources such as vehicles and streetlights and building roofs, building walls, and streetlights with relatively constant light sources as an ROI (Region of Interest). After that, the correlation was analyzed compared to the daytime experiment to see if deep learning-based PM concentrations estimation was possible with nighttime images. As a result of the experiment, the result of roof ROI learning was the highest, and the combined learning model with the entire image showed more improved results. Overall, R² exceeded 0.9, indicating that PM estimation is possible from nighttime CCTV images, and it was calculated that additional combined learning of weather data did not significantly affect the experimental results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.203-210
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• 2011

The current sensor network analyzes the data collected by the sensing of fixed sensor nodes and provides a service. However, this method cannot actively handle the state and the change in the position of people, 'the target for sensing and the change in the environment', including home automation, building automation and real-time road & weather information, and healthcare environment, etc. To support a dynamic situation which is appropriate for an individual in this diverse environment, it is necessary to provide actively differentiated specific information according to the movement of people and the changes in the environment. In this study, a individualized sensor mobile agent middleware which provides the individualized information (the location of fire incidence and the trace for the path of spread), has been realized through the sensor network environment constructed by the installation of wireless sensor nodes mounted with mobile agent middlewares in buildings.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.929-936
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• 2007

The novel vision-based scheme for real-time extracting traffic parameters is proposed in this paper. Detecting and tracking of vehicle is processed at local region installed by operator. Local region is divided to segmented regions by edge and frame difference, and the segmented regions are classified into vehicle, road, shadow and headlight by statistical and geometrical features. Vehicle is detected by the result of the classification. Traffic parameters such as velocity, length, occupancy and distance are estimated by tracking using template matching at local region. Because background image are not used, it is possible to utilize under various conditions such as weather, time slots and locations. It is performed well with 90.16% detection rate in various databases. If direction, angle and iris are fitted to operating conditions, we are looking forward to using as the core of traffic monitoring systems.

• Journal of KIBIM
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• v.4 no.2
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• pp.25-32
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• 2014

Today, there is a growing need of environment-friendly buildings, so-called 'green', facilities, and energy saving buildings to decrease environmental pollutants released into cities by construction activities. Green-Building Information Modeling (Green-BIM) is a purpose-built solution which supports to forecast energy consumption of 3-D model of a building by augmenting its primary 3-D measurements (width, height and depth) with many more dimensions (e.g. time, costs, social impacts and environmental consequences) throughout a series of sequential phases in the lifecycle of a building. The current study was carried out in order to integrate vegetation systems (particularly green roof and green wall systems) and investigate thermal performance of the new Sainsbury's building which will be built on Melton road, Leicester, United Kingdom. Within this scope, a 3-D building model of the news Sainsbury's building was first developed in $Autodesk^{(R)}$ $Revit^{(R)}$ and this model was then simulated in $Autodesk^{(R)}$ $Ecotect^{(R)}$once weather data of the construction site was obtained from $Autodesk^{(R)}$ Green Building $Studio^{(R)}$. This study primarily analyzed data from (1) solar radiation, (2) heat gains and losses, and (3) heating and cooling loads simulation to evaluate thermal performance of the building integrated with vegetation system or conventionally available envelops. The results showed that building integrated vegetation system can potentially reduce internal solar gains on the building rooftops by creating a 'bioshade'. Heat gains and losses through roofs and walls were markedly diminished by offering greater insulation on the building. Annual energy loads for heating and cooling were significantly reduced by vegetation more significantly through the green roof system in comparison to green wall system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.63-70
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• 2011

A bicycle is different from vehicles in the structure that a rider is fully exposed to the surrounding environment. Therefore, it needs to make use of prior information about local weather, air quality, trail road condition. Moreover, since it depends on human power for moving, it should acquire route property such as hill slope, winding, and road surface to improve its efficiency in everyday use. Recent mobile applications which are to be used during bicycle riding let us aware of the necessity of development of intelligent bicycles. This study aims to develop a riding state (up-hill, down-hill, accelerating, braking) recognition algorithm using a low-power wrist watch type embedded system which has 3-axis accelerometer and wireless communication capability. The developed algorithm was applied to 19 experimental riding data and showed more than 95% of correct recognition over 83.3% of the total dataset. The altitude and temperature sensor also in the embedded system mounted on the bicycle is being used to improve the accuracy of the algorithm. The developed riding state recognition algorithm is expected to be a platform technology for intelligent bicycle interface system.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.99-105
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• 2014

Since traffic accidents account for the highest proportion of the artificial disasters which occur in urban areas along with fire, more scientific an analysis on the causes of traffic accidents and various prevention measures against traffic accidents are needed. In this study, the research selected Jinju-si, which belongs to local small and medium-sized cities as a research target to analyze the characteristics of temporal and spacial distribution of traffic accidents by associating the data of traffic accidents, occurred in 2013 with the causes of traffic accidents and location information that includes occurrence time and seasonal features. It subsequently examines the spatial correlation between traffic accidents and the characteristics of urban space development according to the plans of land using. As a result, the characteristics of accident distribution according to the types of accidents reveal that side right-angle collisions (car versus car) and pedestrian-crossing accident (car versus man) showed the highest clustering in the density analysis and average nearest neighbor analysis. In particular, traffic accidents occurred the most on roads which connect urban central commercial areas, high-density residential areas, and industrial areas. In addition, human damage in damage conditions, clear day in weather condition, dry condition in the road condition, and three-way intersection in the road way showed the highest clustering.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.54-68
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• 2014

In order to analyze the land surface properties in Seoul and its surrounding metropolitan area, several indices and land surface temperature were calculated by the Landsat satellites (e.g., Landsat 5, Landsat 7, and Landsat 8). The Landsat data came from only in the fall season with Landsat 5 on October 21, 1985, Landsat 7 on September 29, 2003, and Landsat 8 on September 16, 2013. The land surface properties used are the indices that represented Soil Adjusted Vegetation Index (SAVI), Modified Normalized Difference Wetness Index (MNDWI), Normalized Difference Wetness Index (NDWI), Tasseled cap Brightness, Tasseled cap Greenness, Tasseled cap Wetness Index, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) and the land surface temperature of the area in and around Seoul. Most indices distinguish very well between urban, rural, mountain, building, river and road. In particular, most of the urbanization is represented in the new city (e.g., Ilsan) around Seoul. According to NDVI, NDBI and land surface temperature, urban expansion is displayed in the surrounding area of Seoul. The land surface temperature and surface elevation have a strong relationship with the distribution and structure of the vegetation/built-up indices such as NDVI and NDBI. While the NDVI is positively correlated with the land surface temperature and is also negatively correlated with the surface elevation, the NDBI have just the opposite correlations, respectively. The NDVI and NDBI index is closely associated with the characteristics of the metropolitan area. Landsat 8 and Landsat 5 have very strong correlations (more than -0.6) but Landsat 7 has a weak one (lower than -0.5).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7329-7334
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• 2015

This is to analyze of driver behavioral and the accident characteristics in rollover. The study period was January 2011 to May 2014 and the subject of study was 102 person who were drivers visited the emergency room. Research tool includes a damage information of the vehicle, accident mechanism, damage to the patient clinical information with the injury data from the ROAD Traffic Authority. For data analysis, SPSS 18.0 was used for t-test, ANOVA and Chi-square test. Injury Severity Score average score according to the vehicle type is 6.00 points in the smaller vehicle, at high vehicle 11.78 points, from the other vehicle that showed 14.70 points. Significant differences between the three groups did not show (P=.267). Men did not use a seat belt significantly compared to women(P=.007). Vehicle type and weather, this was no correlation with whether or not use the seat belt(P=.755, P=.793). But showed a tendency to smaller size vehicles drivers do not use a seat belt, the weather could see a little more inclined to use a seat belt rather than a sunny day. Finally, in rollover accidents as in other types of accident it was confirmed that the seat belt has a great influence on the damage.