Journal of the Korea Society of Computer and Information
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v.27
no.8
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pp.77-84
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2022
In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.
This proposes a direction to build and provide an exhibition space based on the metaverse platform so that artists can independently open their own exhibitions in an online environment. Although many artists are produced every year, offline exhibitions are becoming difficult due to not many art galleries, and offline exhibitions are becoming impossible due to Corona, which began at the end of 2019, and online exhibitions are emerging as an alternative. We analyze cases of existing online exhibition methods and visit online exhibition methods such as web, video, and virtual reality and metaverse environment then present a plan for individual exhibitions in consideration of the recent metaverse environment. The proposed metaverse-based personal exhibition method is structured so that artists can construct a space on the metaverse and place their works, and then viewers can freely take a look on it from a remote location. Based on the proposed exhibition direction, the representative metaverse platform was applied to confirm the characteristics and possibilities of exhibition space and composition of works and users' exhibition experience. In the face of the rise of online exhibitions, space can be constructed in the direction the artist pursues in online exhibitions as well as offline exhibitions, but also online exhibitions, and hopes that online exhibitions will become another genre of exhibitions rather than incidental after the end of Covid-19.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.8
no.6
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pp.835-844
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2018
Recently, as the number of smartphone users has been increasing worldwide, various services such as electronic payment, internet use, and financial settlement are being used as a smartphone. In addition, researches for home appliance control and automobile control using smartphone are conducted. As such, smartphone users can enjoy a more convenient life, but by hacking smartphones, tapping texts and conversations on smartphones, tracking location through spy apps, DDoS attacks using smartphones, and malicious apps When a message is received at a specific telephone number when using a micropayment, the corresponding text message is transmitted to a remote server, thereby increasing the risk of leakage of personal information and the like. Therefore, in this paper, we define the risk factors of the smartphone that are caused by the internal and external environmental, physical, contents (apps) of the smartphone through the smartphone that we use in real life, We propose a method to check vulnerability of smartphone security solution such as CC evaluation and the most effective response technique for each risk of smartphone by defining the technique.
Volcanic ash is a fine particle smaller than 2 mm in diameters. It falls after the volcanic eruption and causes various damages to transportation, manufacturing industry and respiration of living things. Therefore diffusion information of volcanic ash is highly significant for preventing the damages from it. It is advantageous to utilize satellites for observing the widely diffusing volcanic ash. In this study volcanic ash diffusion information about two eruptions of Mt. Sakurajima were calculated using the geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) and polar-orbiting satellite, Landsat-8 Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). The direction and velocity of volcanic ash diffusion were analyzed by extracting the volcanic ash pixels from COMS-MI images and the height was retrieved by adjusting the shadow method to Landsat-8 images. In comparison between the results of this study and those of Volcanic Ash Advisories center (VAAC), the volcanic ash tend to diffuse the same direction in both case. However, the diffusion velocity was about four times slower than VAAC information. Moreover, VAAC only provide an ash height while our study produced a variety of height information with respect to ash diffusion. The reason for different results is measured location. In case of VAAC, they produced approximate ash information around volcano crater to rapid response, while we conducted an analysis of the ash diffusion whole area using ash observed images. It is important to measure ash diffusion when large-scale eruption occurs around the Korean peninsula. In this study, it can be used to produce various ash information about the ash diffusion area using different characteristics satellite images.
This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.
This paper reports on the analysis of the location accuracy of a precision image generation system manufactured for CAS 500. The planned launch date of the CAS 500 is 2021, and since it has not yet been launched, the analysis was performed using KOMPSAT-3A satellite images having similar specifications to the CAS 500. In this paper, we have checked the geolocation accuracy of initial sensor model, the model point geolocation accuracy of the precise sensor model, the geolocation accuracy of the precise sensor model using the check point, and the geolocation accuracy of the precise orthoimage using 30 images of the Korean Peninsula. In this study, the target geolocation accuracy is to have an RMSE within 2 pixels when an accurate ground control point is secured. As a result, it was confirmed that the geolocation accuracy of the precision sensor model using the checkpoint was about 1.85 pixels in South Korea and about 2.04 pixels in North Korea, and the geolocation accuracy of the precise orthoimage was about 1.15 m in South Korea and about 3.23 m in North Korea. Overall, it was confirmed that the accuracy of North Korea was low compared to that of South Korea, and this was confirmed to have affected the measured accuracy because the GCP (Ground Control Point) quality of the North Korea images was poor compared to that of South Korea. In addition, it was confirmed that the accuracy of the precision orthoimage was slightly lower than that of precision sensor medel, especially in North Korea. It was judged that this occurred from the error of the DTM (Digital Terrain Model) used for orthogonal correction. In addition to the causes suggested by this paper, additional studies should be conducted on factors that may affect the position accuracy.
Among smart city services, the crime and disaster prevention sector accounted for the highest 24% in 2018. The most important platform for providing real-time situation information is CCTV (Closed-Circuit Television). Therefore, it is essential to create the actual CCTV surveillance coverage to maximize the usability of CCTV. However, the amount of CCTV installed in Korea exceeds one million units, including those operated by the local government, and manual identification of CCTV coverage is a time-consuming and inefficient process. This study proposed a method to efficiently construct CCTV's actual surveillance coverage and reduce the time required for the decision-maker to manage the situation. For this purpose, first, the exterior orientation parameters and focal lengths of the pre-installed CCTV cameras, which are difficult to access, were calculated using the point cloud data of the MMS (Mobile Mapping System), and the FOV (Field of View) was calculated accordingly. Second, using the FOV result calculated in the first step, CCTV's actual surveillance coverage area was constructed with 1 m, 2 m, 3 m, 5 m, and 10 m grid interval considering the occluded regions caused by the buildings. As a result of applying our approach to 5 CCTV images located in Uljin-gun, Gyeongsnagbuk-do the average re-projection error was about 9.31 pixels. The coordinate difference between calculated CCTV and location obtained from MMS was about 1.688 m on average. When the grid length was 3 m, the surveillance coverage calculated through our research matched the actual surveillance obtained from visual inspection with a minimum of 70.21% to a maximum of 93.82%.
An area's topography refers to the shape of the earth's surface, described by its elevation, slope, and aspect, among other features. The topographical conditions determine energy flowsthat move water and energy from higher to lower elevations, such as how much solar energy will be received and how much wind or rain will affect it. Another common factor, the topographic wetness index (TWI), is a calculation in digital elevation models of the tendency to accumulate water per slope and unit area, and is one of the most widely referenced hydrologic topographic factors, which helps explain the location of forest vegetation. Analyses of topographical factors can be calculated using a geographic information system (GIS) program based on digital elevation model (DEM) data. Recently, a large number of free open source software (FOSS) GIS programs are available and developed for researchers, industries, and governments. FOSS GIS programs provide opportunitiesfor flexible algorithms customized forspecific user needs. The majority of biodiversity in island areas exists at about 20% higher elevations than in land ecosystems, playing an important role in ecological processes and therefore of high ecological value. However, island areas are vulnerable to disturbances and damage, such as through climate change, environmental pollution, development, and human intervention, and lacks systematic investigation due to geographical limitations (e.g. remoteness; difficulty to access). More than 4,000 of Korea's islands are within a few hours of its coast, and 88% are uninhabited, with 52% of them forested. The forest ecosystems of islands have fewer encounters with human interaction than on land, and therefore most of the topographical conditions are formed naturally and affected more directly by weather conditions or the environment. Therefore, the analysis of forest topography in island areas can be done more precisely than on its land counterparts, and therefore has become a major focus of attention in Korea. This study is focused on calculating the performance of different topographical factors using FOSS GIS programs. The test area is the island forests in Korea's south and the DEM of the target area was processed with GRASS GIS and SAGA GIS. The final slopes and TWI maps were produced as comparisons of the differences between topographic factor calculations of each respective FOSS GIS program. Finally, the merits of each FOSS GIS program used to calculate the topographic factors is discussed.
Park, GwangSeob;Kim, Hyun-Cheol;Lee, Taehee;Son, Young Baek
Korean Journal of Remote Sensing
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v.34
no.6_2
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pp.1299-1310
/
2018
In this study, we analyzed distribution and movement trends using in-situ observations and particle tracking methods to understand the movement of the drift ice in the Arctic Ocean. The in-situ movement data of the drift ice in the Arctic Ocean used ITP (Ice-Tethered Profiler) provided by NOAA (National Oceanic and Atmospheric Administration) from 2009 to 2018, which was analyzed with the location and speed for each year. Particle tracking simulates the movement of the drift ice using daily current and wind data provided by HYCOM (Hybrid Coordinate Ocean Model) and ECMWF (European Centre for Medium-Range Weather Forecasts, 2009-2017). In order to simulate the movement of the drift ice throughout the Arctic Ocean, ITP data, a field observation data, were used as input to calculate the relationship between the current and wind and follow up the Lagrangian particle tracking. Particle tracking simulations were conducted with two experiments taking into account the effects of current and the combined effects of current and wind, most of which were reproduced in the same way as in-situ observations, given the effects of currents and winds. The movement of the drift ice in the Arctic Ocean was reproduced using a wind-imposed equation, which analyzed the movement of the drift ice in a particular year. In 2010, the Arctic Ocean Index (AOI) was a negative year, with particles clearly moving along the Beaufort Gyre, resulting in relatively large movements in Beaufort Sea. On the other hand, in 2017 AOI was a positive year, with most particles not affected by Gyre, resulting in relatively low speed and distance. Around the pole, the speed of the drift ice is lower in 2017 than 2010. From seasonal characteristics in 2010 and 2017, the movement of the drift ice increase in winter 2010 (0.22 m/s) and decrease to spring 2010 (0.16 m/s). In the case of 2017, the movement is increased in summer (0.22 m/s) and decreased to spring time (0.13 m/s). As a result, the particle tracking method will be appropriate to understand long-term drift ice movement trends by linking them with satellite data in place of limited field observations.
Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.
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