• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.107-118
• /
• 2021

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2001.11a
• /
• pp.321-322
• /
• 2001

대기중 과산화수소($H_2O$$_2$)는 기상과 액상에서 peroxy radicals 간의 결합 (HO$_2$ㆍ+ HO$_2$ㆍ $\longrightarrow$$H_2O$$_2$+O$_2$)에 의해 생성된다. 만약 수소 원자 하나가 organic group으로 치환되면 organic peroxides가 생성된다(Calvert et al., 1985). 이러한 과산화수소($H_2O$$_2$)와 methylhydroperoxide(MHP, $CH_3$COOH), hydroxymethylhydroperocide(HMHP, HOC$H_2O$OH)등의 organic peroxides는 대기 중에서 주요 산화제로 작용한다. 이들 peroxide 물질들은 pH 5 이하의 aqueous phase (cloud, fog and rain water)에서 sulphuric acid (HSO$_4$$^{2-}$ ) 형성에 중요한 역할을 한다(Calvert et al., 1985). (중략)

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.150-152
• /
• 2022

F2C(Fog-to-Cloud) 환경에서 클라우드와 포그는 긴밀하게 협업하여, 동적으로 작용하며 서비스를 제공할 수 있어야 한다. 이에 본 논문에서는 기존 클라우드/서버 컴퓨팅에서 클라우드 서버 중심의 단방향 서비스 이미지 배포대신에 레지스트리를 이용하여 클라우드, 포그, 그리고 에지까지 서비스 이미지를 배포 가능하게 하여, 동적인 서비스 상호운용이 가능한 시스템을 제안하였다. 또한, 클라우드, 포그에 레지스트리 이미지를 설치하고, 서비스 이미지 등록을 통해 서비스 배포, 실행되는 시스템을 구현하였다.

• Journal of Korean Society of Transportation
• /
• v.28 no.1
• /
• pp.157-163
• /
• 2010

It is well known that weather conditions are closely related with the number and severity of traffic accidents. At present, installation of safety countermeasures including systems is common approach to reduce the damage of traffic accidents at expressways. In this study, the differences of causation factors to influence traffic accidents considering road alignment characteristics and weather conditions. In order to identify the relationship between road and weather conditions, discriminant analysis has been performed with 500 traffic accident data at expressways. Weather conditions are divided into several categories such as snow, sunny, rain, fog, and cloud. Also, road conditions such as types of pavements, grades are analyzed. As the results, major impacting road conditions to traffic accidents are concrete pavement and 3% or more down grades. In these road conditions, visible distance will be reduced and actual braking distances will be increased. This study shows that the expressway sections under concrete pavement and down grades should be more cautious than other sections. It also shows that fog condition is the mose dangerous situation in terms of traffic accidents.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.8
• /
• pp.985-992
• /
• 2020

Edge computing is a technology that can prepare for a new era of cloud computing. Edge computing is not a remote data center where data is processed and computed, but low-latency/high-speed computing is realized by adding computing power and data processing power to the edge side close to an access point such as a terminal device or a gateway. It is possible. The types of edge computing include mobile edge computing, fog computing, and cloudlet computing. In this article, we describes existing open source platforms for implementing edge computing nodes. By presenting and comparing the structure, features of open source edge platforms, it is possible to acquire knowledge required to select the best edge platform for industrial engineers who want to build an edge node using an actual open source edge computing platform.

• Journal of the Korean earth science society
• /
• v.27 no.4
• /
• pp.450-463
• /
• 2006

Seasonal threshold values for fog detection over the ten airport areas within the Korean Peninsula have been derived from the data of polar-orbit Aqua/Terra MODIS and geostationary GOES-9 during a two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following four parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul metropolitan area: brightness temperature at $3.7{\mu}m$, the temperature at $11{\mu}m,\;the\;T_{3.7-11}$ for day and night, and the $R_{0.65}$ for daytime. The parameters show significant correlations (r<0.5) in spatial distribution between the two kinds of satellites. The discrepancy between their infrared thresholds is mainly due to the disagreement in their spatial resolutions and spectral bands, particularly at $3.7{\mu}m$. Fog detection from GOES-9 over the nine airport areas except the Cheongju airport has revealed accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification. The accuracy decreases in foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog. The sensitivity of radiance and reflectance with wavelength has been analyzed in numerical experiments with respect to various meteorological conditions to investigate optical characteristics of the three channels.

• Atmosphere
• /
• v.26 no.2
• /
• pp.243-256
• /
• 2016

Total number concentration of aerosols larger than 10 nm ($N_{CN10}$), 3 nm ($N_{CN3}$), and cloud condensation nuclei ($N_{CCN}$) were measured during four different ship cruises over the Yellow Sea. Average values of $N_{CN10}$ and $N_{CCN}$ at 0.6% supersaturation were 6914 and $3353cm^{-3}$, respectively, and the minimum value of $N_{CN10}$ was $2000cm^{-3}$, suggesting significant anthropogenic influence even at relatively clean marine environment. Although $N_{CN10}$ and $N_{CN3}$ increased near the coast due to anthropogenic influence, $N_{CCN}$ was relatively constant and therefore $N_{CCN}/N_{CN10}$ ratio tended to decrease, suggesting that coastal aerosols were relatively less hygroscopic. In general $N_{CN10}$, $N_{CN3}$, and $N_{CCN}$ during the cruises seemed to be significantly influenced by wet scavenging effects (e.g. fog) and boundary layer height variation. Only one new particle formation (NPF) event was observed during the measurement period. Interestingly, the NPF event occurred during a dust storm event and spatial scale of the NPF event was estimated to be larger than 100 km. These results demonstrate that aerosol and CCN concentration over the Yellow Sea can vary due to various different factors.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.9
• /
• pp.3712-3729
• /
• 2020

Smoke detection is helpful for early fire detection. With its large coverage area and low cost, vision-based smoke detection technology is the main research direction of outdoor smoke detection. We propose a two-stage smoke detection method combined with block Deep Normalization and Convolutional Neural Network (DNCNN) and visual change image. In the first stage, each suspected smoke region is detected from each frame of the images by using block DNCNN. According to the physical characteristics of smoke diffusion, a concept of visual change image is put forward in this paper, which is constructed by the video motion change state of the suspected smoke regions, and can describe the physical diffusion characteristics of smoke in the time and space domains. In the second stage, the Support Vector Machine (SVM) classifier is used to classify the Histogram of Oriented Gradients (HOG) features of visual change images of the suspected smoke regions, in this way to reduce the false alarm caused by the smoke-like objects such as cloud and fog. Simulation experiments are carried out on two public datasets of smoke. Results show that the accuracy and recall rate of smoke detection are high, and the false alarm rate is much lower than that of other comparison methods.

• Journal of IKEEE
• /
• v.1 no.1 s.1
• /
• pp.120-137
• /
• 1997

Han's model, which is able to analyze optical communication between earth station and geo-satellite as a function of atmospheric conditions and elevation angles. is presented. In Han's model, atmospheric conditions are roughly classified into six basic types; clear sky, cloud, haze, fog, rain and snow. Data rate satisfying for the BER below $10^{-7}$ is analyzed by Han's model in case of up-link and down-link, respectively. Data rate is more limited by up-link than by down-link because the pointing loss caused by atmosphere on the up-link is greater than the spatial coherence degradation caused by atmosphere on the down-link.

• Korean Journal of Remote Sensing
• /
• v.24 no.1
• /
• pp.79-89
• /
• 2008

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series contaminated by noises resulted from mechanical problems or sensing environmental condition. There is also a high likelihood that during the data acquisition periods the target site corresponding to any given pixel may be covered by fog or cloud, thereby resulting in bad or missing observation. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. A feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. The experimental results of this simulation study show the potentiality of the proposed system to reconstruct the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather. This study provides fundamental information on the elements of the proposed system for right usage in application.