• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.31-41
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• 2019

A fog screen consists of tiny water drops and the viewers see the image transmitted through the fog screen. In contrast to ordinary screens, the viewers can see the actors passing through the image on the fog screen on stage. In this paper, we describe methods to build a top-down fog screen where fog particles generated in top space fall by gravity forming a flat vertical screen. We use a fog generation technique in which fog particles come out of the water surface when ultrasound vibrators immersed in water tank vibrate. We describe how fog particles form a flat screen while coming out of the fog passage tunnel, by generating guiding winds beside the fog screen. This technique utilizes the principle that fog particles are generated on the surface of a water tank by an ultrasonic vibrator placed in a water tank. The technique of forming a guiding wind on both sides of the passage exit where the fog comes out and the design and manufacturing method of the fog screen generating device are described so that the generated fog group can maintain one plane.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.563-564
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• 2018

최근 차량 네트워크에서 포그 컴퓨팅 기능을 적용하는 새로운 연구가 진행 중이다. 특히, 최근 개발 중인 차량 포그 컴퓨팅 기술은 교통 정보를 실시간으로 수집하여 빠른 처리가 가능하며 이를 장법을 통해 안정된 차량 및 교통 서비스를 제공할 수 있다. 이런 차량 포그 컴퓨팅 기술은 교통 정보 수집, 운전 정보 제공, 스마트 교통 통제 및 도로 안전 메시지 등의 정보를 차량에 빠르게 전달할 수 있다. 본 논문에서는 차량 포그 컴퓨팅 기술을 리뷰하고 교차로 환경에서 차량 포그 컴퓨팅 기반 안전 메시지 전달을 위한 교통 시스템을 제안한다. 특히, 제안하는 기법은 대기 시간에 민감한 안전 메시지를 빠르게 전송할 수 있는 장점을 가지고 있다.

• Smart Media Journal
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• v.8 no.1
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• pp.35-42
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• 2019

With IoT device technology developments, such devices now can perceive the surrounding environment and operate upon the condition, but a method for efficiently processing an enormous amount of IoT device data is required. The existing cloud computing has a transmission delay problem due to load and distance. Fog Computing, an environment to control IoT devices, therefore, emerged to solve this problem. In Fog Computing, IoT devices are located close to each other to solve the shortcomings of the cloud system. While many earlier studies on Fog Computing for IoT mainly focus on its structure and framework, we would like to propose an integrated Fog Computing platform that monitors, analyzes, and controls IoT devices.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.250-255
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• 2020

For the resolution of the latency problem of the cloud center-based cloud computing, fog computing was proposed that allows end devices to offload computations to nearby fog nodes. In the fog computing, virtualized service images are placed on fog nodes and, if service images are placed close to end devices, the duplicate service image placement problem may occur. Therefore, in this paper, we propose a service image placement mechanism based on the logical fog network that reduces duplicate service images by considering the pattern of collected service requests. For the performance evaluation of the proposed mechanism, through simulations, we compare ours with the on-demand mechanism placing a service image upon the receipt of a service request. We consider the performance factors like the number of service images, the number of non-accommodated service requests, and the network cost.

• Journal of Bio-Environment Control
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• v.20 no.1
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• pp.1-7
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• 2011

The objective of the present study is to identify the applicability of a low pressure fogging system for cooling commercial tomato greenhouse. In particular, the cooling system in this experiment utilizes low pressure spray nozzles which were developed in Korea recently. The experimental result that the temperature in fog-cooled greenhouse was lower than the non-cooled greenhouse showed the cooling effect by the low pressure fogging system. But because the relative humidity in fog-cooled greenhouse was comparatively low, the satisfactory cooling effect could be acquired by narrowing the space of fog nozzles and extending fogging time to supply more fog spray quantity. The variation of temperature distribution in fog-cooled greenhouse along timelag was insignificant during short time, but that was great during long period of day. This result showed the variation of temperature along timelag was slight by fog cooling but great by other factors like radiation, ventilation, air flow, etc. The advanced operation technology of fog system was required to reduce the variation of temperature along time lag. We plan to suggest the advanced installation and operation technology of low pressure fogging system for cooling commercial tomato greenhouse by further experiments in near future.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.265-276
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• 2020

This study was conducted to provide a basis for raising farm income by increasing the yield and extending the cultivation period by creating an environment where crops can be cultivated normally during high temperatures in summer. The maximum cooling load of the multi-span greenhouse with a floor area of 504 ㎡ was found to be 462,609 W, and keeping the greenhouse under 32℃ without shading the greenhouse at a high temperature, it was necessary to fog spray 471.6 L of water per hour. The automatic fog cooling control device was developed to effectively control the fog device, the flow fan, and the light blocking device constituting the fog cooling system. The fog cooling system showed that the temperature of the greenhouse could be lowered by 6℃ than the outside temperature. The relative humidity of the fog-cooled greenhouse was 40-80% during the day, about 20% higher than that of the control greenhouse, and this increase in relative humidity contributed to the growth of cucumbers. The relative humidity of the fog cooling greenhouse during the day was 40-80%, which was about 20% higher than that of the control greenhouse, and this increase in relative humidity contributed to the growth of cucumbers. The yield of cucumbers in the fog-cooled greenhouse was 1.8 times higher in the single-span greenhouse and two times higher in the multi-span greenhouse compared to the control greenhouse.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.89-92
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• 2020

According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.271-277
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• 2017

In the image processing, foreground image extraction is mainly applied to recognize a moving object or an object. In the game, the objects included in the foreground image can be mainly characters, non player characters, items, and the like. These objects can be the player's primary concern with objects that are the target of players' movement, attack, defense, and collection. In this background, this research is a study to extract players' interest areas. To this end, first, the foreground image is extracted. Second, the extracted foreground image is accumulated for a certain period of time, and the image is displayed as a result image. The accumulated foreground image according to the play time helps to know the location and frequency of screen appearance of game objects. This study can help players design their interest areas and design an efficient UX/UI.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.60-71
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• 2019

As IoT systems such as smart farms and smart cities become popular, a large amount of data collected from many sensor nodes is sent to a server in the Internet, which causes network traffic explosion, delay in delivery, and increase of server's workload. To solve these problems, the concept of fog computing has been proposed to store data between IoT systems and servers. In this study, we implemented a software platform of the fog node and applied it to the prototype smart farm system in order to check whether the problems listed above can be solved when using the fog node. When the fog node is used, the time taken to control an IoT device is lower than the response time of the existing IoT device-server case. We confirmed that it can also solve the problem of the Internet traffic explosion and the workload increase in the server. We also showed that the intelligent control of IoT system is feasible by having the data visualization in the server and real time remote control, emergency notification in the fog node as well as data storage which is the basic capability of the fog node.

• Journal of Bio-Environment Control
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• v.24 no.3
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• pp.147-152
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• 2015

In order to develop the cooling load estimation method in the greenhouse, the cooling load calculation formula based on the heat balance method was constructed and verified by the actual cooling load measured in the fog cooling greenhouse. To examine the ventilation heat transfer in the cooling load calculation formula, we measured ventilation rates in the experimental greenhouse which a cooling system was not operated. The ventilation heat transfer by a heat balance method showed a relatively good agreement. Evaporation efficiencies of the two-fluid fogging system were a range of 0.3 to 0.94, average 0.67, and it showed that they increased as the ventilation rate increased. We measured thermal environments in a fog cooling greenhouse, and calculated cooling load by heat balance equation. Also we calculated evaporative cooling energy by measuring the sprayed amount in the fogging system. And by comparing those two results, we could verify that the calculated and the measured cooling load showed a relatively similar trend. When the cooling load was low, the measured value was slightly larger than calculated, when the cooling load was high, it has been found to be smaller than calculated. In designing the greenhouse cooling system, the capacity of cooling equipment is determined by the maximum cooling load. We have to consider the safety factor when installed capacity is estimated, so a cooling load calculation method presented in this study could be applied to the greenhouse environmental design.