• Journal of Industrial Technology
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• v.20 no.B
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• pp.183-188
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• 2000

In this paper, we present a development of automatic fog water collector that operates during fog events. This collector consists of fraction collectors, a wind hall and a fog sensor. When a fog event is begin, then the fog sensor would judge whether it is a fog or not. If a fog is detected, the fog would be gathered by air suction fans, At the same time, the wind direction, the wind velocity, the atmospheric temperature and pressure would be measured and record simultaneously. We are also developing a wireless communication system for the remote control and data analysis to collect, store and process data collected in the automatic fog water collector.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.385-385
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• 2000

In this paper, We presents the development of an automatic fog water collector that operates during fog events. This collector consists of fraction collectors, a wind hall and a fog sensor. If a fog event occurred, then the fog sensor wouldjudge whether it is a fog or not. If the fog sensor judged the fug, then the fog in the air would be rucked by suction fans. At the same time, the wind direction, the wind velocity, the atmospheric temperature and the atmospheric pressure would be measured and recorded. We are also developing a wireless communication system for the remote control and the remote data analysis in order to collect, store and process the data collected in the automatic fog water collector.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.23-26
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• 2023

In the past, in observing the sea fog on the major sea route and providing real-time information for the safe operation of ships, a visibility sensor or a fog detector with similar operating principles was installed to observe local fog near the place where it was installed. However, it was somewhat unreasonable to immediately provide sea fog observation information to ships and users because the reliability of real-time observation information was somewhat low due to pollution caused by dust, salt, and pollen, or malfunctions of detection sensors by organisms such as spider webs. From 2019 to 2022, the Korea Meteorological Administration and the Ministry of Oceans and Fisheries collaborated to build a more reliable real-time image-based sea fog observation system in 100 regions of the Lighthouse on major sea routes across the country to collect reliable sea fog observation information every 10 minutes and perform real-time public service(webpage).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.385-392
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• 2013

A key element of the fog warning system to prevent large traffic accidents is a visibility measurement device. Recently, the need for it that is similar to the human visual sense and cheap and accurate than expensive fog sensors is increasing. In this paper, we present the performance evaluation and the economic analysis of the Road Visibility Measurement System (RVMS), which is developed for measuring the road visibility through a CCTV camera. For experiments, we have installed a CCTV camera, a fog sensor, and visibility signs at the Yeo-ju Test Road on the Central Inland Expressway. We evaluated the measurements from RVMS and the fog sensor based on observations. The result shows RVMS outperforms the fog sensor with respect to measurement stability and correctness. We also show RVMS has higher economic feasibility and various applications. RVMS can prevent the traffic accidents caused by severe fog and enhance the process of the wide-area visibility information system significantly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.

• Korean Journal of Optics and Photonics
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• v.13 no.5
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• pp.377-383
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• 2002

An all-digital closed-loop (ADCL) signal processor for an open-loop FOG was developed to replace the analog circuitry of a Digital Phase Tracking (DPT) signal processor with new digital circuitry. When the ADCL signal processor without a stabilizer for fiber phase modulator (FPM) was attached to the FOG, temperature drift of FOG was about 0.26$\mu$rad/$^{\circ}C$, which makes the FOG unusable in medium or higher-grade applications. This drift was due to variations of phase modulation amplitude and phase delay of the FPM. The stabilizer controls its phase modulation amplitude and phase delay by regulating the ratio of harmonics of the FOG output. Thus, the stabilizer reduces the drift of the FOG to negligible.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.3
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• pp.265-268
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• 2011

In this paper, we designed and fabricated that fog alarm equipment detected to crew in maritime fog. Developed fog alarm equipment was combined sensor and a transmitter-receiver module using emitting device unit and receiver photoelectric element infrared LED using only the receive sensitivity was low, miniaturization. Experiment of the fabricated device had a standard that was humidity 70%, the fabricated one generating artificial-fog within visibility 1km. When humidity is over 70%, the fabricated one generates alarming sounds for a warning. When developed device apply to vessel will be able to respond quickly, according to dense fog in the accident.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.18-23
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• 2017

In 2015, 100-car pileup was happened because the safe distance from the car in front did not be kept due to much fog at YoungJong Bridge in South Korea. This is why the road would be benumbed with cold weather in winter. For this weather condition, if the driver of the car in front changed the lane suddenly or suddenly slammed on the brake in fog or freezing area, the braking distance of the real car has to be 2 or 3 times longer than usual. In this paper, we have simulated the function that warns and notice about the fog area or the freezing one in the road using Arduino sensors and Beacon. Also we propose the intelligent traffic system to protect the accidents in winter.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.