• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.437-438
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• 2019

본 논문에서는 ROS(Robot Operating System)기반으로한 로봇(Robot)에 레이저 거리 센서(LiDAR)를 설치하여 SLAM(Simultaneous Localization and Mapping : 동시적 위치 추적 지도 작성)기법으로 맵 정보를 습득하고, 저장하여 이를 기반으로 장애물과 건물의 실내 복도 안전하고 정확하게 순찰 할 수 있도록 하였다. 또한, 순찰 로봇(Robot)에 장착된 Raspberry카메라와 OpenCV 영상인식 기술을 이용하여 실시간 영상으로 실내 복도를 순찰하면서 사전에 설정된 특이사항이 있을 시 발견하고 기록하도록 시스템을 개발하였다.

• Journal of odor and indoor environment
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• v.17 no.4
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• pp.303-314
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• 2018

The urban railway system is a convenient public transportation system, as it carries many people without increasing traffic congestion. However, air quality in urban railway environments is worse than ambient air quality due to the internal location of the source of air pollutants and the isolated space. In this paper, characteristics of particulate matter (PM) pollution in urban railway environments are described from the perspective of diurnal variation, chemical composition and source apportionment of PM. PM concentrations in concourse, platform, passenger cabin, and tunnel are summarized through an analysis of 34 journal articles published in Korea and overseas. This information will be helpful in developing effective policies to reduce PM pollution in urban railway environments.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.711-711
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• 2006

• Proceedings of the SAREK Conference
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• 2005.06a
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• pp.14-14
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• 2005

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.137-138
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• 2002

입자상 물질은 자연적 또는 인위적인 오염원에 의해 직접 대기로 배출되거나 가스상 물질의 전환 과정을 통해 생성된다. 서울을 비롯한 우리나라 시정(visibility)은 맡은 부분이 가스상 물질의 전환을 통해 생성된 미세 입자에 영향을 받고 있기 때문에 미세 입자의 생성(formation)과 성장(growth) 변화를 연구하는 것은 시정(visibility)의 원인을 밝히는 중요한 과정이라고 할 수 있다. (중략)

• The Science & Technology
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• v.32 no.9 s.364
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• pp.30-31
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• 1999

새로운 21세기에는 위락산업이 유명한 성장산업으로 떠오르게 된다. 한여름에도 활강을 즐길 수 있는 실내스키돔이 세워지고 원통모양의 '플라이어웨이 돔'에서 우주 비행복으로 갈아입은 뒤 200km의 돌풍을 타고 우주인처럼 유영을 즐길 수도 있게 된다. 2020년경에는 우주호텔이 등장하고 해저캠프촌도 건설된다. 또 아마존강에서 환경친화형 여행도 즐기고 에베레스트 등반 희망자도 줄을 잇게 된다.

• Proceedings of the Korean Fiber Society Conference
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• 1997.10a
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• pp.364-368
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• 1997

The purpose of this Study was to determine thermal sensation and physiological responses for men in summer indoor environment, under various air temperature and relative humidity, with male university students. Subjective Evaluation, Heart Rate Variability(HRV), Electroencephalogram(EEG) were examined. We found that comfort of people was achieved at 50% R.H., 24C, and the difference of skin temperature was found at the calf area as air temperature changes. At low air temperature and low humidity, heart rate was decreased, but there was no change at brain wave, keeping a-wave.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.932-938
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• 2013

Recently, the Fingerprint, which is one of the methods of indoor localization using WLAN, has been many studied owing to robustness about ranging error by the diffraction and refraction of radio waves. However, in the signal gathering process and comparison operation for the measured signals with the database, this method requires time consumption and computational complexity. In order to compensate for these problems, this paper presents, based on proposed modified database, WLAN indoor localization algorithm using selective operation of collected signal in real time. The proposed algorithm reduces the configuration time and the size of the data in the database through linear interpolation and thresholding according to the signal strength, the localization accuracy, while reducing the computational complexity, is maintained through selective operation of the signals which are measured in real time. The experimental results show that the accuracy of localization is improved to 17.8% and the computational complexity reduced to 46% compared to conventional Fingerprint in the corridor by using proposed algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.11 s.114
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• pp.1058-1064
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• 2006

In this paper, the channel capacity of a specified wireless indoor multiple-input multiple-output(MIMO) channel is estimated by analyzing spatial characteristics of this channel using the three-dimensional ray tracing method, and a technique for deriving an optimized separation of multi-antenna elements is proposed. At first, the ray paths, the path losses, and the time-delay profile are computed using the three-dimensional ray tracing method in an indoor corridor environment, which has the line of sight(LOS) and non-line of sight(NLOS) regions. The ray tracing method is verified by a comparison between the computation results and the measurements which are obtained with dipole antennas, an amplifier and a network analyzer. Then, an MIMO system is positioned in the indoor channel environment and the ray paths and path losses are computed for four antenna-position combinations and various values of the antenna separation to obtain the channel capacity for the MIMO system. An optimum antenna-separation is derived by averaging the channel capacities of 100 receiver positions with four different antenna combinations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.936-942
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• 2019

Autonomous driving of drone indoor must move along a narrow path and overcome other factors such as lighting, topographic characteristics, obstacles. In addition, it is difficult to operate the drone in the hallway because of insufficient texture and the lack of its diversity comparing with the complicated environment. In this paper, we study an autonomous drone navigation using Convolution Neural Network(CNN) in indoor environment. The proposed method receives an image from the front camera of the drone and then steers the drone by predicting the next path based on the image. As a result of a total of 38 autonomous drone navigation tests, it was confirmed that a drone was successfully navigating in the indoor environment by the proposed method without hitting the walls or doors in the hallway.