• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.173-174
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• 2010

산불감시활동에 의한 탐지확률을 높이고, 감시자원의 효율적인 이용을 위해서는 산불 감시 우선지역에 대한 분석이 요구된다. 따라서 산불감시 우선지역을 추출하기 위해 가시권 분석과 산불발생확률 분석을 실시하였으며, 중첩을 통해 가중치를 부여하였다. 가시권 분석은 탐지확률과 관련된 감시자원의 높이, 산불연기높이, 지형의 roughness에 따른 유효가시거리 인자를 다르게 하여 실시하였다. 산불발생확률은 로지스틱 회귀분석모형과 연료, 기상, 지형인자 및 토지피복, 접근성 인자 DB를 이용하여 분석하였다. 개발된 산불감시 우선지역 분석체계는 산불감시자원의 효율성 제고를 위한 기초자료로 활용될 수 있을 것으로 예상되었다.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.04a
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• pp.153-153
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• 2000

최근 선진국들은 신규 워게임모형 개발시 장차전 개념을 반영하기 위하여 미래전자의 주요기능인 C4ISR 및 객체지향 기법을 적용하려고 노력하고 있다. 이러한 워게임 모형들은 현실과 같은 가상환경에서 합동작전을 모의할 수 있으며 전략, 작전 및 전술 수준을 모두 고려할 수 있고 지상전, 공중전, 해상전, 미사일전, 정보전 등 현대 전투개념을 모두 반영할 수 있도록 초대형 시뮬레이션 시스템으로 발전되고 있다. 본 고에서는 C4I 기능통합 및 연동화 모의 논리중에서 전략기동, 전술기동, 교전평가, 전략수송, 표적탐색, 미사일 판정을 위한 모의 기법과 초대형 시뮬레이션 시스템의 자료/명령 전달 구조 및 하드웨어/소프트웨어 사양, 구성 모듈등을 분석한다. 특히 현재 미 합참에서 개발중인 JWARS모형의 주요 객체들인 전투공간개체(BSE: Battle Space Entity), 아크-노드 네트워크, 화력 집중점(FCPs: Fire Concentration Points) 등을 살펴보고 현대전의 가장 큰 특징인 C4ISR/(Command, Control, Communication, Computer, Intelligence, Surveillance, Reconnaissance) 분야에서 표적탐지, 통신, 정보 모의 기법을 분석함으로써, 향후 한국적 여건에 적합한 분석모형 개발 방향을 제시하고자 한다.

• Korean Journal of Environmental Biology
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• v.40 no.3
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• pp.335-340
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• 2022

After detection of red imported fire ant (Solenopsis invicta) at Gamman port in Busan in September of 2017, Animal and Plant Quarantine Agency has surveilled invasive ants in the area with a high invasion risk of ants. However, existing surveillance traps have several limitations such as captured ants could escape easily or it is very hard to set up the trap on a hard ground like concrete or asphalt. To solve these problems, we developed a new trap using multiple narrow tubes to attract ants to the inside of the trap and make it hard for ants to escape. The new trap can be easily set up under various conditions. The new trap has more than four times ant capturing efficacy compared to conventional pitfall traps. Our results confirmed that the new trap could prevent captured ants from escaping. We hope that this newly developed trap would contribute to the prevention of invasive ants.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.52-57
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• 2013

This paper describes the color comparison analysis of flame in each standard color model in order to propose the optimal color model for image processing based flame detection algorithm. Histogram intersection values were used to analyze the separation characteristics between color of flame and color of non-flame in each standard color model which are RGB, YCbCr, CIE Lab, HSV. Histogram intersection value in each color model and components is evaluated for objective comparison. The analyzed result shows that YCbCr color model is the most suitable for flame detection by average HI value of 0.0575. Among the 12 components of standard color models, each Cb, R, Cr component has respectively HI value of 0.0433, 0.0526, 0.0567 and they have shown the best flame separation characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.214-220
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• 2021

SUGVs (Small Unmanned Ground Vehicles) are being used to conduct dangerous missions, such as EOD (explosive ordinance disposal), counter-terrorism operations, fire extinguishing and fire-fighting reconnaissance, reconnaissance of disaster areas, and surveillance of contact areas. Technology leading countries, the United States, United Kingdom, France, Germany, and Israel, have developed and operated various SUGVs for use in the military and civilian fields. The developed system was upgraded further based on additional requirements associated with data collected during the actual operation. The development trends of technology leading countries are an important indicator for the future development of SUGVs. In this study, the development trends and missions of SUGVs operating in the technology leading countries were analyzed. Based on the development trends of SUGVs in these countries, this paper discusses the features and design characteristics needed for the development of SUGVs in future military and civilian domains.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.901-920
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• 2015

Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.26-31
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• 2014

In this paper, we present performance analysis of video smoke detection based on BPN-Network that is using multi-smoke feature, and Neural Network. Conventional smoke detection method consist of simple or mixed functions using color, temporal, spatial characteristics. However, most of all, they don't consider the early fire conditions. In this paper, we analysis the smoke color and motion characteristics, and revised distinguish the candidate smoke region. Smoke diffusion, transparency and shape features are used for detection stage. Then it apply the BPN-Network (Back-Propagation Neural Network). The simulation results showed 91.31% accuracy and 2.62% of false detection rate.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.388-395
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• 2014

Nowadays unmanned ground systems are used in supporting of surveillance and explosive ordnance disposal. Also, we expect that will be used to remarkably enhance combat capability through network-based cooperative operations with other combat systems. In order to effectively develop those unmanned systems, we needs a systematic method to analyze combat effectiveness and validate required operation capabilities. In this paper, we propose a practical approach to simulate remote-operated unmanned ground systems by using OneSAF, an US-Army simulation framework. First of all, we design a simulation model of unmanned system by integrating with core components for wireless communications and remote control of mobility and fire. Next, we extend OneSAF functionality to create communication links that connects a remote controller with an unmanned vehicle and define a simulated behavior to operate unmanned vehicles via the communication links. Finally, we demonstrate the feasibility of the proposed model within OneSAF and summarize system effectiveness analysis results.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.233-240
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• 2024

In this study, we introduce a system for real-time monitoring of field conditions within an industrial complex using a 5G network UAV (: Unmanned Aerial Vehicle). When a monitoring event occurs in a sensor mounted on a UAV (detection of fire, harmful gas, or industrial disaster type human accident), key information from the sensor is transmitted to the UAS (: Unmanned Aerial System) application server. As a result of this information transmission and processing, managers or operators of the Industrial Complex Corporation were able to secure legal basis data for fatal accidents, fires, and detection of harmful gases at sites within the Industrial Complex Corporation through trigger processing for each accident risk situation.