• Smart Structures and Systems
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• v.13 no.6
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• pp.1065-1094
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• 2014

Civil engineers always face the challenge of uncertainty in planning, building, and maintaining infrastructure. These works rely heavily on a variety of surveying and monitoring techniques. Unmanned aerial vehicles (UAVs) are an effective approach to obtain information from an additional view, and potentially bring significant benefits to civil engineering. This paper gives an overview of the state of UAV developments and their possible applications in civil engineering. The paper begins with an introduction to UAV hardware, software, and control methodologies. It also reviews the latest developments in technologies related to UAVs, such as control theories, navigation methods, and image processing. Finally, the paper concludes with a summary of the potential applications of UAV to seismic risk assessment, transportation, disaster response, construction management, surveying and mapping, and flood monitoring and assessment.

• Wind and Structures
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• v.8 no.3
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• pp.163-178
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• 2005

Wind-induced mean and dynamic interference effects of tall buildings are studied in detail by a series of wind tunnel tests in this paper. Interference excitations of several types of upwind structures of different sizes in different upwind terrains are considered. Comprehensive interference characteristics are investigated by artificial neural networks and correlation analysis. Mechanism of the wakes vortex-induced resonance is discussed, too. Measured results show significant correlations exist in the distributions of the interference factors of different configurations and upwind terrains and, therefore, a series of relevant regression equations are proposed to simplify the complexity of the multi-parameter wind induced interference effects between two tall buildings.

• Wind and Structures
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• v.8 no.3
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• pp.147-161
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• 2005

Two identical tall building models with square cross-sections are experimentally studied in a wind tunnel with high-frequency-force-balance (HFFB) technique to investigate the interference effects on wind loads and dynamic responses of the interfered building. Another wind tunnel test, in which the interfered model is an aeroelastic one, is also carried out to further study the interference effects. The results from the two kinds of tests are compared with each other. Then the influences of turbulence in oncoming wind on dynamic interference factors are analyzed. At last the artificial neural networks method is used to deal with the experimental data and the along-wind and across-wind dynamic interference factor $IF_{dx}$ & $IF_{dy}$ contour maps are obtained, which could be used as references for wind load codes of buildings.

• Journal of the Society of Disaster Information
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• v.6 no.2
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• pp.45-65
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• 2010

There has been tighten up the need of seismic retrofit about 31 public facilites since published "Korean Earthquake Damage Prevention Law". Therefore, seismic studies have been developed and enforced the studies. Measuring dynamic stiffness of subsurface materials influence on seismic performance evaluation to build up seismic retrofit. The soil dynamic properties for seismic performance evaluation are N-value from using SPT(standard penetration test), dynamic shear elastic modulus and dynamic deformation modulus using laboratory tests. The most unscientific element in ground dynamic properties involved uncertainties is obviously N-value using SPT. This study shows that effect of N-value included natural and artificial uncertainties to seismic performance evaluation of ground structures is not only approached probabilistic analysis using FOSM method and tornado diagram, but also review how to spread effect of seismic performance evaluation of ground structures.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.281-282
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• 2016

본 논문에서는 증대하고 있는 재난안전사고에 효율적으로 대응할 수 있도록 훈련할 수 있는 시뮬레이터 플랫폼을 제안한다. 최근 재난은 복합적이며, 타 부처 간의 협력이 필요한 대규모 성격을 띠고 발생하는 빈도가 커지고 있는 반면 훈련도구는 각 부처별로 재난유형별 시스템들이 필요에 따라 독립개발 및 운영되고 있기 때문에 다양한 시나리오에 의한 종합적 분석결과를 기반으로 하는 스마트한 재난대응 방안 모색이 어려운 실정이다. 이러한 이유로 본 연구에서는 재난에 대응하는 사람의 다양한 능력을 반영하여 인공지능 기반 하에 훈련 시나리오가 생성될 수 있는 지능형 재난대응훈련 시뮬레이터 개발을 위한 플랫폼을 제안한다. 또한 몰입감을 가지고 가상의 상황 하에서 훈련할 수 있도록 가상현실 기반의 시뮬레이터 플랫폼이 될 수 있도록 제안한다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.202-203
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• 2023

최근 화재 탐지 분야는 불꽃 연기의 특징과 인공지능 인식(Detection) 모델을 활용하여 탐지율을 높이려는 연구가 많이 진행되어 왔다. 기존 화재 탐지 정확도를 높이기 위한 모델 연구 이외에도 불꽃·연기의 특징을 다양한 방법으로 데이터 가공한 학습 데이터셋을 활용하는 연구들이 진행되고 있다. 본 논문에서는 화재 탐지시 불꽃/연기의 오탐지율이 높은 것을 확인하고 오탐지율을 낮추기 위해 화재 상황을 인식하여 분류하는 방법과 데이터셋을 제안한다. 제안한 모델은 동영상을 학습데이터로 활용하여 화재 상황의 특징을 추출하여 분류모델에 적용하였다. 평가는 한국정보화진흥원(NIA)에서 진행하는 화재 데이터셋을 이용하여 Yolov8, Slowfast의 모델 성능을 비교 및 분석하였다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.329-330
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• 2023

인공지능(AI)은 지방자치단체 청사의 물리적 보안 시스템을 개선하는 데 활용될 수 있는 유망한 기술이다. 방대한 데이터를 분석하고 패턴을 식별할 수 있어, 테러나 폭력과 같은 위협을 사전에 예방하는데 도움이 될 수 있다. 또한, 인공지능(AI)은 실시간으로 보안 상황을 모니터링하고 이상 징후를 감지할 수 있어, 보안 인력의 업무 효율성을 향상시키고 비용을 절감하는 데에도 도움이 되기에 인공지능(AI)을 적용한 물리적 보안 시스템 개선방안에 대해 제안하고자 한다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.47-48
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• 2023

보안검색은 항공보안에서 가장 핵심적이고 기본적인 분야이다. 9.11 테러 이후 전 세계적으로 보안검색이 강화되었으나 보안검색단계에서 위해물품을 색출하는 것에는 한계가 따른다. 최근 국내 공항의 경우 언론에 보도된 보안검색 실패사례 외에도 다수의 실패사례가 보고되고 있으며 그에 따른 원인과 대책 방안의 하나를 법규에서 찾아보고자 한다. 본 연구는 현재 시행되고 있는 관련 법규와 선행연구 분석을 통해 얻은 결론으로 보안검색요원의 교육과 법적 지위 등의 제도적 문제점을 착안하고 그에 따른 개선안을 도출하여 제시하고자 한다.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.199-205
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• 2024

Purpose: This study aims to improve the recognition rate of Auto People Counting (APC) in accurately identifying and providing information on remaining evacuees in disaster-vulnerable facilities such as nursing homes to firefighting and other response agencies in the event of a disaster. Methods: In this study, a baseline model was established using CNN (Convolutional Neural Network) models to improve the algorithm for recognizing images of incoming and outgoing individuals through cameras installed in actual disaster-vulnerable facilities operating APC systems. Various algorithms were analyzed, and the top seven candidates were selected. The research was conducted by utilizing transfer learning models to select the optimal algorithm with the best performance. Results: Experiment results confirmed the precision and recall of Densenet201 and Resnet152v2 models, which exhibited the best performance in terms of time and accuracy. It was observed that both models demonstrated 100% accuracy for all labels, with Densenet201 model showing superior performance. Conclusion: The optimal algorithm applicable to APC among various artificial intelligence algorithms was selected. Further research on algorithm analysis and learning is required to accurately identify the incoming and outgoing individuals in disaster-vulnerable facilities in various disaster situations such as emergencies in the future.

• Convergence Security Journal
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• v.23 no.1
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• pp.147-159
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• 2023

Recently, Chat GPT artificial intelligence (AI) is of keen interest to all governments, companies, and military sectors around the world. In the existing era of literacy AI, it has entered an era in which communication with humans is possible with generative AI that creates words, writings, and pictures. Due to the complexity of the current laws and ordinances issued during the recent national crisis in Korea and the ambiguity of the timing of application of laws and ordinances, the golden time of situational measures was often missed. For these reasons, it was not able to respond properly to every major disaster and military conflict with North Korea. Therefore, the purpose of this study was to revise the National Crisis Management Basic Act, which can act as a national tower in the event of a national crisis, and to promote artificial intelligence governance by linking artificial intelligence technology with the civil, government, military, and police.