• Journal of Convergence for Information Technology
• /
• v.7 no.6
• /
• pp.201-207
• /
• 2017

Failure of the power apparatus causes many inconveniences and problems due to power outage in all places using power such as industry and home. The main causes of faults in the Power Apparatus are aging, natural disasters such as typhoons and earthquakes, and animals. At present, the long high temperature status is monitored only by the assumption that a fault occurs when the temperature of the power apparatus becomes higher. Therefore, it is difficult to cope with the failure of the power apparatus at the right time. In this paper, we propose a power apparatus monitoring system as an efficient countermeasure against general faults except for faults caused by sudden natural disasters. The proposed monitoring system monitors the power apparatus in real time by attaching a thermal sensor, collects the monitored data, and predicts the failure using the accumulated information through learning using the artificial neural network. Through the learning and experimentation of artificial neural network, it is shown that the proposed method is efficient.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.20 no.4
• /
• pp.1-8
• /
• 2016

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.11a
• /
• pp.556-559
• /
• 2020

최근 태풍, 지진, 산불, 산사태, 전쟁 등 다양한 재난 상황으로 인한 인명피해와 자금 손실이 꾸준히 발생하고 있고 현재 이를 예방하고 복구하기 위해 많은 인력과 자금이 소요되고 있는 실정이다. 이러한 여러 재난 상황을 미리 감시하고 재난 발생의 빠른 인지 및 대처를 위해 본 논문에서는 인공지능 기반의 재난 드론 시스템을 설계 및 개발하였다. 본 연구에서는 사람이 감시하기 힘든 지역에 여러 대의 재난 드론을 이용하며 딥러닝 기반의 최단 경로 알고리즘을 적용해 각각의 드론이 최적의 경로로 효율적 탐색을 실시한다. 또한 드론의 근본적 문제인 배터리 용량 부족에 대한 문제점을 해결하기 위해 Ant Colony Optimization (ACO) 기술을 이용하여 각 드론의 최적 경로를 결정하게 된다. 제안한 시스템 구현을 위해 여러 재난 상황 중 산불 상황에 적용하였으며 전송된 데이터를 기반으로 산불지도를 만들고, 빔프로젝터를 탑재한 드론이 출동한 소방관에게 산불지도를 시각적으로 보여주었다. 제안한 시스템에서는 여러 대의 드론이 최적 경로 탐색 및 객체인식을 동시에 수행함으로써 빠른 시간 내에 재난 상황을 인지할 수 있다. 본 연구를 바탕으로 재난 드론 인프라를 구축하고 조난자 탐색(바다, 산, 밀림), 드론을 이용한 자체적인 화재진압, 방범 드론 등에 활용할 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.06a
• /
• pp.212-215
• /
• 2019

지난 4월4일 고성 산불로 사망자 2명과 부상자 1명, 가옥 500여 채, 삼림 1757ha가 불에 탔다. 강원 산불에 이어 영덕지진 등에서 늑장대응을 보여준 재난방송시스템에는 많은 국민들에게 실망감을 안겨주었다. 재난방송 주관방송사인 KBS는 물론, MBC, SBS의 경우도 재난방송시스템에 관련 된 측면에서 본다면 아직 이웃나라 인 일본에 비해서는 매우 열악한 형편이다. 그럼에도 불구하고 점점 대형화, 다발화 하는 재난발생에 대응하기 위해서는 국가적인 차원에서도 특단의 조치가 필요하다. 미국의 경우는 차세대 재난정보 전달체계인 IPAWS(Integrated Public Alert and Warning System)를 개발해 지상파뿐만 아니라, 케이블TV, SNS 등 다양한 매체를 통해 재난정보를 신속하게 전달하고 있다. 일본도 이와 유사한 재난경보전달시스템인 J-Alert를 개발해 2020년까지는 '재난 약자 제로(Zero)시대'를 목표로 구현하고 있다. 우리나라는 지난 아현동 KT 화재사건에서도 경험했듯이 통신이 먹통이 되는 통신블랙아웃도 경험했다. 따라서 대형재난발생 시는 신속한 재난경보전달시스템이 재난피해를 줄일 수 있는 가장 중요한 생명줄이 될 수 있다. 미국이나 일본의 경우는 재난방송전달시스템을 관련법령으로 제도화 하고 있다. 특히, 일본에는 재난에 관한 모법이라고 할 수 있는 (1)"재해대책기본법"이 있는데, 이는 재해로부터 국토, 국민의 생명과 재산을 보호하기 위한 기본법으로 규정되어 있다. 그 밖에도 (2)방송법 (3)대규모지진대책특별 조치법 (4)국민보호법 (5)소방조직법 (6)수해방지법 등으로 규정하고 있다. 과거 일본도 우리나라와 같이 대형 산불이 잦았으나 요즘은 소형 산불만 발생하는 추세다. 이는 NHK가 보유한 700여 대의 로봇카메라와 전 국토를 샅샅이 감시하는 CCTV 덕택이다. 또한, NHK 보도국의 '기상 재해센터'는 재난에 대비해 40여 명의 전문 인력이 24시간 대응체제를 갖추고 있다. 나아가 NHK는 전국 12개의 거점지역에 헬리콥터 15대를 배치하여 신속하게 취재하고 있다. 이 뿐만 아니라, 46개의 지역방송국을 7개의 거점방송국으로 분할하여, 거점방송국마다 40여명의 카메라맨을 상주시켜 언제든지 재난을 취재할 수 있도록 하고 있다. 세계 각국에서 사용하고 있는 방송 주파수는 공공재(公共材)다. 국제전기통신연합(ITU : International Telecommunication Union)으로부터 주파수를 할당받아 사용하고 있기 때문에 주파수에 관한 사용 권한은 각국의 국민 모두에게 있다. 그러나 효과적인 주파수 활용을 전제로 정부가 일정한 자격을 갖춘 방송사업자에게 일시적으로 주파수 사용권을 위임하고 있다. 따라서 일본 정부도 국가적인 위기나 대형 재난발생으로 국민들의 생명과 재산이 위협받고 있을 때에는 공공재인 주파수를 즉시 재난방송으로 사용할 수 있도록 <재해대책기본법 제6조>와 방송법 제108조에 규정하고 있다.

• The Journal of Engineering Geology
• /
• v.19 no.2
• /
• pp.139-144
• /
• 2009

The microseismic monitoring system with wide range of frequency has been operating in real time and it is remotely monitored at indoor and on-site for one year. This system was constructed and established in order to secure the safe and effective operation of the KAERI Underground Research Tunnel(KURT). For one year monitoring work, total 14 events were recorded in the vicinity of the KURT, and the majority of events are regarded as ultramicroseismic earthquake and artificial impacts around the tunnel. The major event is the magnitude 3.4 earthquake which was centered around Gongju city, Chungnam Province. It means that there is no significant evidence of high frequency microseismic event, which is associated with fracture initiation and/or propagation in the rock mass and shotcrete. Three components sensor was applied in order to analyze and define the direction of vibration as well as an epicenter of microseismic origin, and also properly designed and installed in a small borehole. This monitoring system is able to predict the location and timing of fracturing of rock mass and rock fall around an undreground openings as well as analysis on safety of various kinds of engineering structures such as nuclear facilities and other structures.

• The KIPS Transactions:PartD
• /
• v.13D no.6 s.109
• /
• pp.775-788
• /
• 2006

Many disaster monitoring systems are constantly studied to prevent disasters such as environmental pollution, the breaking of a tunnel and a building, flooding, storm earthquake according to the progress of wireless telecommunication, the miniaturization of terminal devices, and the spread of sensor network. A disaster monitoring system can extract information of a remote place, process sensor data with rules to recognize disaster situation, and provide work for preventing disaster. However existing monitoring systems are not enough to predict and prevent disaster, because they can only process current sensor data through utilizing simple aggregation function and operators. In this paper, we design and implement a disaster prevention system to predict near future dangerous area through using outside sensor network and spatial Information. The provided prediction technique considers the change of spatial information over time with current sensor data, and indicates the place that could be dangerous in near future. The system can recognize which place would be dangerous and prepare the disaster prevention. Therefore, damage of disaster and cost of recovery would be reduced. The provided disaster prevention system and prediction technique could be applied to various disaster prevention systems and be utilized for preventing disaster and reducing damages.

• KIPS Transactions on Computer and Communication Systems
• /
• v.10 no.4
• /
• pp.117-122
• /
• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• Proceedings of the Korea Contents Association Conference
• /
• 2007.11a
• /
• pp.80-83
• /
• 2007

Entering 21st century, various natural disasters have been caused by the scorching heat wave, earthquake, tsunami, typhoon and so on. The casuality and damages have been drastically increased in terms of the frequency and magnitude. Therefore, 50 nations around the world agreed to build up the GEO(Global Earth Observation) in charge of the earth observation for the understanding of the earth system changes, monitoring and prediction and it is on operation. To keep the pace with GEOSS for the cooperation of Science & Technology and to successfully achieve the GEOSS project, KGEO office was established and has been on its duty. Moreover, for more prosperous building of the GEOSS, in cooperation with KGEO and KISTI(Korea Institute of Science and Technology Information), we've conducted the survey of the domestic situation about 9 societal benefit areas of the GEOSS. This survey consists of 5 sections as follows: the standardization, the information system management, the raw data and metadata, the infrastructure, and the others. This survey results will be used as the basic material for establishing the National Global Earth Observation System.

• Journal of Satellite, Information and Communications
• /
• v.12 no.1
• /
• pp.6-12
• /
• 2017

Recently, the demand for SAR imaging is growing to monitor natural disasters or military sites to foresee topographic changes, where optical sensing is not easily available. High-resolution SAR images are useful in exploring topography and monitoring artificial land objects in all weather conditions. In this paper,high resolution SAR images acquired from KOMPSAT-5 are exploited for the applications of change detection and classification. In order to detect change areas, amplitude change detection (ACD) and coherence change detection (CCD) algorithms are employed and their performances are compared in practical applications. For enhanced performance, the potential of small scaled change detection is explored by combining multi-temporary SAR images. The k-means and SVM methods are applied for land classifications and their performances are compared by applying to the real spaceborne SAR images.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.5
• /
• pp.1-11
• /
• 2008

Wireless Sensor Networks is applied to improvement of life convenience or service like U-City as well as environment pollution, tunnel and structural health monitoring, storm, and earthquake diagnostic system. To increase the usability of sensor data and applicability, mobile devices and their facilities allow the applications of sensor networks to give mobile users and actuators the results of event detection at anytime and anywhere. In this paper, we present MUSNEMO(Multi-sensor centric Ubiquitous Smart sensor NEtwork using Mobile devices) developed system for providing more efficient and valuable information services with a variety of mobile devices and network camera integrated to WSN. Our system is performed based on IEEE 802.15.4 protocol stack. To validate system usability, we built sensor network environments where were equipped with five application sensors such magnetic, photodiode, microphone, motion and vibration. We also built and tested proposed MUSNEMO to provide a novel model for event detection systems with mobile framework.