• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.430-439
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• 2018

Purpose: The purpose of this study is to verify the effectiveness of maintenance method using GPR exploration by buried detective materials in the ground for efficient maintenance of recovered cavities. Method: EMI sheet, EMI paint, and ferronickel slag were used as the detection materials, and the experiment was conducted by varying the size and depth of the buried detectable material. Results: As a result of the exploration, Detectable influence range by GPR exploration was found depending on the size and depth of buried detectable material in all materials, and the possibility of using it as a detection material was confirmed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.929-932
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• 2007

The integrated prevention of disaster management system is collected prevention of disaster data from prevention of disaster relation other systems and smart sensor in USN. This system manages fire fighting facility effectively. The relation equipment which is used in existing and network using "Open Protocols" about under using the support system which is integrated effectively as the destroyer. It connects CCTV, the sensitivity environmental sensor, automatic fire detection equipment and security equipment and air flow equipment system using Internet. The System Server was collected monitoring data at the each equipment and processing by operational scenario. It will verified the effectiveness of operational scenario and integrated prevention of disaster management system

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.364-373
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• 2022

Purpose: The purpose of this paper is to develope smoke detection using AI model for detecting the initial fire in underground utility tunnels using CCTV Method: To improve detection performance of smoke which is high irregular, a deep learning model for fire detection was trained to optimize smoke detection. Also, several approaches such as dataset cleansing and gradient exploding release were applied to enhance model, and compared with results of those. Result: Results show the proposed approaches can improve the model performance, and the final model has good prediction capability according to several indexes such as mAP. However, the final model has low false negative but high false positive capacities. Conclusion: The present model can apply to smoke detection in underground utility tunnel, fixing the defect by linking between the model and the utility tunnel control system.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.429-430
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• 2022

본 논문에서는 일산화탄소 센서와 미세먼지 센서를 이용하여 연기농도에 따른 감도시험을 수행하였다. 일산화탄소 센서와 미세먼지 센서는 광전식감지기 감도시험 챔버 내에서 발생시킨 연기농도에 따라 감지반응이 있었으며, 다양한 화재정보를 제공을 위해 가스 센서 및 미세먼지 센서가 기술기준 도입이 필요할 것으로 사료된다.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.110-116
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• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.135-143
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• 2012

Remote sensing which observes repeatedly the whole Earth and GIS-based decision-making technology have been utilized widely in disaster management such as early warning monitoring, damage investigation, emergent rescue and response, rapid recovery etc. In addition, various countermeasures of national level to collect timely satellite imagery in emergency have been considered through the operation of a satellite with onboard multiple sensors as well as the practical joint use of satellite imagery by collaboration with space agencies of the world. In order to respond heavy snowfall disaster occurred on the east coast of the Korean Peninsula in February 2011, snow-covered regions were analyzed and detected in this study through NDSI(Normalized Difference Snow Index) considering reflectance of wavelength for MODIS sensor and change detection algorithm using satellite imagery collected from International Charter. We present the application case of National Disaster Management Institute(NDMI) which supported timely decision-making through GIS spatial analysis with various spatial data and snow cover map.

• Journal of the Society of Disaster Information
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• v.13 no.4
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• pp.422-441
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• 2017

Notifying emergency evacuation methods, accurate disaster location and evacuation route guidance can be very active alternatives to quickly minimize evacuation and casualties in disaster situation in the development of subway disaster prevention detection system that detects the disaster signs at the subway station early on the basis of Internet of things and leads passengers to evacuate. It's not easy to ensure perfect functioning of fire fighting facilities and equipments due to underground space structure with narrow exits. Therefore, we developed disaster provision EL Display integrated board that can induce the most efficient evacuation and the field experiment was conducted to examine the practical application in this study. Especially the applicability was verified by field application test because there is no case in which EL panels are used to evacuate disasters.

• Fire Science and Engineering
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• v.23 no.2
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• pp.1-5
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• 2009

We studies wish to investigated establishment form of cabinet board, and confirm possibility of electrical disaster prevention through reappearance experiment of odor detection system. Established breaker consists of MCCB, RCD order in cabinet board for house, but industry is used together with. When imposed shock using shaker to terminal block that contact becomes in appropriate, flame was made sure. According to result that experiment attaching odor capsule in terminal block, capsule commissioned exactly by occurred heat. According to establishment position of sensor, difference of inspection time was about 10 seconds. Estimate odor inspection system by thing which electrical device accident prevention is available. When there is abnormal generated heat in connection of electric wire, accident prevention estimates that is possible by giving an alarm state of overheat to administrator.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.1-8
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• 2021

In this paper, we propose the construction of an IOT that monitors foresters' physical abnormalities in real time, performs emergency measures, and provides alarms for natural disasters or heatstroke such as a nearby forest fire or landslide. Nodes provided to foresters include 6-axis sensors, temperature sensors, GPS, and LoRa, and transmit the measured data to the network server through the gateway using LoRa communication. The network server uses 6-axis sensor data to determine whether or not a forester has any signs of abnormal body, and performs emergency measures by tracking GPS location. After analyzing the temperature data, it provides an alarm when there is a possibility of heat stroke or when a forest fire or landslide occurs in the vicinity. In this paper, it was confirmed that the real-time detection of physical abnormalities of foresters and the establishment of disaster early warning IOT is possible by analyzing the data obtained by constructing a node and a gateway and constructing a network server.