• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.11a
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• pp.7-10
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• 2008

In our study, Monitoring RF System in real-time on leakage of gas cylinder is developed. The system is consisted of Pressure Transmitting part, Main Controller and Operating program. The pressure data of gas cylinder are transmitted to the modem of main controller part by RF module of Pressure Transmitting part and the data received through the modem are recorded in real-time and showed the situation of gas cylinder on the PC monitor. Through the test on the case of the artificial pressure-reduction, the detecting performance. of the developed system is conformed.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.13-21
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• 2004

The usefulness of the multi-temporal satellite image to monitoring the vegetation recovery process after forest fire was tested. Using multi-temporal Landsat TM and ETM＋data, NDVI and NBR changes over times were analyzed. Both NDVI and NBR values were rapidly decreased after the fire and gradually increased for all forest type and damage class. However, NBR curve showed much clearer tendency of vegetation recovery than NDVI. Both indices yielded the lowest values in severely damaged red pine forest. The results show the vegetation recovery process after forest fire can detect and monitor using multi-temporal Landsat image. NBR was proved to be useful to examine the recovering and development process of the vegetation after fire. In the not damaged forest, however the NDVI shows more potential capability to discriminate the forest types than NBR..

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2005.11a
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• pp.266-271
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• 2005

• Fire Science and Engineering
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• v.30 no.2
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• pp.43-48
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• 2016

One of the main problems with gaseous fire extinguishers is the decrease in fire suppression capability due to the leakage of the fire extinguishing agents, either naturally or caused by obsolete equipment. Therefore, in this study, a real-time detector module for monitoring pressure leakages was developed and an assessment on its performance was carried out. Currently, there are no domestic or global standards for testing pressure leakage detection systems. Therefore, similar global standards, such as ISO 7240 and FM 1421, and the domestic law on "Receiver type-approval and technical standards for product inspection" were used as a reference for assessing the performance of the newly developed module. Its basic performance was assessed by applying compressed air to the module, and, as a result, the minimum working pressure was identified as 0.3 bar. Its environmental qualification was carried out to confirm the proper functioning of the module in different climates and the module was confirmed to function properly at both high ($50^{\circ}C$) and low ($-10^{\circ}C$) temperatures.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.04a
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• pp.43-46
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• 2004

Through investing the criteria and evaluation for fire performance of interior components, this paper introduce the testing items and requirements for Flammability, Smoke density, and Toxicity properties of TTX(Tilting Train eXpress) interior parts. Next time, all trains including TTX will be occupied the components with superior fire-resistance and the sensing and monitoring system for fire in train.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.151-161
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• 2006

This paper has a goal to construct monitoring web GIS system which displays maps that are results of the fire detecting algorithms using MODIS image. To design and build more efficient system, foreign fire monitoring systems using satellite image are researched and analyzed. As a result of that, the information about interfaces and services provided by them are obtained. In concretely, new logical DFD is used to do a process modelling. ArcIMS 4.0 of ESRI, IIS 5.1 of Microsoft are utilized to build the web GIS System. In the aspects of data input and transfer, a specific module, which converts a binary image to a kind of vector file, is developed to adjust raster data to the web GIS system.

• Fire Science and Engineering
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• v.32 no.3
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• pp.134-139
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• 2018

Extremely fine particles seriously affect people and are becoming a social problem. Conventional methods using the type of beta ray absorption are difficult to have real-time measurements and miniaturization for the acquisition of fine dust. In this paper, a light scattering method was used. The sensors were configured internally with semiconductor laser diodes for miniaturization, low cost and lightweight. The use of the FFT method makes it easier to separate fine dust according to size compared to conventional light scattering sensors. Bluetooth communication also allows the connection, monitoring and control of devices using smart phones.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.536-546
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• 2022

A society will lose a lot of something in this field when the forest fire broke out. If a forest fire can be detected in advance, damage caused by the spread of forest fires can be prevented early. So, we studied how to detect forest fires using CCTV currently installed. In this paper, we present a deep learning-based model through efficient image data construction for monitoring forest fire smoke, which is unstructured data, based on the deep learning model YOLOv5. Through this study, we conducted a study to accurately detect forest fire smoke, one of the amorphous objects of various forms, in YOLOv5. In this paper, we introduce a method of self-learning by producing insufficient data on its own to increase accuracy for unstructured object recognition. The method presented in this paper constructs a dataset with a fixed labelling position for images containing objects that can be extracted from the original image, through the original image and a model that learned from it. In addition, by training the deep learning model, the performance(mAP) was improved, and the errors occurred by detecting objects other than the learning object were reduced, compared to the model in which only the original image was learned.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.40-47
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• 2013

In case of wild fire, early detection of wild fire is the most important factor in minimizing the damages. In this paper, we suggest an effective system that detects wild fire using a panoramic image from a single camera with PAN/TILT head. This enables the system to detect the size and the location of the fire in the early stages. After converting RGB image input to color YCrCb image, the differential image is used to detect changes in movement of the smoke to determine the regions which may be prone to forest fire. Histogram analysis of fire flame is used to determine the possibility of fire in the predetermined regions. In addition, image matching and SURF were used to create the panoramic image. There are many advantages in this system. First of all, it is very economical because this system needs only a single camera and a monitor. Second, it shows the live image of wide view through panoramic image. Third, this system can reduce the quantity of saved data by storing panoramic images.

• Journal of the Korean Institute of Gas
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• v.24 no.2
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• pp.50-55
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• 2020

The heuristics accumulated in the field activities of firefighters were reviewed through big data analysis of fire occurrences in Gyeonggi-do and researched to be utilized for proper fire prevention activities according to time, day, and target through quantitative modeling. Empirical rules with high sympathy were collected through direct interviews with firefighters. Among them, the rule of thumb that "Friday is the most fire-prone" is considered to be the most important in terms of fire monitoring and prediction. A big data comparison analysis was conducted, including the number of fires and damages that occurred in Gyeonggi-do in 2018. Furthermore, fire occurrence patterns by region, day of the week, time of day, and building type were derived. Regarding empirical rules that have been validated through research, relatively inexperienced firefighters also can make decisions by relying on refined quantitative predictive modeling and empirical rules including local government and time-based factors that reflect big fire occurrence data.