• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.450-453
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• 2005

A forest fire occurs mainly as natural factor such as wind, temperature or human factor such as light. Recently, the most of forest fire prevention is prediction or prevision against forest fire by using remote sensing technology. However in order to forest fire prevention, the remote sensing has many limitations such as high cost and advanced technologies and so on. Therefore, we need to multisensor integration system that utilize not only remote sensing but also in-situ sensing in order to reduce large damage of forest fire though analysis of happen cause and prediction routing of occurred forest fire. In this paper we propose a multisensor integration system that offers prediction information of factors and route of forest fire by integrates collected data from remote sensor and in-situ sensor for forest fire prevention. The proposed system is based on wireless sensor network for collect observed data from various sensors. The proposed system not only offers great quality information because firstly, raw data level fuse different format of collected data from remote and in-situ sensor but also accomplish information level fusion based on result of first stage. Offered information from our system can help early prevention of factor and early prevision against occurred forest fire which transfer to SMS service or alert service into monitoring interface of administrator.

• The Korean Journal of Emergency Medical Services
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• v.6 no.1
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• pp.185-197
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• 2002

Today, the basic problem of functional safe management of Korean Disaster Control system was separately administrated 33 acts that are relating to safe management in 13 ministries. Because of the facts that the fire service is not provided practically, the control system and risk management for safe administration are not operated, the information can not be shared with each other, and the various laws have the lacks of linkage, the National Safe System was appeared unsteady. The roles and functions of fire service have started with restriction to operate structurally and institutionally, which operational structure of fire service is becoming weak. As a result, the federal and local fire organizations have not reached yet to the institutionalization and the local fire service agencies have bias with the task regarding the fire service because of the relation between organizational structure and the local fire agency. With the enforcement of the federal and local fire system, professionality and autonomy for making policy, and dealing with changes of fire service positively, the national fire service on the policy performance can be established. Promotion of research and development and education training to strengthen innovation in technology and competition in fire industry will contribute to the firmly establishment of control system to prevent from fire, flood, terror and national disaster. This article proposed that (a) the established law and administration, agency are required efforts to effectively operate fire service system; (b) the national fire service agency, national college of fire, national institute of science fire, and national fire service hospital should be early established to make firmly policy to operate effectively and practically. These kinds of innovational acts are known the best ways of operating solid policy of national fire service system.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.747-749
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• 2003

For forest fire monitoring in relatively cool area like Siberia, design of Decision Support System (DSS) is proposed. The DSS is consisted of three different algorithms to detect potential fires from NOAA AVHRR image. The algorithm developed by CCRS (Canada Center for Remote Sensing) uses fixed thresholds for multi-channel information like one by ESA (European Space Agency). The algorithm of IGBP (International Geosphere Biosphere Program) involves contextual information in deriving fire pixels. CCRS and IGBP algorithms are rather liberal compared to more conservative ESA algorithm. Fire pixel information from the three algorithms is presented to the user. The user considers all these information in making decision about the location fire takes place.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1847-1859
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• 2022

Wildfires in North Korea can have a directly or indirectly affect South Korea if they go south to the Demilitarized Zone. Therefore, this study calculates the regional optimized Forest Fire Danger Index (FFDI) based on Local Data Assessment and Prediction System (LDAPS) weather data to obtain forest fire risk in North Korea, and applied it to the cases in Goseong-gun and Cheorwon-gun, North Korea in April 2022. As a result, the suitability was confirmed as the FFDI at the time of ignition corresponded to the risk class Extreme and Severe sections, respectively. In addition, a qualitative comparison of the risk map and the soil moisture map before and after the wildfire, the correlation was grasped. A new forest fire risk index that combines drought factors such as soil moisture, Standardized Precipitation Index (SPI), and Normalized Difference Water Index (NDWI) will be needed in the future.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2095-2107
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• 2000

In maned ship, crews may have risks as they manage damage control system in IPMS in damage situations such as fire in a ship. So the application of unmaned autonomous systms can reduce the number of boarding crews and attribute to safe marine transportation. The paper suggests an intelligent system of the fire fighting control using fuzzy logic in Integrated Platform Management System which can take measures against fire situation of a ship excluding unnecessary warnings with undamaged situations. The system here detected the fire more accurately and adopted more appropriate measures according to ship status compared with conventional systems. Of all, a reduction of false detection of fires was noted.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1737-1741
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• 2022

Active fire monitoring using high-resolution drone images and deep learning technologies is now an initial stage and requires various approaches for research and development. This letter examined the detection of active fire objects using You Look Only Once Version 7 (YOLOv7), a state-of-the-art (SOTA) model that has rarely been used in fire detection with drone images. Our experiments showed a better performance than the previous works in terms of multiple quantitative measures. The proposed method can be applied to continuous monitoring of wide areas, with an integration of additional development of new technologies.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.243-251
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• 2020

This study is intended to verify the efficiency of the information system by using the navigation application in case of fire. In the demonstration scenario simulation, it was assumed that a fire occurred 6th floor in Korea Institute of Industrial Design Promotion located in C city, K province. Eighty juniors students from K University's department of paramedics of science participated. As a result of the experiment, the demonstration simulation using the navigation application showed that the evacuation time was faster than the case of evacuation guidance in a fire situation. The need for a fire prevention system and fire prevention awareness before and after the implementation of the demonstration scenario simulation increased the need for a fire prevention system and fire prevention awareness score after the experiment.

• International Journal of Safety
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• v.4 no.2
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• pp.12-17
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• 2005

This paper aims at the development of an knowledge base for an electrical fire cause diagnosis system using the entity relation database. The relation database which provides a very simple but powerful way of representing data is widely used. The system focused on database construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. In order to store and access to the information concerned with electrical fires, the key index items which identify electrical fires uniquely are derived out. The knowledge base consists of a case base which contains information from the past fires and a rule base with rules from expertise. To implement the knowledge base, Access 2000, one of DB development tools under windows environment and Visual Basic 6.0 are used as a DB building tool. For the reasoning technique, a mixed reasoning approach of a case based inference and a rule based inference has been adopted. Knowledge-based reasoning could present the cause of a newly occurred fire to be diagnosed by searching the knowledge base for reasonable matching. The knowledge-based database has not only searching functions with multiple attributes by using the collected various information(such as fire evidence, structure, and weather of a fire scene), but also more improved diagnosis functions which can be easily wed for the electrical fire cause diagnosis system.

• International Journal of Safety
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• v.6 no.2
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• pp.27-32
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• 2007

For last several decades with the achievement of fast economic development, the electrical fires occupies over 30 percent of total fire incidents almost every year in Korea and not decreased in spite of much times and efforts. Electrical fire cause diagnostics are to confirm a cause for the fire by examination of fire scene. Cause diagnosis methods haven't been systematized yet, because of limits for available information, investigator's biased knowledge, etc. Therefore, in order to assist the investigators and to find out the exact causes of electrical fires, required is research for an electrical fire cause diagnosis system using DB, computer programming and some mathematical tools. The electrical fire cause diagnosis system has two functions of DB and electrical fire cause diagnosis. The cause diagnosis is conducted by a case-based reasoning on a case base and rule-based reasoning on a rule base. For the diagnosis with high reliability, a mixed reasoning approach of a case-based reasoning and fuzzy rule-based reasoning has been adopted. The electrical fire cause diagnosis system proposes the electrical fire causes inferred from the diagnosis processes, and possibility of the causes as well.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.35-38
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• 2009

The paper presents an effective method to detect fire in video surveillance and monitoring system. The main contribution of this work is that we successfully use the Hidden Markov Models in the process of detecting the fire with a few preprocessing steps. First, the moving pixels detected from image difference, the color values obtained from the fire flames, and their pixels clustering are applied to obtain the image regions labeled as fire candidates; secondly, utilizing massive training data, including fire videos and non-fire videos, creates the Hidden Markov Models of fire and non-fire, which are used to make the final decision that whether the frame of the real-time video has fire or not in both temporal and spatial analysis. Experimental results demonstrate that it is not only robust but also has a very low false alarm rate, furthermore, on the ground that the HMM training which takes up the most time of our whole procedure is off-line calculated, the real-time detection and alarm can be well implemented when compared with the other existing methods.