• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.103-109
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• 2015

This paper introduces a multi-purpose smart fusion sensor. Normally, this type of sensor can contribute to energy savings specifically related to lighting and heating/air conditioning systems by detecting individuals in an office building. If a fire occurs, the sensor can provide information regarding the presence and location of residents in the building to a management center. The system consists of four sensors: a thermopile sensor for detecting heat energy, an ultrasonic sensor for measuring the distance of objects from the sensor, a fire detection sensor, and a passive infrared sensor for detecting temperature change. The system has a wireless communication module to provide the management center with control information for lighting and heating/air conditioning systems. We have also demonstrated the usefulness of the proposed system by applying it to a real environment.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.621-632
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• 2013

The most important things for a forest fire detection system are the exact extraction of the smoke from image and being able to clearly distinguish the smoke from those with similar qualities, such as clouds and fog. This research presents an intelligent forest fire detection algorithm via image processing by using the Gaussian Mixture model (GMM), which can be applied to detect smoke at the earliest time possible in a forest. GMMs are usually addressed by making the model adaptive so that its parameters can track changing illuminations and by making the model more complex so that it can represent multimodal backgrounds more accurately for smoke plume segmentation in the forest. Also, in this paper, we suggest a way to classify the smoke plumes via a feature extraction using HSL(Hue, Saturation and Lightness or Luminanace) color space analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.69-71
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• 2022

Today, the AI market is very large due to the development of AI. Among them, the most advanced AI is image detection. Thus, there are many object detection models using YOLOv5.However, most object detection in AI is focused on detecting objects that are stereotyped.In order to recognize such unstructured data, the object may be recognized by learning and filtering the object. Therefore, in this paper, a fire monitoring system using YOLOv5 was designed to detect and analyze unstructured data fires and suggest ways to improve the fire object detection model.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.157-160
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• 2008

This study analyzed on the area of Samcheok, Kangwondo about forest fire alarming area and enlargement of the area. Then, visible area by unattended watching camera and watchtower for forest fire which were run by Samcheok was cross-checked with geographic information system, and it could be whether effective on watching the area where the forest fire risk was high enough and also it could be expanded to larger forest fire. The result of study, the visible area by watching facilities only holds for 13.4% of the whole forest fire alarming area, but the forest fire can be observed even though it is occurred in small valley because of smoke and all the forest fire have been occurred in daytime. Therefore, it can be determined that watching area will be extended around 50.3% while the observation radii of watching facilities raise by 4km. However, Samcheok has much greater area of mountain area in compared to any other cities or counties, watching facilities should be installed and run additionally for extinguishing the forest fire from the beginning.

• Fire Science and Engineering
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• v.25 no.2
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• pp.71-79
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• 2011

Since 2008 Korea's fire administration has recognized the importance of human resources by introducing a mentoring system for new employees. This mentoring program is helping new employees adapt to the organization quickly and effectively. In addition, prevention inspectors are improving their job ability and expertise by ensuring the mentoring system has been introduced and operated. However, the current operating and fire officials mentoring system has a variety of problems including lack of expertise on the part of the mentors, deficiency of the legal system, lack of mentoring for information and materials, and lack of compensation, and formal mentoring training for mentors. In this study, the fire officials' mentoring system analysis and previous studies on the fire officials' mentoring functions will be analyzed to determine its effect on job performance. Results of this study of fire officials' job ability show that the variables that affect the mentoring program include the role model, business achievement, teaching method, attitude, interest, and achievement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.497-498
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• 2018

In the fire scene, it is difficult to see 1m ahead because of power failure, smoke and toxic gas, even with thermal imaging camera and Xenon searchlight. Analysis of the smoke particles in the fire scene shows that even if the smoke is $5{\mu}m$ or less in wavelength, it is difficult to obtain a front view when using a conventional thermal imaging camera if the visual distance exceeds 1 meter. In the case of black smoke with a particle wavelength of $5{\mu}m$ or more, a space permeation sensor technology using various sensors other than a single sensor is required because chemical materials, gas, and water molecules are mixed. Firefighters need a smoke detection technology for smoke detection and spatial information visualization for forward safety view.In this paper, we design the interface of the information processing system with 32bit CPU core and peripheral circuit. We also implemented and simulated the interface with Lidar sensor. Through this, we provide interface that can implement information processing system of human enhancement fire helmet in the future.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.87-94
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• 2008

In this paper, we propose a new vision-based fire detection method for a real-life application. Most previous vision-based methods using color information and temporal variation of pixel produce frequent false alarms because they used a lot of heuristic features. Furthermore there is also computation delay for accurate fire detection. To overcome these problems, we first detected candidated fire regions by using background modeling and color model of fire. Then we made probabilistic models of fire by using a fact that fire pixel values of consecutive frames are changed constantly and applied them to a Bayesian Network. In this paper we used two level Bayesian network, which contains the intermediate nodes and uses four skewnesses for evidence at each node. Skewness of R normalized with intensity and skewnesses of three high frequency components obtained through wavelet transform. The proposed system has been successfully applied to many fire detection tasks in real world environment and distinguishes fire from moving objects having fire color.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.9-16
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• 2020

In this paper, we propose a prototype design and implementation of a fire detection algorithm using multiple sensors. The proposed topic detection system determines fire by applying rules based on data from multiple sensors. The fire takes about 3 to 5 minutes, which is the optimal time for fire detection. This means that timely identification of potential fires is important for fire management. However, current fire detection devices are very vulnerable to false alarms because they rely on a single sensor to detect smoke or heat. Recently, with the development of IoT technology, it is possible to integrate multiple sensors into a fire detector. In addition, the fire detector has been developed with a smart technology that can communicate with other objects and perform programmed tasks. The prototype was produced with a success rate of 90% and a false alarm rate of 10% based on 10 actual experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.535-538
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• 2010

In this paper, this study goal is development for WSN-based fire prevention systems of using temperature/humidity Sensor. So, distributed sensor nodes structural and packet transfer characteristics study for fire monitoring. Battery-operated wireless sensor networks is data transfer manner of multi-hop. WSN fire prevention system need to sensor nodes management and energy consumption of efficient adjust for sustained action. Thus, study with efficient energy consumption the normal WSN environment is not, characteristics for WSN fire prevention environment.

• Journal of the Korean Professional Engineers Association
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• v.32 no.6
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• pp.148-157
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• 1999

As cultural Heritages are source of the national history and a life transition, their extinction is a fatal shock as result of cutoff the genealogy of the creative national spirit. So, we have necessarily to protect them, and to get the duty and the responsibility which the cultural inheritance hands over tnem to descendants with preserving and meaning safely at present time. In these days, the risk of fire in the Cultural Heritages building is increased because of rash changing environments from the indiscreet development of them. Accordingly, in order to get the original transmission of the Cultural Heritages, this paper involves being intensive the fire safety information of the Cultural Heritage in kyonggi-do province, analyzing their diagnoses, and studying a Fire Safety Prevention Management model to protect and to maintain them continuously. Therefore, it is to contribute from this approach to collecting fire safety information, analyzing diagnostic problems in fire accidents, and to manage the prevention method for protecting and maintaining the Cultural Heritages.