• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.561-564
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• 2009

This paper present design and implementation of U-city infrared image surveillance system based on the digital media processor. The hardware is designed and implemented by using commercial chips such as DM642 processor and video encoder, video decoder and the functions of software are to analyze temperature distribution of a monitoring image and to monitor disaster situation such as fire. The required functions and performances are confirmed by testing of the prototype and we verified practicality of the system.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.471-477
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• 2011

A wide distribution of CCTV cameras in many public areas can be used not only for video surveillance systems but also for preserving fire occurrence. A proposed approach is based on visual information through a static camera. Video sequences are analyzed to find fire candidates and then spatial analyses procedure for detected fire-like color foreground is carried out. If spatial and temporal variances changes rapidly and close to fire motion, fire candidate is considered as fire.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.1011-1016
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• 2009

In this paper, we propose the method of fire detection. A wide distribution of CCTV cameras (Closed Circuit Television) in many public areas can be used not only for video surveillance systems but also for detecting fire occurrence. A proposed approach is based on visual information through a static camera. Video sequences are analyzed to find fire candidates and then spatial analyses procedure for detected fire-like color foreground is carried out. From the simulation results, our method showed the best performance when spatial and temporal fire candidates changes rapidly and close to fire motion.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.499-504
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• 2006

터널 내 화재 발생 시 대규모의 인명, 재산 피해가 발생하는데 이러한 상황을 조기에 탐지함으로써 피해를 최소화하기 위한 시스템이 필요하다. 또한 터널 내 설치된 CCTV를 사람이 24시간 감시하기에는 너무 어려운 점이 많다. 이에 따라 적절한 영상 처리를 통한 화염 및 연기 검출 시스템을 통해 경보를 알려줄 경우, 보다 편리하고 사람이 모니터 앞에 없을 때 화재 발생 시 화재를 검출할 수 있어 피해를 최소화 할 수 있다. 본 논문에서는 영상처리 기법을 이용하여 터널 안에서 발생한 화재 및 연기를 고속으로 탐지하기 위한 알고리즘을 제안하였다. 터널 안에서의 화재 탐지는 차량 조명 및 터널내의 조명등과 같은 여러 가지 상황에 의해 산불 탐지 알고리즘과 다른 독자적인 알고리즘의 개발이 요구된다. 본 논문에서 제시한 두 가지 알고리즘은 기존 알고리즘보다 정확한 위치 탐지와 초기 단계에서의 탐지가 가능하도록 되었다. 또한 우리는 실험 결과를 통해 각각의 성능을 비교함으로써 제시한 알고리즘의 타당성을 보여주었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.719-720
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• 2024

센서 기반의 자동화재탐지설비의 역할을 지원할 목적으로, 합성곱 신경망 기반의 AI 화재 감시장비등이 연구되어왔다. ai 기반 화재 감지에 사용되는 알고리즘은 전이학습을 주로 이용하고 있고, 이는 화재 감지에 기여도가 낮은 프로세스가 내장되어 있을 가능성이 존재하여, 딥러닝 모델의 복잡성을 가중시키는 원인이 될 수 있다. 본 연구에서는 이러한 모델의 복잡성을 개선하고자 다양한 딥러닝 및 해석 기술들을 분석하였고, 분석 결과를 토대로 화재 감지에 최적화된 아키텍처인 "IF2bNet" 을 제안한다. 구현한 아키텍처의 성능을 비교한 결과 동일한 성능을 내면서, 파라미터를 약 0.1 배로 경량화 하여, 복잡성을 완화하였다.

• Fire Science and Engineering
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• v.17 no.4
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• pp.86-91
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• 2003

Since the air stream in the room controlled by HVAC system affects on he expected response of conventional detectors which are designed in accordance with normal characteristics of air stream in the fire incident, unexpected operation time delay may occur in fire. In order to solve this problem and to improve sensitivity so that to initiate fire in its early stages for minimizing damage and protecting people, we studied and developed Air Sampling Smoke Detector. The Air Sampling Smoke Detector is a kind of active-type fire detection system. it draws air continuously from the protected area through an air sampling pipe network to the smoke density analyzer. This study presents smoke density analysing technique and air intake balancing technique through an air sampling pipe network. As a result of evaluating, Air Sampling Smoke Detector was much more sensitive than conventional smoke detectors that passively wait for smoke to reach them and was not affected by ambient airflow in the room by means of balanced air intake through the sampling holes.

• Fire Science and Engineering
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• v.27 no.6
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• pp.83-88
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• 2013

Catastrophic disasters are sprouting out recently, i.e., the radiation leaks and the hydrofluoric acid gas leaks, etc. The restoration work for these kinds of disasters is very harmful and dangerous for human beings to handle themselves, thus allowing manless robots to fly the reconnaissance planes over to the disaster stricken areas and do the necessary work instead. For this endeavor and purpose, we created and tested an intelligent robot that can inspect those areas, using Mbed (ARM processor) technology temperature sensors and gas sensors aided by CAM (Computer-Aided Manufacturing) cameras. Also, HTTP Server, PC, androids and their combined efforts allow their remote controlled operation from far away with timing control. These intelligent robots can be on duty for 24 hours, minimizing the accidents and crimes and what not, and can respond more quickly when these misfortunes actually happen. We can anticipate the economic effects as well, derived from the reduced needs for hiring human resources.

• Journal of the Korean Society for Railway
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• v.19 no.4
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• pp.526-538
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• 2016

The government of South Korea has made great efforts in the area of railway safety management by means of a railway safety law and an integrated railway safety plan established in 2004 after the Daegu subway fire accident. However, after certain railway incidents, a reactive railway safety management system has been implemented that has led to fatal accidents caused by the collision, derailment, and fire every year. Hence, this study is intended to propose a framework that integrates data from distributed detection devices into a real-time railway safety monitoring and control system for proactive safety management. Furthermore, we will provide a future development direction for safety performance monitoring indicators to determine whether the railway safety monitoring and control system works effectively. The proposed framework is expected to be a cornerstone for the real-time railway safety monitoring and control system to be implemented in the future.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.365-366
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• 2013

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.135-145
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• 2011

These days, the research of a sensor data management system for USN based real-time monitoring application is active thanks to the development and diffusion of sensor technology. The sensor data is rapidly changeable, continuous and massive row level data. However, end user is only interested in high level data. So, it is essential to effectively process the row level data which is changeable, continuous and massive. In this paper, we propose a sensor data management system with multi-analytical query function using OLAP and anomaly detection function using learning based classifier. In the experimental section, we show that our system is valid through the some experimental scenarios. For the this, we use a sensor data generator implemented by ourselves.