• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.367-371
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• 2007

최근 여러 지역에서 발생되는 지하철 참사 및 대형화재 또는 지하철 역사, 대형 지하상가, 백화점, 지하공간, 대형쇼핑센터, 숙박업소, 공공건물등 대형 다중이용시설 등에서 발생될 수 있는 예측 불가능한 인재, 천재지변에 안전하게 대피하기 위한 수단으로 비상등 및 여러 감지기들이 소방법 개정으로 의무설치 하고 있다. 비상등 및 감지기들은 비상시 위험 감지 및 경고 전파를 위해 사용되는데 방음벽이나 격벽, 경고 거리의 제한으로 인해 경고 전달의 어려움이 있다. 본 논문에서는 무선 데이터 전송기능 및 경고등, 음성전파 기능을 갖는 무선 지능형 화재 감지/경고시스템을 설계하고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1082-1087
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• 2019

Video Incident Detection System is a detection system for the purpose of detection of an emergency in an unexpected situation such as a pedestrian in a tunnel, a falling object, a stationary vehicle, a reverse run, and a fire(smoke and flame). In recent years, the importance of the city center has been emphasized by the construction of underpasses in great depth underground space. Therefore, in order to apply Video Incident Detection System to a Double Deck Tunnel, it was developed to reflect the design characteristics of the Double Deck Tunnel. and In this paper especially, the fire detection technology, which is not it is difficult to apply to the Double Deck Tunnel environment because it is not supported on existing Video Incident Detection System or has a fail detect, we propose fire detection using color image analysis, silhouette spread, and statistical properties, It is verified through a real fire test in a double deck tunnel test bed environment.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.265-270
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• 2003

Though the probability of tunnel fire accident is very low, but critical fatalities are expected when it occurred. In this study the effect of critical safety parameters on tunnel fire accident are examined using probabilistic technique. Fire detection time, smoke spread velocity, passenger escape velocity, flash-over time, and emergency service arrival time are considered. In order to estimate the uncertainties of input parameters Monte Carlo simulation are used, and fatalities for each assumed accident scenarios are obtained as results. For the efficiency of iterative calculation PRA(Probabilistic Risk Analysis) code is developed in this study. As a result fire detection have large effect.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.4
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• pp.180-186
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• 2002

This paper describes on the development of power detection system with one-chip microcontroller. The designed system is composed of power detection circuits and analyzing software. The system detects, 3-phases voltage, 3-phases current, external temperature, leakage current and stores in flash memory. AT89C52 was used as CPU and AM29F040B was used as memory to store the data. The analysis saftware was developed to detect the cause of the electrical fire incidents. With a data-compression technology, the data can be stored for the 43.5 days in a normal state, four hours and fifteen minutes in emergency state.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.355-360
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• 2023

Fire is a disaster that causes irreversible damage to many people due to personal injury and property damage. Various fire detection equipments are installed around us to detect and cope with it quickly. However, due to various problems such as artificial, environmental, and aging, fire detection equipment is activated even though it is not a actual fire, and there are many problems such as delaying the support to the necessary fire scene. In this paper, we analyze the non-fire alarm of the fire detection equipment and propose a system that enables the field staff to check the scene situation through the video as a way to prevent the mobilization due to the misinformation by checking the fire. The purpose of the present invention is to stably cope with a disaster by suggesting a customized automatic guidance system which induces a rapid evacuation by sending an evacuation guidance notification to a range of a fire occurrence neighboring area, and supports a rapid and accurate processing by a rapid dispatch of a firefighter, rather than a wide range of guidance such as an existing emergency disaster guidance letter when it is determined to be an actual fire through the confirmation procedure.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• 전자공학회논문지 IE
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• v.48 no.3
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• pp.26-32
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• 2011

This paper proposed that the method be searched for optimal route of evacuation by algorithm using potential field in specific situation, fire. When robot met an obstacle to be indicated it to ignition point, the installed sensor could be detected the point in restricted area. In according as the data of a fire detection sensor and a sensor complex in a building, the information was transmitted to server which computed optimal route of evacuation by algorithm using potential field. After that, it was able to blow a siren and mark the safe-path with using wireless device such as smart-phone. It was confirmed that the proposed method in functional test, fire emergency evacuation algorithm using potential field, was advanced in circumstance of simulation.

• Fire Science and Engineering
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• v.25 no.6
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• pp.98-103
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• 2011

Currently, domestic architecture has applied the building fire-fighting equipments to most buildings except conventional houses, villas and facilities, and so on. However, the use of fire-fighting equipments what are not working properly result in a human life and property damages consistently like a fire of Icheon warehouse facilities, Korea cold storage, the tragic incident of subway in Daegu and the recent issue of a fire in the high-rise efficiency apartment, etc. In this study, I'm trying to seek solutions by taking research on the actual condition of fire alarming system, fire escaping equipment, Indoor Fire Hydrant Installation.

• The Korean Journal of Emergency Medical Services
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• v.24 no.2
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• pp.27-38
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• 2020

Purpose: Stroke is a time-sensitive disease that could have reduced complications and mortality with timely diagnosis and treatment. This study aimed to analyze the causes of delay in detecting the clinical signs and symptoms of stroke. Methods: This retrospective observational study analyzed the emergency medical services reports of suspected stroke patients with positive predictive values on the Cincinnati Prehospital Stroke Scale. The study was conducted in Daejeon, Republic of Korea from January 1, 2016 through December 31, 2017. Results: Prolonged prehospital time was associated with high blood pressure, history of cerebrovascular disease, and incidences during daily activities, and sleep. High blood pressure and complications from a previous stroke strongly associated with the prolonged stroke-detection phase (p<.05). Total prehospital time was shortened when patients had evident stroke symptoms, such as decreased level of consciousness, dysarthria, and hemiplegia (p<.05). There was no significant difference in gender or age as a factor that delayed the total prehospital time of the suspected stroke patients. Conclusion: Many patients did not recognize the early clinical symptoms and signs of a stroke. Furthermore, risk factors, such as high blood pressure and history of stroke, prolonged the total prehospital time. Therefore, we need targeted interventions that educate about warning symptoms of stroke, along with emphasis on the importance of emergency calls to substantially reduce the prehospital delays.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1263-1269
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• 2016

Hearing impaired persons are exposed to the danger since they can't be aware of many dangerous situations like fire alarms, car hones and so on. Therefore they need haptic or visual informations when they meet dangerous situations. In this paper, we design a dangerous sound detection engine for hearing impaired. We consider four dangerous indoor situations such as a boiled sound of kettle, a fire alarm, a door bell and a phone ringing. For outdoor, two dangerous situations such as a car horn and a siren of emergency vehicle are considered. For a test, 6 data sets are collected from those six situations. we extract LPC, LPCC and MFCC as feature vectors from the collected data and compare the vectors for feasibility. Finally we design a matching engine using an artificial neural network and perform classification tests. We perform classification tests for 3 times considering the use outdoors and indoors. The test result shows the feasibility for the dangerous sound detection.