• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.57-64
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• 2022

If the inside of a building collapses due to a disaster such as fire, collapse, or natural disaster, the physical security inside the building is likely to become ineffective. Here, physical security is needed to minimize the human casualties and physical damages in the collapsed building. Therefore, this paper proposes an algorithm to minimize the damage in a disaster situation by fusing existing research that detects obstacles and collapsed areas in the building and a deep learning-based object detection algorithm that minimizes human casualties. The existing research uses a single camera to determine whether the corridor environment in which the robot is currently located has collapsed and detects obstacles that interfere with the search and rescue operation. Here, objects inside the collapsed building have irregular shapes due to the debris or collapse of the building, and they are classified and detected as obstacles. We also propose a method to detect rescue requesters-the most important resource in the disaster situation-and minimize human casualties. To this end, we collected open-source disaster images and image data of disaster situations and calculated the accuracy of detecting rescue requesters in disaster situations through various deep learning-based object detection algorithms. In this study, as a result of analyzing the algorithms that detect rescue requesters in disaster situations, we have found that the YOLOv4 algorithm has an accuracy of 0.94, proving that it is most suitable for use in actual disaster situations. This paper will be helpful for performing efficient search and rescue in disaster situations and achieving a high level of physical security, even in collapsed buildings.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.196-205
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• 2021

As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1135-1142
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• 2017

In this paper, we propose IoT based smart CCTV security service to prevent crime in blind spot and prevent unexpected fire or danger. In the proposed method, a RC (Radio Control) car is made using Raspberry pie, and a camera and various modules are installed in an RC car. It was then implemented using Raspbian O / S, Apache Web Server, Shell script, Python, PHP, HTML, CSS, Javascript. The RC car provides a security service that informs the manager of the situation by judging the risk of the scene with modules such as video, voice and temperature. Experimental results show that the transmission time of video and audio information is less than 0.1 second. In addition, real-time status transmission was possible in AVG, emergency, and manual mode. It is expected that the proposed method will be applied to the development of smart city by applying it to unmanned vehicles, drones and the like.

• Journal of the Korean Institute of Gas
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• v.16 no.5
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• pp.41-46
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• 2012

The flash point the lowest temperature at which the concentration of vapor of the substance in the air reaches the lower flammability limit(LFL), and is one of the most important physical properties used to determine the potential for fire and explosion hazards of industrial materials. The most published flash point data was for pure components and the flash points of the binary solutions that have flammable components, appear to be scarce in the literature. In the present study, the flash points of tert-pentanol+n-decane system were measured by Tag open-cup tester. The measured data were compared with the values calculated by the Raoult's law and the optimization methods based on the Wilson and NRTL equations. The calculated values by optimization methods were found to be better than those based on the Raoult's law.

• Journal of the Korean Institute of Gas
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• v.15 no.5
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• pp.57-62
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• 2011

Modern chemical plants including petroleum refinery and gas industries have evolved into more complex and specialized. In these industrial complexes, it is important to maintain acceptable safety level protecting from various potential disasters caused by fire, explosion and the leakage of toxic materials. Recently possibility and consequence of accidents are increasing in the industrial process. So there is a trade-off between the plant operation efficiency and safety level. In this study SIF(Safety instrument Functions) was incorporated into SIL(Safety Integrity Levels). As a result, the safety level was upgraded by designing resonable allocation of safety instruments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2225-2233
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• 2013

This study was designed to identify the extent of incident shock who are in high risk of post traumatic shock stress, and analyze the related factors that affect the extent of incident shock. The subjects are 415 rescue workers from Seoul Metropolitan Fire & Disaster Headquarters, who are in high frequency of fire outbreaks and rescue mobilization. With a reliability of Cronbach's ${\alpha}$=.975, the results show invasion, avoidance, sleep disorder and emotional paralysis, dissociative symptom, hyper arousal as foremost causes respectively. Moreover, the results imply that the extent of incident shock was higher in people with more age or being married. Also, from the occupational perspective, the number of years as fire fighters, as rescue workers, mobilization and experiences at work in proportion to incident shocks has risen exponentially. It is notable that the groups who alleviate stress by consuming liquors had higher extent of incident shock. In conclusion, to deal with groups in high risk, management system and prevention care programs for incident shocks need to be introduced immediately and put into effect.

• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.166-172
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• 1997

The BEF on the radial distribution line refers to a class of ground faults in which the load-side power line only is grounded, with the distribution line broken into two parts, the source-side and the load-side. Because its mechanism is remarkably different from that of other earth faults, the fault current is very low, and then difficult to detect the BEF. Thus, it is necessary to analyze its properties and to find an appropriate method that can economically protect the BEF of nonautomation area in the substation. As a result of analyzing the BEF data obtained by the RTDS, EMTP simulation, and the field test data of ETSA, we believe that it is the dominant factor in distinguishing the BEF from normal conditions by a criterion value that is appropriately handled from the zero-sequence current. Thus, with this criterion value, a BEF detecting algorithm is constructed which measures the variations of the zero-sequence current and processes then properly so as to make the fault decision. To prove the accuracy of this algorithm, it is compared with the field test data of ETSA under various conditions. The results show that the proposed algorithm is accurate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.583-589
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• 2016

Volatile organic compounds(VOCs) are regarded as a harmful cause substance not only causing air pollutions but also causing global warming phenomenon. For this reason, VOCs are managed politically to reduce emissions by each country. In particular, the vapor from the gas station contains VOCs which is harmful to the human body such as carcinogens benzene and pollute the atmosphere, the Ministry of Environment defined every gas station must install vapor recovery equipment to recover volatile organic compounds. Recently, there are many accidents caused by existing vapor treatment methods, the liquefaction recovery technology is getting the spotlight to cool the vapor at the field. However, because the liquefaction recovery technology have risks of fire or explosion in accordance with temperature, the real time monitoring is critical factor. In this paper, we implement an Android-based monitoring application for liquified vapor recovery device which attached sensor module for temperature and power to monitoring real time information.

• Korean Chemical Engineering Research
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• v.54 no.3
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• pp.367-373
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• 2016

Many of plastic powders handled in industry are combustible and have the hazard of dust fire and explosion accidents. However poor information about the safe handling has been presented in the production works. The aim of this research is investigated experimentally on explosive characteristics of various plastic powders used in industry and to provide additional data with safety informations. The explosibility parameters investigated using standard dust explosibility test equipment of Siwek 20-L explosion chamber. As the results, the dust explosion index ($K_{st}$) of ABS ($209.8{\mu}m$), PE ($81.8{\mu}m$), PBT ($21.3{\mu}m$), MBS ($26.7{\mu}m$) and PMMA ($14.3{\mu}m$) are 62.4, 59.4, 70.3, 303 and 203.6[$bar{\cdot}m/s$], respectively. And flame propagation velocity during plastic dust explosions for prediction of explosive damage was estimated using a flame propagation model based on the time to peak pressure and flame arrival time in dust explosion pressure assuming the constant burning velocity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.380-386
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• 2020

The ESS load test device (ELTD) can store and exchange electrical energy during the load test of an emergency generator. On the other hand, it is difficult to commercialize ELTDs based on Li-ion batteries because of the high initial cost, which is higher than a load bank test. If the trade of electrical energy stored in ELTD during the test of an emergency generator is considered, it may be possible to commercialize the ELTD. Therefore, this paper proposes an economic model of ELTD composed of the costs and benefits by considering electrical energy trade to perform accurately economic evaluations of an ELTD. From the simulation results of the economic evaluations of an ELTD and the load bank method, it was found that the commercialization of ELTD is possible when the trade in electrical energy in ELTDs is considered.