• Journal of Korean Society of societal Security
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• v.2 no.4
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• pp.19-20
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• 2009

• 한국도로학회지:도로
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• v.17 no.2
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• pp.55-64
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• 2015

• Korea Information Processing Society Review
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• v.15 no.1
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• pp.90-98
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• 2008

• Fire Science and Engineering
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• v.4 no.2
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• pp.89-94
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• 1990

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.237-238
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• 2016

대부분의 작업환경에서는 여러 가지 위험요소로 인한 안전사고가 자주 발생한다. 추락이나 작업환경의 붕괴 등 안전사고 발생시, 작업자가 관리자에게 응급상황을 전해야하지만, 사고로 인해 작업자가 원활하게 몸을 사용하지 못하는 경우에는 응급상황을 전달하는데 문제점이 발생한다. 본 논문에서는 이러한 문제를 해결하기 위해서 블루투스로 스마트폰에 응급상황을 전할 수 있는 웨어러블 단말기와 스마트폰의 WI-FI나 LTE망을 사용하여 작업자의 상황을 실시간으로 모니터링 할 수 있는 안전 시스템을 설계한다.

• Information and Communications Magazine
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• v.34 no.6
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• pp.58-64
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• 2017

공공안전을 위한 ICT 시스템에 있어서 응급 상황의 전력 지원은 매우 중요한 문제이다. 특히 전력 인프라가 취약한 산악 지역 등 야외 환경에서 발생하는 안전 사고의 빈도를 고려하면, 공공 안전을 목적으로 하는 ICT 응용 기술은 비상시의 전력 공급을 반드시 염두에 두고 개발되어야 할 필요가 있다. 본 고에서는 효과적인 에너지 변환 방법에 기반한 양질의 전력 생성과 더불어, 휴대성과 사용 편의성을 극대화하기 위한 착용 형태의 동적 에너지 수확기를 제안하였다. 개발된 착용형 에너지 수확기의 프로토타입은 최대 3W, 평균 0.3W 수준의 양질의 출력이 가능하며, 무엇보다 사용자가 모바일 기기를 사용하는 데 불편함을 주지 않으면서 동시에 전기에너지 생성이 가능함을 입증하였다. 향후 연구를 통해 공공 안전의 여러 이슈에 대응 가능한 응급 상황 지원 기술로 개발할 예정이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.807-809
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• 2020

기존의 CCTV 관리 체계는 사건·사고에 대한 신속한 조치가 불가능하고 정황 파악이나 증거자료 확보 등 사후조치의 성격이 강하다. 본 논문에서는 Mask R-CNN(Regions with CNN)을 이용하여 CCTV가 읽어 들이는 객체가 응급상황인지 판단하는 방법을 제시한다. 사람으로 인식되는 영역을 다층 퍼셉트론(MLP, Multi-Layer Perceptron)으로 학습시켜 해당 대상이 처한 상황을 인지하고 응급상황으로 인식되는 상황이 지속될 경우 관리 모니터를 통해 사용자에게 알림을 준다. 본 연구를 통해 실시간 상호작용적인 CCTV 관리 체계를 구축하여 도움이 필요한 사람의 골든타임을 놓치지 않게 될 것으로 기대한다.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.225-236
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• 2010

This study proposes a method for the recognition of emergency situation according to the bimodal information of camera image sensor and gravity sensor. This method can recognize emergency condition by mutual cooperation and compensation between sensors even when one of the sensors malfunction, the user does not carry gravity sensor, or in the place like bathroom where it is hard to acquire camera images. This paper implemented HMM(Hidden Markov Model) based learning and recognition algorithm to recognize actions such as walking, sitting on floor, sitting at sofa, lying and fainting motions. Recognition rate was enhanced when image feature vectors and gravity feature vectors are combined in learning and recognition process. Also, this method maintains high recognition rate by detecting moving object through adaptive background model even in various illumination changes.

• The Korean Journal of Emergency Medical Services
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• v.28 no.1
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• pp.63-76
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• 2024

Purpose: To analyze trends related to demography and EMS and to provide supporting data for the appropriate deployment of EMS providers. Methods: In this cross-sectional study, data on patients transported by 119 EMS, demographics, and EMS factors were collected using the Korean Statistical Information Service (KOSIS) and the National Fire Agency annual report from 2017 to 2021. Results: During the study period, the total number of patients and those with severe disorders transported via 119 EMS showed an increasing trend. The total fertility rate and population during the same period tended to decrease, and the population density and number of households increased; however, there was a disparity between regions. The main demographic factors affecting the number of patients transported were population density and total fertility rate, while the main EMS factors were the number of ambulances and provision of emergency medical information services(hospital guidance, pharmacy information, and first aid guidance). Conclusion: From the perspective of EMS providers' force deployment, it is necessary to consider population density, population, number of households, total fertility rate, and number of emergency medical institutions and to strengthen the role of diverting the use of 119 EMS by minor patients by providing emergency medical information.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.99-107
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• 2021

With the recent establishment of a ubiquitous-based medical and healthcare environment, the medical information system for obtaining situation information from various sensors is increasing. In the medical information system environment based on context-awareness, the patient situation can be determined as normal or emergency using situational information. In addition, medical staff can easily access patient information after simple user authentication using ID and Password through applications on smart devices. However, these services of authentication and patient information access are staff-oriented systems and do not fully consider the ubiquitous-based healthcare information system environment. In this paper, we present a authentication service model based context-awareness system for providing situational information-driven authentication services to users who access medical information, and implemented proposed system. The authentication service model based context-awareness system is a service that recognizes patient situations through sensors and the authentication and authorization of medical staff proceed differently according to patient situations. It was implemented using wearables, biometric data measurement modules, camera sensors, etc. to configure various situational information measurement environments. If the patient situation was emergency situation, the medical information server sent an emergency message to the smart device of the medical staff, and the medical staff that received the emergency message tried to authenticate using the application of the smart device to access the patient information. Once all authentication was completed, medical staff will be given access to high-level medical information and can even checked patient medical information that could not be seen under normal situation. The authentication service model based context-awareness system not only fully considered the ubiquitous medical information system environment, but also enhanced patient-centered systematic security and access transparency.