• International Journal of Internet, Broadcasting and Communication
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• 제7권2호
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• pp.51-55
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing dangerous situation. The proposed method firstly extracts the facial region using Harr-like technique from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, detects facial expression, and recognizes dangerous situation. The proposed method is evaluated for MUCT database image and web cam input. The proposed method produces good results of facial expression and discriminates dangerous situation well and the average recognition rate is 91.05%.

• 한국멀티미디어학회논문지
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• 제22권1호
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• pp.62-69
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• 2019

In this paper, we propose iZone system for safe walking of children. The proposed system recognizes the state that a child is down a roadway as a dangerous situation. And then it informs the surrounding adults and guardians of the child in the event of a dangerous situation. The iZone system consists of the iZone device that attaches to a child's bag or clothing, the iZone app for children, the iZone server, and external beacons. The proposed system uses the ultrasonic sensor of the iZone device and the GPS coordinates and external beacons information by the children's smartphone to determine the dangerous situation. The proposed system uses external beacons to calibrate the GPS coordinates. Moreover, it determines whether the child is down the roadway in sidewalk by measuring the height difference between the roadway and the sidewalk using ultrasonic sensor.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.798-799
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• 2016

기존의 시약장의 경우 시약들을 성상 별로 분류하지 않고 관리하게 되면 위험 상황이 발생할 수 있는 문제점이 있다. 또한 위험 상황 발생 시 외부에서 시약장을 제어할 수 있는 기능이 미비한 실정이다. 본 논문에서는 시약들을 관리하기 위해 성상 별로 분류하고 모바일 디바이스에서 시약장을 관리할 수 있는 시스템을 설계한다. 성상 분류를 통해 제 1류에서 제 6류까지 각 시약들을 분류에 맞게 관리하고 모바일 디바이스에서는 센서 제어, 시약 및 센서 데이터 모니터링, 위험 상황 발생 시 알람 메시지를 전송한다. 이로 인해 성상 분류를 통하여 연구실 내 사고를 줄이고 위험 상황 발생 시 외부에서도 신속한 대처가 가능할 것으로 사료된다.

• 한국정보통신학회논문지
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• 제21권1호
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• pp.193-198
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• 2017

최근 건강에 대한 관심이 증가함에 따라 사용자의 생체정보를 측정할 수 있는 스마트 워치와 스마트 밴드 등 다양한 웨어러블 디바이스(Wearable Device)들이 연구되고 있다. 그러나 기존의 웨어러블 디바이스들은 측정된 생체정보를 단순 모니터링이나 질병 예방법, 운동량 등을 제공하는 형태로만 서비스하고 있어 실제 사용자가 위험상황이 발생할 경우에 대한 대처는 미흡한 실정이다. 이에 본 논문에서는 이러한 문제점을 해결하기 위해 위험상황 알림 시스템을 제안한다. 아두이노를 통해 가속도 센서와 심박 센서로 측정된 생체정보를 실시간으로 어플리케이션에 전송하고 센서 우선순위 측정과 위험상황 식별 알고리즘을 통해 위험상황을 식별한 후 위험상황이 발생하면 보호자에게 사용자의 현재 위치를 알림 메시지를 전송한다. 이에 따라 보호가 필요한 사용자에게 위험한 상황이 발생하면 신속하게 대처할 수 있을 것으로 사료된다.

• 한국멀티미디어학회논문지
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• 제18권3호
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• pp.408-418
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• 2015

This paper describes the design and implementation of situation recognition system with smart phone sensors, which recognizes the dangerous situation at anytime, anywhere through intuitive data analysis of the combination of the sensor. The implemented system consists of wearable heart rate sensor and acceleration sensor of smart phone instead of existing sensor that is attached to the body. It is also designed to get more effective results of recognition about the dangerous situation using merged displacement values of acceleration sensor and heart rate sensor which are measured in the process of recognizing dangerous situations. This research, in accordance with the wide penetration of smartphones, achieves the fast status determination through the combination of an acceleration sensor and a heart rate sensor applied to its own status perception algorithm for anyone who needs the stable perception of risk without the need for a separate provision of the sensor.

• 공학교육연구
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• 제13권5호
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• pp.36-40
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• 2010

The vehicle oriented block box system based on the u-healthcare and the human-free guard functions is developed in this paper. We also suggested the design philosophies, ideas, and analyzed the performance of the suggested system. The developed vehicle oriented black box system has some characteristics such as; 1) detects the dangerous situation by ultrasonic sensor in advance, and stores the situation information of the neighborhood of the vehicle to the imbedded SD memory card if the dangerous situation may be occurred in the parked vehicle; 2) detects the present location and speed information of the vehicle by GPS receiver and 3-axes acceleration sensor, and stores the information to the SD memory card periodically if the vehicle is running; 3) measures the dioxide carbon in the vehicle inside using $CO_2$ sensor, and forces the ventilation motor of the vehicle to operate and maintains the driver's health if the measured level is more than standard health requirements; 4) provides the stored vehicle's operating information to the driver by GUI (Graphical User Interface) based touch LCD monitor.

• 한국멀티미디어학회논문지
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• 제24권3호
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• pp.345-354
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• 2021

Recently, deep learning-based image recognition systems have been adopted to various surveillance environments, but most of them are still picture-type object recognition methods, which are insufficient for the long term temporal analysis and high-dimensional situation management. Therefore, we propose a method recognizing the specific dangerous situation generated by human in real-time, and utilizing deep learning-based object analysis techniques. The proposed method uses deep learning-based object detection and tracking algorithms in order to recognize the situations such as 'trespassing', 'loitering', and so on. In addition, human's joint pose data are extracted and analyzed for the emergent awareness function such as 'falling down' to notify not only in the security but also in the emergency environmental utilizations.

• Journal of the Optical Society of Korea
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• 제14권4호
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• pp.451-457
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• 2010

Increasing demands on the safety of public train services have led to the development of various types of security monitoring systems. Most of the surveillance systems are focused on the estimation of crowd level in the platform, thereby yielding too many false alarms. In this paper, we present a novel security monitoring system to detect critically dangerous situations such as when a passenger falls from the station platform, or when a passenger walks on the rail tracks. The method is composed of two stages of detecting dangerous situations. Objects falling over to the dangerous zone are detected by motion tracking. 3D depth information retrieved by the stereo vision is used to confirm fallen events. Experimental results show that virtually no error of either false positive or false negative is found while providing highly reliable detection performance. Since stereo matching is performed on a local image only when potentially dangerous situations are found; real-time operation is feasible without using dedicated hardware.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.488-490
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• 2022

최근 산업안전보건법, 중대재해처벌법 등과 같은 산업재해에 관한 관심이 증가하는바, 연구 기관과 각계의 산업 분야에서 근로자의 안전 관리에 대한 안전 관리자의 수요가 늘고 있는 실정이다. 근로자 안전 관리를 위해 공장, 작업장에 CCTV를 증설하고 있으며 작업자를 모니터링하여 안전에 대한 관리를 높이고 있다. 본 논문에서는 이러한 작업장의 CCTV를 활용해 데이터를 구축하고 JSON 형태로 모델링하여 위험 상황 판정 시스템을 설계하고자 한다. 데이터 모델링은 한국지능정보사회진흥원의 인공지능 학습용 데이터셋 구축 안내서와 품질 관리 가이드라인을 참고하여 제작하였다. 이러한 시스템을 통해 위험 상황 시나리오별로 작업장에 어떠한 위험 관리가 존재하고 있는지를 확인하여 더욱 체계적인 시스템 구축에 활용하고자 한다.

• 한국멀티미디어학회논문지
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• 제23권2호
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• pp.282-292
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• 2020

In order to minimize casualties from marine vessel accidents that occur frequently at home and abroad, it is important to ensure the safety of the passengers aboard the vessel in the event of an accident. There is an EPIRB system as a system for disaster preparedness in the marine situation currently on the market, but there is a problem that the price is very expensive. In order to overcome the cost problem, which is a disadvantage of previous system, LoRaWAN-based communication is used. LoRaWAN communication-based vessel positioning and risk detection system based on LoRaWAN communication transmits measurement data of each module using two Beacon and GPS modules to stably perform position measurement for both indoor and outdoor situations. The rider danger situation detection system can detect the safety status of the rider using the 3-axis acceleration sensor, collect data from the rider positioning system and the rider safety status detection system, and send to server using LoRa communication. When conducting communication experiments in the long-distance maritime situation and actual communication experiments using the implemented system, it was found that the two experiments showed over 90% communication success rate on average.