• Annual Conference of KIPS
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• 2019.10a
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• pp.502-505
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• 2019

노인들이 많이 이용하는 이동 보조 기구인 기존 보행기에 다양한 기능이 부족하여 안전 서비스, 알림 서비스, 스마트폰 애플리케이션 서비스로 분류하여 기능을 추가하였다. 안전 서비스 부문의 기능으로는 경사로 사고 방지 시스템, 장애물 알림 시스템, 밝기에 따른 전조등 시스템, 손잡이에서 손이 떨어지면 자동으로 동작되는 브레이크 시스템, 겨울철 손을 따뜻하게 유지하기 위한 난방 시스템이 있다. 알림 서비스로는 현재의 온·습도 및 미세먼지 농도를 알려준 후 외출하기에 부적합할 시 경고등으로 알려주는 시스템이 있다. 스마트폰 애플리케이션 서비스는 심박 및 체온을 알려주고, 노인의 위치와 SOS신호, 운동량을 알 수 있고, 도난 방지 시스템이 있는 스마트 안전 노인 보행기를 설계하였다.

• Annual Conference of KIPS
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• 2022.11a
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• pp.815-817
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• 2022

This paper is about the development of an automatic stair climbing trolley for carrying loads without manpower. The design of tri-wheeled structure and center of mass enable the trolley to move on flat ground and also to ascend stairs by self-balancing. The overall design enables the trolley to avoid collision to walls when the trolley rotates on domestic landings. When the camera recognizes the stair, the sensor measures distance from the trolley to the stair. Then the trolley can move to align itself in the middle of the stair and it starts climbing. It can ascend to a specific floor based on the floor number entered by the user. As a result, the automatic stair climbing trolley is expected to help humans by protecting from accidents of dropping loads and saving their power. It is also expected to use for various purposes such as delivering packages, moving and carrying heavy loads in buildings without elevator.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.859-864
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• 2017

IoT is a new emerging technology to lead the $4^{th}$ industry renovation and has been widely used in industry and home to increase the quality of human being. In this paper, IoT based face detection and recognition system for a smart elevator is developed. Haar cascade classifier is used in a face detection system and a proposed PCA algorithm written in Python in the face recognition system is implemented to reduce the execution time and calculates the eigenfaces. SVM or Euclidean metric is used to recognize the faces detected in the face detection system. The proposed system runs on RaspberryPi 3. 200 sample images in ORL face database are used for training and 200 samples for testing. The simulation results show that the recognition rate is over 93% for PP+EU and over 96% for PP+SVM. The execution times of the proposed PCA and the conventional PCA are 0.11sec and 1.1sec respectively, so the proposed PCA is much faster than the conventional one. The proposed system can be suitable for an elevator monitoring system, real time home security system, etc.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.783-793
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• 2015

TV display which existed only in house started to show up out of house around us and now it found naturally its place in everywhere like street, bus, subway and elevator. It is called digital signage which showed up through digitalization of sign, that is, sign board and bulletin board. The distinction of digital sign from existing signs is that the latter one should go through physical process like removal after installation every time its contents are changed but the former one can produce its various outputs flexibly once it is installed. Also existing sign may be static image or 2 or 3 pieces of image to express simple motion while digital sign can contain multi media contents luxurious in design and motion. This paper confined the range of contents in digital signage in bus and subway. It needs to analyze characteristics of mass transportation-people of use, consumer by place and time, accommodation environment for consumer etc and arrange planned contents along with time and place. Developments of dedicated contents suitable to those digital signages will harmonize with place and time and promote the realm of digital signage which provides variety of experience to consumer and with which communication is possible and which is distinctive. Furthermore we may expect the birth of smart signage as a new media, in which fun and art are combined.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.