• Journal of the Korean Society for Railway
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• v.10 no.3 s.40
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• pp.290-295
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• 2007

The Seoul Metropolitan Subway Corp. have gradually installed screen doors in platforms of 115 subway stations in Seoul on lines 1, 2, 3, and 4. Installation in nine areas among those has been completed and screen doors are being operated as a model operation. Traffic signs should be clear for users. The essential functions of signs should be fully investigated from the aspect of user as well as the visual beauty and recognition. Signs should be able to provide users with information regarding location, position, directions, etc. Particularly, safety and convenient signs should be visually and sensually correlated. However, the entire screen doors in platforms installed in line 2 subway in Seoul are used for commercial advertisement, consequently, the functions and roles as public signs are not fulfilled aggravating inconvenience for users. In this study, cases have been studied to investigate requirements for user-oriented sign system in platform and public sign space to fulfill the functions of sign system in platform. Using an anthropometry approach, the study aimed to obtain the space to install the sign system and to systemize necessary and sufficient conditions for user-oriented system for platform in which screen doors have been installed using. The study suggests fundamental information to obtain the space of public sign system on the entire screen door.

• Annual Conference of KIPS
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• 2020.11a
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• pp.251-254
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• 2020

매년 1인 가구를 대상으로 한 범죄가 증가하고 있다. 이에 따라 지문인식, 스마트키와 같은 도어록 제품들이 출시되었지만 오히려 범죄에 악용되는 사례들이 발생하였다. 본 논문에서는 얼굴인식장치(face identifier, FI)를 통해 객체를 인식하고, 원격 도어록 관리자(remote door lock manager, RDM)를 통해 잠금제어부(locking control unit, LCU)를 관리하는 긴급 상황 인식 스마트 도어록을 제안한다. 사용자의 얼굴을 얼마나 빠르고 정확하게 인식하는지 속도와 신뢰도에 대한 테스트를 진행하였고, 긴급 상황 시 사용자가 안전하게 집으로 들어갈 수 있음을 확인하였다. 본 제품을 통해 주거 침입, 스토킹 등 1인 가구 대상 범죄율과 도어록 악용 범죄율이 낮아질 것으로 사료된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.267-274
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• 2018

This paper introduces a smart door system composed of security system and secretary system. As ratio of single households increase, the security of household became more important. Also already there were a lot of artificial intelligence secretary system based on voice called smart home technology. But It has limits. It can not work without user's requests. That mean it is not automatic. And the voice recognition depend on user's pronounce. Thus in this paper, we design and develop smart door system that is added function of security and secretary. That can inform users that there are outsider in front of their house in real time. Also that can speak information such as user's requirements, delivery and weather information using TTS. As a result they can prevent crimes and use convenient secretary system.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.174-179
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• 2018

Currently, various security technologies such as fingerprint recognition and face recognition are being developed. However, although many technologies have been developed, the field of incorporating technologies is quite limited. In particular, it is easy to adapt modern security technologies into existing digital systems, but it is difficult to introduce new digital technologies in systems using analog systems. However, if the system can be widely used, it is worth replacing the analog system with the digital system. Therefore, the selected topic is the electronic attendance system. In this paper, a camera is installed to a door to perform a Haar-like feature training for face detecting and real-time face recognition with a Eigenface in principal component analysis(PCA) based face recognition using raspberry pi. The collected data was transmitted to the smartphone using wireless communication, and the application for the viewer who can receive and manage the information on the smartphone was completed.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2363-2374
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• 2016

Communication occurs through verbal elements, which usually involve language, as well as non-verbal elements such as facial expressions, eye contact, and gestures. In particular, among these non-verbal elements, gestures are symbolic representations of physical, vocal, and emotional behaviors. This means that gestures can be signals toward a target or expressions of internal psychological processes, rather than simply movements of the body or hands. Moreover, gestures with such properties have been the focus of much research for a new interface in the NUI/NUX field. In this paper, we propose a method for recognizing the number of fingers and detecting the hand region based on the depth information and geometric features of the hand for application to an NUI/NUX. The hand region is detected by using depth information provided by the Kinect system, and the number of fingers is identified by comparing the distance between the contour and the center of the hand region. The contour is detected using the Suzuki85 algorithm, and the number of fingers is calculated by detecting the finger tips in a location at the maximum distance to compare the distances between three consecutive dots in the contour and the center point of the hand. The average recognition rate for the number of fingers is 98.6%, and the execution time is 0.065 ms for the algorithm used in the proposed method. Although this method is fast and its complexity is low, it shows a higher recognition rate and faster recognition speed than other methods. As an application example of the proposed method, this paper explains a Secret Door that recognizes a password by recognizing the number of fingers held up by a user.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.837-846
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• 2003

This paper deals with plain figures on the architectural drawings of apartment. This kind of architectural drawings consist of main walls represented by two parallel bold lines, symbols (door, window, $\cdots$), dimension line, extension line, and dimensions represent various numerical values and characters. This paper suggests a method for recognizing main wall which is a backbone of apartment in an architectural drawing. In this thesis, the following modules are realized : an efficient image barbarization, a removal of thin lines, a vectorization of detected lines, a region bounding for main walls, a calculation of extension lines, a finding main walls based on extension line, and a field expansion by searching other main walls which are linked with the detected main walls. Although the windows between main walls are not represented as main walls, a detection module for the windows is considered during the recognition period. So the windows are found as a part of main wall. An experimental result on 9 different architectural drawings shows 96.5% recognition of main walls and windows, which is about 5.8% higher than that of Karl Tombre.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.30-36
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• 2016

Recently, digital doorlock systems have been employing biometric recognition and smartphone as personal authentification means. The performance of a digital doorlock system is determined by the two conflicting indices such as security and convenience. This paper proposes and implements one grip based doorpull shaped doorlock systems using fingerprint and touch sensor grip pattern. The proposed system sequentially performs fingerprint recognition and grip pattern identification when a user grips the doorpull in order to open the door. This method so called 'One Grip' is considered to enhance security while maintaining users' convenience. We expect the proposed method can solve the phone missing problem encountered in developing smart doorlock systems based on smartphones.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.495-505
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• 2009

Unpaid Family Worker is blind area of industry safety. Danger of industrial accident is some high but because was excepted in industrial accident compensation insurance application. In most case, because paltry Unpaid Family Worker is no opportunity to take safety education to prevent industrial accidents and there are few safety facility and safety equipment, etc., among business, it may be said that probability to suffer industrial accidents on a trifling mistake or carelessness is higher than general worker of business. Consider such difficult actuality of Unpaid Family Worker and our country must give these benefit of industrial accident compensation insurance application, as opened the door of insurance application in recognition of worker position by "Industrial accident compensation insurance Law" to middle·smaller enterprise's business proprietor or special form labor employees.