• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.193-194
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• 2024

스마트홈과 연동하는 안전한 방범창은 외부의 침입자를 차단하고 주거 내의 물품 도난 및 개인의 신변을 보호하기 위한 안전설비로 다양한 형태의 방범창이 존재한다. 스마트홈은 건물 내의 센서가 화재를 감지하면 방범창 내부의 원격시스템이 자동으로 방범창을 매우 짧은 시간 안에 개방할 수 있도록 설계한다. 화재 등 재난시 상하부 방법창이 자동으로 개폐되도록 랙피니언을 이용하여 방범창의 위쪽 창틀을 상승시켜 창살이 움직일 수 있도록 개방하고 동시에 아래쪽 창틀이 회전하도록 구성하여 화재 및 폭우 등에 인명피해를 줄일 수 있도록 설계한다. 스마트홈 시스템과의 연계로 재난을 미리 감지하고 탈출구를 개방한다면 신속하고 안전한 대피가 가능하고, 기존의 프레임 부분 변경에 간단한 시스템만 변경하여 적용할 수 있어, 간단한 구조로 설치할 수 있고 낮은 비용으로 스마트홈을 구성할 수 있다. 특히 스마트홈과 연동하여 재난을 미리 감지하고 탈출구를 개방함으로써 신속하고 안전한 대피가 가능하여 다양한 재난을 대비할 수 있다.

• Composites Research
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• v.17 no.4
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• pp.61-67
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• 2004

Nondestructive damage sensitivity on single-basalt fiber/epoxy composites was evaluated by micromechanical technique and acoustic emission (AE). Piezoelectric lead-zirconate-titanate (PZT), polyvinylidene fluoride (PVDF) and poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) copolymer were used as AE sensor, respectively. In single-fiber composite, the damage sensing with different sensor types were compared to each other. Piezoelectric PVDF polymer sensor was embedded in and attached on the composite, whereas PZT sensor was only attached on the surface of specimen. In case of embedded polymer sensors, responding sensitivity was higher than that of the attached case. It can be due to full constraint inside specimen to transfer elastic wave coming from micro-deformation. For both the attached and the embedded cases, the sensitivity of P(VDF-TrFE) sensor was almost same as that of conventional PVDF sensor.

• Journal of IKEEE
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• v.19 no.1
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• pp.58-63
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• 2015

This study suggested the mobile intelligent management system based on the cloud service. The mobile intelligent management system are composed of cloud server, middleware and sensor networks. Each modules are controlled on mobile environment and observed operating status of each apparatus for environment. In this pater, the image-based moving detection algorithm applied in order to detect an intruder and average 12.3% are measured in moving detection experiments. it was confirmed the validity of the security device.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.373-376
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• 2019

최근 AI 기술이 학술적 연구단계를 넘어 산업계에서 활용이 확산됨에 따라, 실시간 시스템 분야에서도 AI를 접목하려는 움직임이 증가하고 있다. 실시간 시스템은 시간 제약이 있는 시스템으로써, 자율주행 시스템과 같은 안전 최우선 시스템에서는 시간 제약 위반으로 인한 예외 상황 발생 시, 심각한 피해로 이어질 수 있기 때문에 예외 상황 처리를 위한 신뢰성 있는 시스템 설계가 필요하다. 본 논문에서는 실시간 임베디드 AI를 위한 스트림 데이터 처리 언어인 Splash에 신뢰성 향상을 위한 예외 처리 메커니즘을 구현하였다. 구체적으로 예외 감지와 처리 부분으로 나눠서, 예외 상황을 감지하는 시점 및 방법을 정의하고 예외 발생 시 이를 처리하는 과정을 구현하였다. 예외 처리 메커니즘은 실시간 발행/구독 기반의 통신 미들웨어인 DDS 상에 라이브러리 형태로 구현되었으며, 시계열 센서 데이터를 사용하여 확인한 결과, 응용 개발자가 명시한 제약 사항 위반 시 발생하는 예외를 성공적으로 감지하고 예외 처리 동작을 수행하는 것을 확인하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.499-500
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• 2021

현재 4차 산업혁명의 시대로 들어서고 수많은 분야에서 사고와 안전에 관련하여 발전을 이루고 있지만, 매년 화재피해로 인한 인명손실과 재산피해는 다른 사고보다 피해와 규모가 다르며 여전히 고민해야할 숙제이다. 화재 골든타임은 화재 발생직후 5분이내의 시간을 일컫으며, 이 시간을 지키느냐 마느냐에 따라서 화재로 인한 사망자 수는 2배이상 차이가 난다. 본 논문의 화재 감지 시스템은 화재 골든타임을 지키는것에 중점을 두고 이 시스템 자체로 화재를 방지하고, 감지하여 초동조치까지 이루어질 수 있도록 화재 위험요소 차단, 화재 발생시 즉각적인 대처, 인명 피해 최소화, 2차피해 방지를 목적으로 구성되었다. 이로 인해 결과적으로 화재 골든타임을 지켜 화재를 방치시키는 상황이 줄어들 것이고, 인명피해와 재산피해까지 줄일 수 있을것이라 예상된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.524-526
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• 2021

As the video wall controller market is growing rapidly, issues that have not been addressed so far are raised. One of them is a phenomenon in which a black screen is displayed on a multi-screen. Black screen is displayed due to an error in the video being displayed in the video wall controller. Human intervention is inevitable to recognize and solve the black screen. However, it is impossible for the operator to monitor the multi-screen 24 hours a day. In this paper, we propose a model that detects the black screen being displayed on the video wall controller. We propose a CNN based architecture to detect a black screen.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.5
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• pp.499-507
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• 2004

We have studied tile detection techniques, which can determine the location and the weight of an intruder into infrastructure, by using fiber-optic ROTDR (Rayleigh optical time domain reflectometry) sensor and fiber-optic BOTDA (Brillouin Optical time domain analysis) sensor, which can use an optical fiber longer than that of ROTDR sensor Fiber-optic sensing plates of ROTDR sensor, which arc buried in sand, were prepared to respond the intruder effects. The signal of ROTDR was analyzed to confirm the detection performance. The constructed ROTDR could be used up to 10km at the pulse width of 30ns. The location error was less than 2 m and the weight could be detected as 4 grades, such as 20kgf, 40kgf, 60kgf and 80kgf. Also, fiber optic BOTDA sensor was developed to be able to detect intrusion effect through an optical fiber of tells of kilometers longer than ROTDR sensor. fiber-optic BOTDA sensor was constructed with 1 laser diode and 2 electro-optic modulators. The intrusion detection experiment was peformed by the strain inducing set-up installed on an optical table to simulate all intrusion effect. In the result of this experiment, the intrusion effort was well detected as the distance resolution of 3m through the fiber length of about 4.81km during 1.5 seconds.

• Journal of Sensor Science and Technology
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• v.11 no.4
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• pp.209-217
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• 2002

The developing of buried fiber optic sensor with high sensitivity and broad-area detecting intruders is carried out using fiber optic ROTDR(Rayleigh Optical Time Domain Reflectometry). The sensing part was designed to be able to broad-area detect intrusion effect per optical fiber length under ground. The bending light losses in optical fibers are investigated by commercial mini ROTDR with wavelength $1.55{\mu}m$, distance range 5km, pulse width 20ns, SNR=5.7. The sensing fibers are selected as the common telecommunication fibers are the 1.5mm, 3.5 mm outer diameter, 4km each length fiber products. Experiments were investigate the characteristics of signal sensitivity according to applied intrusion weight. The relation between the applied weight and the bending loss was almost linear, and broad-area detect intrusion effects are the 2m resolution and $1.3m^2$ per optical fiber length respectively. The light loss by the applied weight on fiber was 0.17 dB/kg. that the sensitivity of the optical fiber sensor was sufficient to detect intruders passing over the buried optical fiber.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.81-88
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• 2021

Structural health monitoring (SHM) systems have attracted considerable interest owing to the frequent earthquakes over the last decade. Smart concrete is a technology that can analyze the state of structures based on their electro-mechanical behavior. On the other hand, most research on the self-sensing response of smart concrete generally investigated the electro-mechanical behavior of smart concrete under a static loading rate, even though the loading rate under an earthquake would be much faster than the static rate. Thus, this study evaluated the electro-mechanical behavior of smart ultra-high-performance concrete (S-UHPC) at three different loading rates (1, 4, and 8 mm/min) using a Universal Testing Machine (UTM). The stress-sensitive coefficient (SC) at the maximum compressive strength of S-UHPC was -0.140 %/MPa based on a loading rate of 1 mm/min but decreased by 42.8% and 72.7% as the loading rate was increased to 4 and 8 mm/min, respectively. Although the sensing capability of S-UHPC decreased with increased load speed due to the reduced deformation of conductive materials and increased microcrack, it was available for SHM systems for earthquake detection in structures.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.3
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• pp.53-59
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• 2020

This paper proposes color segmentation for detecting missing persons in a smart lighting system using radar and camera sensors. Recently, smart lighting systems built-in radar and cameras have been efficient in saving energy and searching for missing persons, simultaneously. In smart lighting systems, radar detects moving objects and then the lights turn on and camera records. The video recorded is useful to find out missing persons. The color of their clothes worn in missing persons is one of critical hints to look for missing persons. Therefore, color segmentation is an effective means for detecting the color of their clothes. In this paper, during the color segmentation step, the ROI(Region of interest) setting based on the size of an object is applied and the background is reduced. According to experimental results, the color segmentation has good accuracy of more than 97%.