• 한국전자통신학회논문지
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• 제14권4호
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• pp.715-722
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• 2019

본 논문은 가시광 통신을 이용한 사용자 인식 시스템의 구현 방법과 시스템 동작 결과를 소개하고 있다. 가시광 통신을 이용한 사용자 인식 시스템은 안드로이드 시스템 기반의 송신부와 오픈소스 컨트롤러 기반의 수신부로 나뉘어져 있다. 송신부 모듈에서는 사용자의 개인 인식 정보 데이터를 코드로 변환하고 이를 안드로이드 기반의 스마트폰 카메라 인터페이스를 사용하여 가시광으로 변환하여 수신부로 전송한다. 수신부에서는 포토다이오드 모듈을 통해 가시광을 수신하고 이를 전기신호로 변환한다. 수신 데이터에 대한 프로세싱 모듈역할은 오픈소스 컨트롤러가 맡게 되며, 본 시스템에서는 AVR 마이크로 컨트롤러 기반의 아두이노를 사용하였다. 버스트모드(burst mode) 방식의 통신이 가능하도록 0111의 비트 패턴을 스타트비트로 설정하고 이를 인식하도록 하였다. 실험 결과, 제안하는 시스템은 가시광을 매개로 맨체스터 데이터 인코딩 (Manchester data encoding)방식의 데이터 송신과 수신이 가능함을 확인하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권2호
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• pp.8-14
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• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.413-416
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• 1998

Sensitivity and calibration considerations are most important in the design and implementation of real control systems. Ideally parameter changes due to various causes should not appreciably affect the system's performances. But all the values of physical components of the plants and controllers as well as the relevant environmental conditions change in time, thus the output performance can be deteriorated during the operating span of the system. Naturally the duty of calibration or the prevention of performance deterioration due to excessive component sensitivity should be provided to the control system. In this paper, we propose a digital controller which has the capability of calibration and gain adjustment as well as the execution of control law. Specifically the problems of gain adjustment and offset calibration in the light source and CdS sensor module for position measurement in a flexible link system are considerably resolved. The parameters of measurement module are prone to change due to environmental brightness conditions resulting in poor steady state performance of the overall control system. Thus a proper method is necessary to provide correction to the changed values of gain and offset in the position measurement module. The proposed controller, whenever necessary, measures the open-loop characteristics, andthen calculates the offset and sensor gain correction values based on the prepared standard measurements. It is applied to the control of a flexible link system with the gain and offset calibration porblems in the light sensor module for position to show the applicability.

• International Journal of Advanced Culture Technology
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• 제8권1호
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• pp.207-212
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• 2020

The human centric lighting (HCL) control is a major focus point of the smart lighting system design to provide energy efficient and people mood rhythmic motivation lighting in smart buildings. This paper proposes the HCL control using indoor surveillance camera to improve the human motivation and well-beings in the indoor environments like residential and industrial buildings. In this proposed approach, the indoor surveillance camera video streams are used to predict the day lights and occupancy, occupancy specific emotional features predictions using the advanced computer vision techniques, and this human centric features are transmitted to the smart building light management system. The smart building light management system connected with internet of things (IoT) featured lighting devices and controls the light illumination of the objective human specific lighting devices. The proposed concept experimental model implemented using RGB LED lighting devices connected with IoT features open-source controller in the network along with networked video surveillance solution. The experiment results are verified with custom made automatic lighting control demon application integrated with OpenCV framework based computer vision methods to predict the human centric features and based on the estimated features the lighting illumination level and colors are controlled automatically. The experiment results received from the demon system are analyzed and used for the real-time development of a lighting system control strategy.