• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.715-722
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• 2019

This paper introduces the implementation of an user-aware system using a visible light communication and its operations. The user-aware system using a visible light communication consists of the transmitter based on the Android system and the receiver based on an open-source controller. In the transmitter, user's personal information data is encoded and converted to visible light signals by the Android camera interface. In the receiver, the photodiode module receives the incoming visible light signals and converts to electrical signals and the open-source controller, that is arduino processes the received data. The processing module finds the start bit of 0111 to determine the user information data from the packet for the burst-mode communication. According to the experimental results, the proposed system successfully transmits and receives visible light data with the manchester encoding.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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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.

• Proceedings of the IEEK Conference
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• 1998.10a
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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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• v.8 no.1
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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.