Design and Implementation of Remote Controlling System Using GAN in Optical Camera Communication

Abstract

This article illustrates the controlling mechanism along with data transmission using optical camera communication in both line-of-sight and non-line-of sight (NLOS) environment. The transmitter of the system is mainly composite of microcontroller (Arduino Mega), DHT sensor, two LEDs, and four push button switches. Here, two LEDs are continuously transmitting the control and data signal. The control signal is operated through push button switches. We have used four different control signals that are transmitted from the LEDs and data transmission by collecting data from the surrounding through the temperature and humidity sensor. The entire transmitter operations are processed and controlled through arduino programming in a microcontroller. The COOK modulation technique is used for this system. For data reception, we have used laptop's camera that is controlled through five different exposure times and operated based on the rolling shutter effect of the camera. A logistic regression algorithm is applied to recognize the data transmitting LED from the normalized intensity of the stripe patterns. The receiver is capable to collect data under certain conditions, if the light source is obstructed by an object through deep neural network. Again, Generative Adversial Network (GAN) is used as a decoder to reduce the BER during moving scenario and NLOS conditions. Different activation functions are used in the GAN model to find the optimum solution for the system. However, we have archived the maximum 2.5 m communication distance with 10-4 BER. The receiver program is designed using Python 3.8.

Keywords

• Optical communication
• image processing
• logistic regression
• deep neural network
• feature extraction
• camera- on-off-keying