Free Space Optical Communication and its Implementation Using

Diffractive Optical Elements Using Artificial Intelligence (AI)

Free Space Optics (FSO) is a wireless data transmission method for infrastructure

that uses laser beam energy to transmit information waves through the atmosphere. Furthermore,

due to its high bandwidth potential and simple deployment, FSO has garnered considerable

interest. However, atmospheric turbulence and misalignment present obstacles to establishing

dependable and effective FSO links.

For systems varying from space invariant to totally space variant, the optimal design of

free-space optical connectivity systems using diffractive optics is found from an engineering perspective.

Parameters such as the light's wavelength, the system's total number of optical sources and

detectors, their sizes, and their spacing are used to determine the system's volume. Another important

parameter is the diffractive lens's f-number. Diffraction Optical Elements (DOEs) have

emerged as a promising means of addressing these difficulties. Also, the patent related to automated

honey beehive box gives the insight of its monitoring system.

This paper provides an overview of the implementation and advancements of FSO systems

utilizing DOEs, including the fundamental principles, design considerations, and performance

improvements. The study discusses the basics of diffraction and the role of DOEs in FSO systems. It

explores the diffraction grating equation and the Huygens-Fresnel principle to understand wave

propagation and interference phenomena. Design considerations for FSO systems equipped with

DOEs are discussed, including the selection of appropriate DOEs and evaluation of performance

benefits. The study also investigates the application of AI methods, such as machine learning and

deep learning, in optimizing FSO systems with DOEs.

A thorough overview of Free Space Optics (FSO) systems utilizing Diffraction Optical Elements

(DOEs) is given in this review study. It examines diffraction theory and DOE use in FSO,

emphasizing their potential for beam forming, beam steering, and adaptive optics. The study examines

FSO with DOE design concerns, performance improvements, applications, and future approaches.

FSO systems may overcome problems with air turbulence, misalignment, and fading by

using the characteristics of DOEs, opening the door for dependable and effective wireless communication.

In conclusion, the effect of DOEs on BER efficiency is also modified by the obscuration

ratio. Transmission power is increased when more DOEs are used by an amount defined by their

obscuration ratios. Additionally, because of the increased power complement in these systems, the

effect of DOEs is more pronounced. The integration of AI further enhances FSO capabilities by

providing adaptive optimization, fault detection, predictive maintenance, and improved security.

Future research directions may include exploring advanced AI techniques and conducting practical

implementations of FSO systems with DOEs for various applications, particularly in Internet of

Things (IoT) scenarios.