This study deals with the problem of fiber-free optical communication systems—known as free space optics—using received signal strength identifier (RSSI) prediction analysis for hard switching of optical fiber-free link to base radio-frequency (RF) link and back. Adverse influences affecting the atmospheric transmission channel significantly impair optical communications, therefore attention was paid to the practical design, as well as to the implementation of the monitoring device that is used to record and process weather information along a transmission path. The article contains an analysis and methodology of the solution of the high availability of the optical link. Attention was paid to the technique of hard free space optics (FSO)/RF-switching with regard to the amount of received optical power detected and its relation to the quantities influencing the optical communication line. For this purpose, selected methods of machine learning were used, which serve to predict the received optical power. The process of analysis of prediction of received optical power is realized by regression models. The study presents the design of the optimal data input matrix model, which forms the basis for the training of the prediction models for estimating the received optical power.

In this paper a collection of technical solutions and results of simulation, supporting the concept of management a small group of unmanned aerial vehicles such as drones, are presented. The focus is given on collision avoiding and communications. The anti-collision system utilises the drone camera and is built on the Robot Operating System using the Histogram of Oriented Gradients and the Support Vector Machine. The proposed inter-drone communication employs ZigBee for system management and telecommunication networks for data exchange and teleoperations.

The purpose of this paper is to describe an example of home automation system utilising electromagnetic interference-free Li-Fi optical wireless communications. The proposed home automation system solution is built upon KNX, which is one of the global industry-adopted building automation standards. The experimental setup was developed using Raspberry Pi minicomputers while communication modules were built using Arduino boards. Communication range was within ten meters which is sufficient for the majority of home automation cases.

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