## 3 Recording of Atmospheric Conditions Using a Weather Monitoring Station to Predict RSSI Value
### Recording of Atmospheric Conditions Using Unmanned Aerial Vehicle (ULAV)  
This sensor system plays a significant role in the deployment of FSO technology in critical situations. If necessary, this technology can be used within minutes to analyze and map the appropriate location of the FSO head. It will allow us to quickly detect an unfavorable environment for this technology and the subsequent deployment of a secondary RF communication line. It is a technology suitable for rapid deployment in the field. The sensor system can also be used in hard-to-reach places or life-threatening places without the need to shut down these dangerous factors. The sensor system focuses on three basic factors affecting the ability to use FSO. It will detect humidity and ambient temperature, as at high temperatures near water areas there is a high probability of mist and water particles in the air absorbing or scattering the laser beam, resulting in inefficient or even impossible use of FSO technology in the area. Furthermore, the system detects the presence of dust particles in the air. These particles have the most significant effect on the FSO capability of the head. If there is a high occurrence of polluting particles in the air, the beam can be greatly attenuated or even completely interrupted, which is the most unfavorable scenario. The most important part of this system is the ability to map the environment and then plot it in Google Earth with the appropriate air quality values. The actual connection of the sensor system can be seen in Figure 4.  
From information about air pollution obtained by drone survey flights in several areas, we obtained sufficient data to analyze air quality and its impact on the FSO communication line. The acquisition of the necessary data took place in two localities. The first location was the premises of the Technical University in Kosice; several reconnaissance flights took place \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Physical Quantity** & **Indication** & **Sensor Name** & **Units** \\ \hline Signal Strength & RSSI & Flight Strata 155E & dBm \\ Visibility & VI & miniOFS & m \\  & TE1 & gp2y1010 au & \({}^{\circ}\)C \\ Temperature & TE2 & DS18B20 & \({}^{\circ}\)C \\  & TE3 & DHT22 & \({}^{\circ}\)C \\ Concentration of particles in the air & KC & gp2y1010 au & \(\upmu\)g/m\({}^{3}\) \\ Wind Speed & RV1 & Anemometer & m/s \\ Wind Voltage & RV2 & Anemometer & m/s \\ Humidity & VL & DHT22 & \% \\ Pressure & TL & BMP183 & hPa \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of sensors. Figure 3: FSO head FlightStrata 155E with backup RF line and weather monitoring station. here. The survey was conducted to design the location of FSO technology as an extension of the existing communication network. The first and second columns describe latitude and longitude, and the third to fifth columns describe the measured value of temperature, humidity, and dust particles in the air. Temperature was measured in degrees Celsius (\({}^{\circ}\)C), humidity in percent (%), and air pollution in micrograms per cubic meter (\(\mathrm{\SIUnitSymbolMicro g}/\mathrm{m}^{3}\)). The Google Earth Pro location data processing program was used to display the research results on the map. In Figure 5 it is possible to see the whole assembly of the UAV device together with the weather monitoring station and Figure 6 shows the legend to the map shown in Figure 7  
Measurements of air pollution and the presence of airborne particles were successful. No disturbing air quality data were found on the premises of the TUKE. The values of particles in the air did not exceed 800 \(\upmu\)g/m\({}^{3}\), which means only average pollution. The number of measured values in space is easily visible on the map in Figure 7. The individual points shown on the map represent the measurement points. The measurement was performed every 5 s and then assigned to the position based on continuity of time. Table 2 shows sample data for processing in graphical Google Earth.