Abstract
The purpose of this study was to adaptively optimise sensor networks using unmanned aerial vehicles to reduce information losses and ensure the minimum possible technical performance of information transmission channels in the face of a considerable number of architectural obstacles. In this study, experiments were conducted on data transmission via a wireless channel using Wi-Fi technology, where the access point was placed on an unmanned aerial vehicle. The study was conducted in complex architectural settings, using the 2.4 GHz and 5 GHz frequency bands to investigate the behaviour of radio channels and assess their effectiveness in real-world conditions. As a result of the study, a new method for estimating and optimising the energy parameters of radio channels was proposed, which accommodates the influence of a range of factors to improve the coverage efficiency of wireless sensor networks based on unmanned aerial vehicles. This method helped to partially solve the problem of information losses through adaptive optimisation of network coverage when influencing factors occur. The experimental models developed in this study allow estimating the signal distribution in space for sensor networks based on unmanned aerial vehicles, considering the influence of external factors, using fluctuation coefficients. The study also developed a mechanism for using a control device that allows measuring signal strength at any distance from the base station, providing flexibility and accuracy of assessment. The results showed a prominent level of measurement accuracy, with 95% reliability for an observation period of 20 seconds and an error of up to ±0.5 dBm. The total error of the methodology does not exceed 5%, which confirms the high reliability of the results and their compliance with real operating conditions. Thus, the findings of this study contribute to improving the efficiency and reliability of wireless sensor networks based on unmanned aerial vehicles, providing stable and high-quality connection in various operating conditions