Browsing by Author "Smishchuk, Bogdan Mykolayovych"

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    Improving Mesh Network Efficiency for UAV Control Using Machine Learning
    (National Aviation University, 2024-06-15) Smishchuk, Bogdan Mykolayovych; Сміщук, Богдан Миколайович
    In recent years, unmanned aerial vehicles (UAVs) have become an integral part of many industries, including agriculture, environmental monitoring, rescue operations, logistics, and military operations. Their ability to perform complex tasks in conditions where human presence may be dangerous or impossible significantly increases the efficiency and safety of operations. However, a reliable communication system capable of adapting to changing environmental conditions is needed to coordinate many UAVs and ensure their smooth operation. Mesh networks are a promising technology for creating such communication systems, as they are characterized by a decentralized structure and the ability to self-organize. These networks are resistant to the failure of individual nodes and provide uninterrupted communication even in difficult conditions. However, to get the most out of mesh networks, the network protocols that control routing and data transmission must be optimized. The application of machine learning techniques offers the potential to optimize network protocols in cellular networks. The application of machine learning algorithms allows analyzing a significant amount of data about the state of the network and its environment in real time. This data is used to automatically adjust network parameters for optimal performance. This leads to improvements in key performance metrics such as latency, throughput and power consumption, which are vital for effective UAV control. The relevance of this topic is due to the need to develop modern technologies that will ensure high reliability and efficiency of UAV control systems. As the popularity and importance of UAVs in various industries continues to grow, optimization of network protocols using machine learning is becoming a critical task. The use of unmanned aerial vehicles in different areas requires the use of different communication and control methodologies. This requires coordination and rapid exchange of information between devices. In the context of rescue operations, the possibility of fast and reliable communication is of paramount importance to save lives. In military operations, the reliability of communication between UAVs is of primary importance for the successful execution of missions. Therefore, research on improving the efficiency of mesh networks for controlling UAVs using machine learning is timely and important, as it meets the modern challenges and needs of the development of unmanned systems. Optimizing communication systems using the latest technologies will significantly increase the efficiency and reliability of UAVs, which will contribute to their wider use and increase the overall level of safety and productivity.