5G and artificial intelligence integration to improve drone routing

The development of 5G and artificial intelligence technologies creates new opportunities for improving the routing of unmanned aerial vehicles, which is particularly relevant for logistics, rescue operations, and monitoring of critical infrastructure. The purpose of the study was to analyse the prospects for implementing 5G and AI in drone routing, identify key challenges, and develop recommendations for their effective integration into Ukrainian airspace. The study used methods of theoretical analysis of scientific sources, comparative analysis of international experience, and systematisation of modern approaches to drone routing using 5G and AI. The architecture of 5G networks, route optimisation algorithms, and coordination mechanisms for swarms of drones was analysed. The main results of the study showed that the combination of 5G and AI provides a significant increase in the efficiency of autonomous unmanned systems, allowing helping to quickly adapt routes, optimise energy consumption, and improve the level of flight safety. Special attention was paid to comparing two popular route optimisation algorithms for UAVs: the particle swarm and the ant colony optimisation algorithms. The analysis showed that both algorithms effectively solve routing problems, but they have their advantages depending on the specifics of the application. The particle swarm algorithm proved to be more efficient for problems with a large number of variables, helping to optimise routes in real time under rapidly changing conditions. The ant colony optimisation algorithm, in turn, demonstrated an advantage in solving complex problems with a large number of obstacles. The practical significance of the study was to identify key technical and regulatory challenges associated with the integration of 5G and AI into drone routing, and to develop evidence-based approaches to solving them. The results obtained can be used to improve national regulations, promote the introduction of intelligent unmanned systems in logistics, infrastructure monitoring and rescue operations, and for further research in the field of autonomous aviation technologies