A DYNAMIC INTERACTION MODEL OF UNMANNED AERIAL VEHICLES WITH A SENSOR NETWORK FOR ENERGY-EFFICIENT MONITORING

Modern unmanned aerial vehicles (UAVs) are increasingly integrated with sensor networks, which significantly expands the possibilities for data collection, transmission, and real-time processing. This integration is critically important for various sectors, including environmental monitoring, smart city infrastructure management, agriculture, and military operations. UAVs provide mobility and access to remote and hard-to-reach locations, enabling efficient monitoring in conditions where conventional networks are unavailable or ineffective. However, numerous technical challenges arise along with these advantages. They concern, in particular, the optimization of drone flight routes to ensure maximum sensor network coverage, the minimization of energy consumption, and the resolution of data security problems, including cyber threats. Another key aspect is flight duration, which depends on UAV battery capacity, as well as energy-saving approaches for sensor nodes, such as the use of alternative energy sources like solar panels. This study presents a dynamic interaction model of UAVs and a sensor network, examining the data collection process, the transmission of these data to a central server, and how increasing the number of sensor nodes affects the total mission time. A stochastic model is proposed to account for environmental heterogeneities such as data transmission delays caused by interference or variations in connection speed. An analysis is carried out regarding the impact of these factors on data collection efficiency and on the optimization of flight routes, particularly through the use of dynamic programming and heuristic methods.