Analysis and Modeling of UAV Data Collection in IoT Systems Based on Markov Fluid

The rapid development of technologies such as the Internet of Things (IoT) has greatly facilitated various aspects of people's lives and profoundly transformed their daily routines and work environments. Sensor devices, a vital component of the IoT, offer a reliable and real-time data source for the advancement of applications like artificial intelligence and the industrial internet. However, there are still numerous unresolved issues in the data collection process of sensor devices, particularly in harsh conditions. Utilizing drone platforms for real-time data collection appears to be a viable approach at present. This paper addresses the optimization and control of energy consumption in unmanned aerial vehicle (UAV) data collection. It comprehensively considers factors such as the distribution of sensor devices, UAV speed control, and sensor energy consumption. By integrating Markov fluid theory, we provide a mathematical expression of the relationship between UAV energy consumption, the distribution of sensor devices, and data collection transmission variables in this scenario.