Edge Intelligence Resource Consumption by UAV-based IR Object Detection

Andrii Polukhin, Yuri G. Gordienko, Mairo Leier, Gert Jervan, Oleksandr Rokovyi, Oleg Alienin, Sergii G. Stirenko

Abstract: The investigation of the feasibility of using the YOLO (You Only Look Once) architecture for object detection in infrared images from unmanned aerial vehicles (UAVs) on low-power devices, specifically the Raspberry Pi, and Orange Pi, is conducted. The study measures the consumption of computing resources for each device, such as inference time (ms), peak power consumption (W), memory consumption (MB), inference energy (J), memory consumption (MB), and storage consumption (MB). It also investigates the correlation between number of model parameters and resource consumption of the different YOLO model sizes. Finally, the study draws conclusions about the expediency and realism of using YOLO on low-power devices for Edge Intelligence and proposes methods of speeding up work. The results show that YOLO can be used effectively on low-power devices with some optimizations to increase performance and energy efficiency.