5G Edge Cloud Power Real-time Inspection Technology Based on YOLOV4-Tiny
DOI:
https://doi.org/10.13052/dgaej2156-3306.3643Keywords:
Deep learning, edge cloud, 5G, real-time power line inspection.Abstract
Power line corridor inspection plays a vital role in power system safe opera-
tion, traditional human inspection’s low efficiency makes the novel inspection
method requiring high precision and high efficiency. Combined with the
current deep learning target detection algorithm based on high accuracy and
strong real-time performance, this paper proposes a YOLOV4-Tiny based
drone real-time power line inspection method. The 5G and edge computing
technology are combined properly forming a complete edge computing archi-
tecture. The UAV is treated as an edge device with a YOLOV4-Tiny deep-
learning-based object detection model and AI chip on board. Extensive exper-
iments on real data demonstrate the 5G and Edge computing architecture
could satisfy the demands of real-time power inspection, and the intelligence
of the whole inspection improved significantly.
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