Intelligent Warehouse Material Detection Based on RFID and Deep Learning

With the rapid advancement of artificial intelligence, there has been a thriving development of intelligence in the logistics field. Material inbound and outbound detection, an indispensable component of logistics, is in urgent need of automation. This paper proposes the utilization of existing warehouse cameras in logistics scenarios to capture video image data and employs deep learning model for intelligent material inbound and outbound detection. Through preliminary experiments, it was discovered that cameras themselves have limitations, including susceptibility to lighting conditions. To address these limitations, we further suggest the integration of RFID radio frequency technology with deep learning approach to enhance the accuracy of detection. Extensive experimentation validates that our proposed method significantly outperforms the use of deep learning method alone.