SoC Design and Implementation of Incorrect Facemask Wearing Detection System

In this paper, we present a system-on-chip (SoC) design for incorrect face mask-wearing detection on a low-cost FPGA device. The SoC architecture realizes a VGG9 model to classify the incorrect face mask-wearing persons. To accelerate the processing time, we proposed a convolution IP that can compute 32 convolutional calculations in parallel. The experimental result shows that our SoC system can process up to 15 image frames per second at an operating frequency of 130Mhz and the coverage score achieved up to 93.3% in real-time.