A Crowd Alert System for Pandemic Control using Yolov4

The Covid-19 pandemic in the late 2019 caused the world to shut down. Even though it is recommended to reduce overcrowding it still cannot be avoided. This can cause the pandemic to spread even more, especially since offices, schools and colleges are slowly reopening. With image detection making huge breakthroughs in the last decade, modern image detection technologies can now be combined with the current hardware to combat problems like overcrowding, which massively spreads the pandemic. In this paper, the YOLO v4 algorithm has been used, which greatly speeds up the process of detection and improves the overall accuracy of the system.