Outdoor Social Distancing Violation System Detection Using YOLO Algorithm

The government issued orders to implement social distancing or physical distancing. Social distancing is a method of maintaining a distance of at least one meter from other people. This is useful for reducing/preventing disease transmission (virus) and reducing the chain of the spread of covid-19. So the hospital can provide optimal service. For this reason, this research is structured to create a system that can detect violations of social distancing in an open place. This system uses the You Only Look Once (YOLO) algorithm. The developed system uses a pre-trained Yolov4 model to detect 80 object classes. Testing of this system is carried out based on several scenarios. The system is programmed using Python, with tools for coding Microsoft Visual Studio Code and Anaconda. The best result from creating the detection mode is obtained from a dataset ratio of 90% train data and 10% test data, with the mean average precision results obtained being 54.11%.