Face mask detection using video streaming analytics and deep learning for healthcare management system

Video stream analytics is already a well-known topic and is constantly increasing its value these days. In addition, in the context of medical services development and the application of AI technologies to the hospital system. Understanding this, we aim to set a problem by analyzing the entity recognition inside the video in combination with identifying people wearing masks as the topic of the report. This study is of great help in identifying entities in isolation areas that need to wear masks in hospitals. To solve this problem, we uses a combination of three models: object recognition analysis, face identification, and face mask identification to analyze and solve the problem. After a period of research, we completed the Streaming video and identified more than 80 objects with the “person” object that we focused on. We also successfully built a simple HTML application that can display the results as images. This is considered a positive result with facial recognition analysis in real-time video.