The purpose of this study work is to provide a sophisticated automated system that has been created for effective management in situations that need little human contact during times of public health crisis. A suite of computer vision modules, such as gesture recognition and gender recognition, are included to the system. Each of these modules has been painstakingly customized to handle unique issues that are faced in real-time dynamic contexts. The gesture recognition module makes use of both hand and upper body key points to handle the delicate nuances of a wide variety of human movements within dynamic environments. It does this by deftly reducing obstacles associated to varying lighting conditions, picture quality, and occlusions. This automated system has practical uses outside of venues such as restaurants, amusement parks, and service areas, in addition to the technological achievements it has made. The deployment of this system makes it possible to gather input in real time in an independent and objective manner, which represents a big step forward in the direction of improving public health outcomes.