Guidelines published by government agencies like the U.S. Centers for Disease Control and Prevention and the European Centre for Disease Prevention and Control recommend that individuals wear a mask or cloth face covering in public places, especially in locations where social distancing guidelines are difficult to follow—for example, elevators and other enclosed spaces.
Aerosols produced simply by breathing, talking, coughing, or sneezing may contain a wide spectrum of pathogens. Many respiratory particles can remain airborne for hours, which reinforces the need to adhere to social distancing guidelines and wear masks.
Following these guidelines, many locations trying to reopen for business have made it mandatory to wear masks on premises. Floor markers indicating proper social distancing (typically six feet, or two meters) and prompting occupants of a space to follow those requirements are a common
However, for many organizations, enforcing compliance to wear masks within the facility is currently a manual process with no automated workflow processes.
SO HOW DOES IT WORK?
Video analytics and deep learning artificial intelligence can be used to effectively identify occupant mask and social distancing compliance.
It is recommended for use in critical areas of a building such as entrances and before entering an elevator, as well as potentially crowded common areas like a cafeteria.
A system with the ability to create real-time notifications of health and safety policies violations can help inform the building operator, enable immediate corrective actions, and better protect building occupants.