For many business and educational leaders, the resumption of work and learning amid the COVID-19 pandemic continues to be a challenge. As soon as they figure out how to address one issue, another crops up. Often, these relate to the logistics of recommendations intended to allow people to carry on with their activities without compromising each other’s health. For example, policies may require individuals to wear masks, but what happens when they fail to comply, either intentionally or by wearing a mask improperly?

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Enforcing health and safety policies and detecting noncompliance can be difficult to accomplish, especially in high-traffic areas, but it’s crucial. Enhanced video surveillance can help. In recent months, many organizations have repurposed existing EVS systems, typically deployed for physical security, to support screening measures related to COVID-19, such as thermal imaging scans, occupancy management and contact tracing.

Layering face mask detection into video analytics, and potentially integrating it with access control systems, provides an additional layer of protection. As with occupancy management and contact tracing, many companies find that automated solutions are far more effective at mask monitoring than humans are.

Software Detects Missing or Incorrectly Worn Masks

Real-time mask detection is accomplished by an artificial intelligence–enabled analysis that detects objects in the field of view, recognizes them as human and determines whether they are wearing a mask. The software can detect whether people are wearing masks properly and even whether they’re attempting to trick the camera by holding an object, such as a phone, up to their face. For an employee monitoring the video feed, a yellow square around a person’s head might indicate appropriate mask wearing, whereas a red square might indicate a problem.

When the system detects an issue, it can automatically trigger a notification, an alert or an audio message on a speaker at the building entrance. At that point, employees have actionable information that not only helps to keep people healthy, but also instills confidence that the organization is taking a state-of-the-art approach to maintaining the well-being of its community.

As with so many other aspects of digital transformation, this process has a valuable data component too. Information about mask adherence can provide useful insights to help leaders make decisions about operations, occupancy limits and other matters.

Multipurpose Analytics Support a Variety of Organizational Aims

Leveraging video surveillance for face mask detection is powerful, because it relies on AI-driven analytics. It’s also cost-effective, because it’s relatively easy to implement without a significant IT investment. Many organizations have already deployed smart cameras with video capabilities or back-end video management software for physical security or other objectives. Leveraging these assets for mask detection may require only the integration of new software. Those that do not have hardware already in place can install a limited number of smart cameras with face mask detection capabilities to cover specific areas.

It’s important to note, too, that if an organization deploys a new camera with analytics specifically for face mask detection, that device likely has other analytics capabilities that will be useful, such as motion tracking, detection of objects left behind and people counting. One reason that EVS has become so popular is because it’s so versatile. So although the initial investment may be to facilitate mask wearing compliance, organizations will likely find multiple ways to repurpose that solution in the future.