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Enforcing Face Masks Without Confrontation Or Bias

Enforcing Face Masks Without Confrontation Or Bias
Steve Reinharz
Steve Reinharz
Contact company
Contact Robotic Assistance Devices, LLC. (RAD)
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Summary is AI-generated, newsdesk-reviewed
  • AI-powered cameras enforce mask compliance, reducing confrontations and boosting regulatory adherence.
  • Autonomous systems decrease security costs, minimizing worker confrontations over face mask use.
  • Mask detection technology ensures accountability and document compliance in health and remote sites.

The COVID-19 pandemic has presented an unprecedented challenge to businesses. From retail stores to office buildings to warehouses and construction sites, a big question looms: how can landlords, executives, and employers ensure their facilities don’t contribute to the spread of the virus?

A low-tech solution - the face mask - has become a leading preventative measure. But, a high-tech solution is necessary to ensure that everyone is wearing them. Cameras powered by artificial intelligence can now identify whether or not people entering a facility are wearing facemasks and help enforce adherence to mask mandates. This technology is proving to be a cost effective solution that reduces risks of confrontations over masks policies and gives managers the data they need to document regulatory compliance and reduce liability.

Layers of security

They can also be integrated into access control systems or woven into other preventative measures that create overlapping layers of security. These cameras are an ideal solution for low-traffic, remote sites, or areas that are only accessible to employees that need to monitor mask compliance but at which hiring a manned guard is just too expensive.

Cameras with mask detection capabilities are especially useful when the technology piggybacks on existing autonomous devices, such as mobile security drones.

The premise is simple. When a person without a mask is detected by the autonomous robotic security device, the system can generate, depending on customer preferences, audible and visible alerts to remind people to mask up. It also feeds alerts to a cloud-based data storage system so that security executives can analyze data for trends or quickly locate video of important incidents.

Why masks?

One study published in the Proceedings of the Royal Society A highlights the benefits of mask usage. If just 50 percent of people use masks, the rate of COVID-19 transmission will slowly decline. If 80 percent of people use them, the rate will plummet.

Bu,t people don’t love wearing them. They’re hot. They make eyeglasses foggy. It’s hard to make yourself heard when talking to others. We’re all familiar with industries that wear masks of some type or other, on a regular basis - health care, construction, and heavy industry to name a few. But for the general public, wearing a mask for long periods of time is not a regular habit.

For the general public, wearing a mask for long periods of time is not a regular habit

We also know that other measures site managers have used to limit the spread of coronavirus are ineffective. For example, at least three meatpacking plants rank among the top 50 locations for coronavirus clusters. One factor driving that spread: many employees, to avoid missing a day’s pay, masked their mild fevers with ibuprofen to fool the infrared temperature scanners that employers used to protect against the outbreak.

The paradox of masks, however, isn’t that they protect the wearer from infection. It’s the other way around: when an infected person wearing a mask sneezes, coughs, or breathes, they don’t spread the virus as far, and thus masks slow the spread of the virus from infected people, including those that are not showing symptoms.

Prove it

One of the very reasons why county and state governments have instituted mask orders is simple: it’s an easily verifiable sign that an organization is taking steps to limit the spread of coronavirus. Mask detection cameras, coupled with autonomous security systems, can provide the documentation employers need to ensure mask compliance.

Imagine, for example, a warehouse full of manual laborers. The county orders everyone to wear a mask any time they leave home. A disgruntled employee, recently terminated, files an anonymous complaint to local health officials stating that the warehouse isn’t enforcing mask compliance - or worse, preventing employees from wearing masks to prevent theft. The county sends an inspector.

Mask detection cameras provide site managers with the documentation they need to disprove these allegations. The autonomous systems developed by RAD will feed video footage into a cloud database, documenting not only the instances of non-compliance, but also the instances of compliance - with the mask clearly highlighted. Any inspector that arrives on a job site can see hours and hours of footage, without having to pour through hours of video.

Reducing confrontation

We’ve all seen the videos in which angry shoppers confront retail clerks and security guards over mask usage. In some cases, these confrontations have turned violent, resulting in injury or death. For every one of these videos, there may well be hundreds of others.

While most of the videos featuring mask confrontations focus on retail settings, manned guards also face challenges in enforcement. Confrontations over mask usage have the potential to drive up workman’s compensation claims higher when guards are injured. Because autonomous security units generate alerts automatically, the chance of confrontation is minimised.

It’s easy to imagine a couple of scenarios in which autonomous units can be beneficial. In health care settings, where emotions run high, autonomous devices can serve as a force multiplier for patrolling guards in parking areas. For example, roving units can identify people that are not wearing masks, and remind them to do so before they enter the building. These can also be placed in entryways that generate alerts as visitors approach doors.

In many buildings, mask detection systems can be integrated into access control systems

Autonomous security units can be deployed for a fraction of the cost of manned security. In healthcare, autonomous units can be used to re-allocate security spending, placing less emphasis on low intensity guards whose primary function is to observe and report - particularly those that patrol parking garages - and more emphasis on trained professionals capable of defusing confrontations inside the hospital. In other words, autonomous units outside allow facilities to hire better quality inside, where confrontations are most likely to take place. In many buildings, mask detection systems can be integrated into access control systems, which might be especially useful at entrances that are not manned by security, but accessible via key card.

Changing behaviors

There was a time when smoking in public was not seen as particularly anti-social. Almost everyone will stop at a stop sign, even when we can see for miles in every direction, and we know that the risk of an accident is zero.

We do these things because we have been trained to. These behaviors make us safer, but we didn’t adopt them overnight. Many of us forget, but the fight over banning smoking in bars and restaurants was filled with confrontation.

So, too, will it be with mask compliance. But time is short, and we all need to do everything we can to encourage good behavior. Mask detection technology can do that, and these solutions are very cost effective. In some cases, the cost may be just 5 percent of using a manned guard. They’re effective too. Autonomous systems enforce mask policies consistently and drive accountability. That can make us all safer.

Understand how converged physical and cybersecurity systems can scale protection.

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Discover how AI security solutions enhance face mask enforcement while reducing confrontations and bias in our in-depth article.

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