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Diving into the Award-Winning Artificial Intelligence Technology Behind Evolv Express®

It’s always nice to see your work recognized, so it was gratifying to me and the entire team here at Evolv Technology to learn we earned an Artificial Intelligence Excellence Award from the Business Intelligence Group. The award is particularly meaningful because it goes to companies that “bring AI to life and apply it to solve real problems.”

That certainly describes Evolv, which uses AI to fundamentally transform human security screening, which until Evolv, has had to rely on a nearly 100-year-old metal detection technology, purpose-built for finding metal as the name implies. And, as we all know, in today’s world, we carry metal every day – our smartphones. So, it’s about time we start differentiating between a metal that is a threat, and a metal that is not.  

Evolv’s use of AI enables our Evolv Express® touchless screening system to screen some 3,600 people per hour, about 10 times the rate of an outdated walk-through metal detector. It does so without requiring most people to slow down, stop, get frisked, or empty their pockets and bags. That’s a particularly important point during the pandemic; this touchless technology allows for social distancing and requires no contact with people or their belongings – attributes a recent Harris Poll found to be important in getting people back to schoolslive event venues, and workplaces

It’s fitting that our award fell under the “automatic target recognition” application category, one of the earliest applications of radar. As radar was upon its debut, I like to think Evolv’s use of AI for screening is a technological leap forward today. 

Screening technology takes a giant leap forward

A traditional metal detector transmits an electromagnetic field that triggers an alarm upon the detection of metal, so it either finds metal or it doesn’t. If it does, you know the drill – it’s off to the guard with the wand, perhaps a pat-down and emptying of your pockets and bags, and likely another pass through the metal detector, back and forth like a yo-yo. It’s a time-consuming and highly physical interaction and I posit; do you really want to find every bit of metal?

Evolv’s technology combines AI technology with sophisticated state-of-the-art sensors which together not only detect metal but can determine the type of metal and shape of the object. That’s important on a couple of fronts. 

By looking at the data from a wide range of firearms, consumer electronics, and other common metal objects, certain consistent patterns emerge in the metals used, their dimensions, etc.  By applying AI technology, these patterns of metal content and shape can help identify what the object is – a cell phone, a set of keys, or the like. By differentiating between benign objects and threats, there’s no need for people to empty their pockets or bags. 

Well-trained AI and state-of-the-art sensors 

A number of technologies come into play to deliver on that kind of accuracy. 

Our AI model has been trained on nearly 50,000 object scans, including multiple types of firearms along with everyday items that people carry in their pockets or bags. 

Equally crucial is our sensor technology. We use transmitters and receivers that operate in the ultra-low frequency radio wave spectrum. That spectrum is able to deliver the best characterization of properties, enabling us to detect those different types of metals. 

And using multiple other sensors to account for distinct environmental conditions, our software can self-calibrate in the measurement results, to maintain high levels of accuracy. 

Unsung hero: data cleaning and pre-processing

One other ingredient in our secret sauce, and a key to what makes the system effective in real-time, is data cleaning and pre-processing. I think of this technology like a goalie in soccer; they tend to get little fanfare or glory (although plenty of blame), but for a team to excel it needs a good goalie. The same goes for AI when it comes to data pre-processing. 

Pre-processing happens on-site as people are coming through the Evolv Express system. We take all the data that’s coming at us, then factor in any interference nearby along with a series of filters that help us isolate the signals we really care about – the objects people are carrying. By the time we hand off data on a given subject to our AI engine, the data is clean, focused, and crunched into a useable format. The end result is an AI that is robust, efficient, and simple, relatively speaking. Of course, operators don’t need to know anything about the technology itself. While Evolv Express may be full of sophisticated technology, it’s simple to use.  

Harnessing the power of AI 

Hopefully, this gives you some sense of the power that AI brings to everyday applications like screening – and how it’s a sea change from the traditional metal detector. While the technology behind Evolv Express was in development well before anyone ever heard of Covid-19, it’s clear it offers an effective solution to keeping people safe from weapons and intruders, and socially distanced and safe from health threats as they return to schools, ticketed venues, and workplaces. 

I’m gratified that the folks at Business Intelligence Group could see the value in Evolv Express and saw fit to recognize us with an Artificial Intelligence Excellence Award.

Alec Rose Headshot
Alec Rose
Chief Scientist

Dr. Alec Rose is a member of the Evolv Technology Executive Leadership Team, where he serves as Chief Scientist. He has authored more than twenty different publications ranging from various subjects in physics, electromagnetic imaging, and automated detection. He made significant contributions to the field of nonlinear metamaterials as a member of Professor David R. Smith’s electromagnetics lab at Duke University, the groundbreaking research group known for novel demonstrations of negative refraction and cloaking. He is credited for five different patents underpinning Evolv’s technology, helping drive and shape the products known in the market today. Alec holds a bachelor’s degree in physics from Boston College, as well as a Ph.D. in Electrical and Computer Engineering from Duke University.

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