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IFSEC Insider, formerly IFSEC Global, is the leading online community and news platform for security and fire safety professionals.
September 24, 2015


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Tracking Suspects or Fashion Trends: How Qognify’s Suspect Search is Breaking New Ground in Video Analytics

Last year NICE Systems, the Israeli innovator in data security and surveillance applications, launched a ground-breaking video analytics solution called Suspect Search.

Boasting patented algorithms Suspect Search will quickly locate suspects matching a given description from multiple camera streams, in real time or from hours of recorded footage. Rather than manually trawling hours of footage from multiple cameras control room operators can build an avatar based on the suspect’s description and track suspects matching those details no matter how crowded the environment.

We spoke to Moti Shabtai, President of Qognify – which this week concluded the acquisition of NICE Systems’ Physical Security Business Unit – about Suspect Search and how the company’s predictive analytics innovations could even be applied to applications beyond the security arena.

IFSEC Global: Hi, Moti. A year after launch what’s the strategic plan for Suspect Search?

Moti Shabtai: We want to take it to new areas of detection. One dimension is to not limit only to human beings, but cars for example, or any other type of object, like airplanes.

Another dimension is to add to it ancillary means of detection other than just taking your set of characteristics – writing a digital signature, associated with other means, in order to track people for marketing purposes.

What is the flow of people in the retail areas in Heathrow airport? Where are the more beneficial areas versus the others? How can I price them differently? Same with other environments of business.

So we are seeing this application becoming going beyond the area of rescuing lost children or finding crime suspects.

IG: So a researcher into fashion trends could, for example, find out how many people were wearing red trousers down a particular high-street?

MS: Right, right. Or people with a specific hair colour. Anything unique is very easy to follow.

Even you, you have that name tag here – not many people do. You have a burgundy tie – not many people do. You have a combination of brown shoes with a dark suit – not many people do.

But if you’re wearing common stuff, like in the US everyone has a navy blue suit, still we can find something about you – your posture, your skin, your body weight…

If someone manages to breach a security checkpoint in an airport then typically you have to shut down the airport until you find them. At an airport like Heathrow that costs tens of thousands of pounds per minute. That’s obviously a big driver for our application.

Nice 2IG: So return on investment would be relatively quick?

MS: Exactly. Because it’s reducing a typical shutdown of anything from 20 minutes to three hours sometimes down to a few minutes.

We’ve also seen growing demand in hospitals where it’s used to track people who are stealing drugs or sometimes even babies.

Another area is casinos. There are people who can count cards in their head, which is a perfectly legal action. However, as a private property I can ask you to please leave the property.

But since these people can make a living out of it then they go to the next property or come back the next day.

Mass transit is another perfect example. Utilities, believe it or not, have people going into energised areas, and they want to understand the circumstances and how they can prevent this. This is a growing problem for utilities.

IG: This is pretty much the only product of its type on the market, eight?

MS: Absolutely. It’s patented. Nobody has solved the algorithmic problem that we have solved.

There are applications that can tell you have a white shirt. What they cannot say is this white shirt was here and it was there and there too. They haven’t solved the problem of similarity. That’s the patent we have.

We’ve already got eight industry awards for originality, creativity, innovation. So we’re absolutely the only game in town.

IG: What other problems does this platform solve?

MS: Guys running organisations in mission-critical environments – it could be airports, mass transit, utilities, banks, the Googles of the world – have a very big problem. They need to maintain business continuity and streamline operations.

However, they have over the years acquired a plethora of systems that do not talk to each other. They’re not interconnected, so they find themselves facing a sea of data they know nothing about. They need to turn that data into information and, even better, to intelligence.

At the same time they have a growing number of threats and incidents, both in impact and amount. And their management is pushing them to get more efficiency – to do more with less. So they are in a kind of conundrum: understanding how to face the sea of data in front of them.

This is where technology in situation management and informational intelligence can help. Meaning we can take all that data and get an insight from it. We’re the guys that can find the needle in the haystack.

We will correlate that information and give them some kind of situational awareness to say “this is what is happening now” or say your organisation is doing better or worse – whatever KPI they define.

That’s the beauty of it. They define the performance criteria and we provide the tool.

I give you an example: the Department of Transportation [in the US]. How do they provide a good traffic flow on the roads?

They measure the flow, the density of the highway. They have sensors all over, they measure the speed, the friction…

But they have single sensors. They don’t have a unified view to say you know the flow of the highway is that, and in the winter time it goes down, and summer time it goes up, and we can improve it by doing so and so and so.

IG: So it’s being predictive as well as reactive…

MS: Predictive analytics, exactly. This is what we provide. And it’s called situation management, because you manage situation.

And it’s called operational intelligence because it enables them to run their business better.

Banks are another example. More than any sector they’re all about business continuity. How do they maintain the business continuity of hundreds or thousands of branches at the highest level?

The KPI they define is the average response time per incident and they want to take it from 15 minutes to five because this means dollars on the top line and bottom line.

So again, quantified ROI.

Technology can help them shorten the response time to incidents because they will have a better awareness of what is going on. They will have a better set of procedures as they can automate processes.

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