Mesh networks drive law enforcement, public sector applications in motion

Mesh networks drive law enforcement, public-sector apps in motion

On an ordinary day in February this year, a car in Media, Pa., pulled up to the curb along State St., the main thoroughfare of the town of 5,400 and county seat to Delaware County.

A man exited the car, followed by a woman holding a baby. Without notice, the man assaulted the woman, punching her in the face and knocking her down and out. Then he jumped back in the car and sped away.

The case wound up going to court. “The case may not have been going as well as everyone would have liked until the jury saw the video and saw what he did,” said Media Mayor Bob McMahon. “They literally gasped. The guy is now behind bars and apparently there were several other situations that he’s been in too.”

McMahon credits the verdict to a high definition video surveillance system the town installed last October, which he described as “a force multiplier, extra eyes on the ground -- people know [it's there] and it makes them feel safer.”

Media's six-camera network is also the first law enforcement-based  installation of wireless network technology developed by Rajant Corp., which enables organizations to set up private mesh networks that operate between mobile or “kinetic” nodes and  that support HD video processing at the ends of the network.

In contrast to mobile phone networks that rely on fixed towers, all elements of the mesh network can be in motion, Rajant CEO and co-founder Robert Schena explained.

“What that means is that since the network itself can move, it can go on police vehicles, trucks, buses, trains, on aircraft, helicopters, drones,” said Schena. “It can create this network environment that’s continuously in change, but the network maintains itself.”

In July Rajant launched CacheCrumb, a wireless node with built-in processing power that the firm says reflects a new trend toward edge network computing in industrial and public sector-applications.

In Media, surveillance cameras are plugged directly into the CacheCrumb node. “The reason we call it a CacheCrumb is that in addition to its meshing wireless routing capabilities, it also has an extra gigabyte CPU available and an extra terabyte of solid state memory.”

Output from the cameras can be stored right in the wireless node on the pole. A web server native to the CacheCrumb node means that police, using only a web browser, can go directly to the camera and collect high definition video of an incident.

“It doesn’t burden the network with a lot of video traffic,” said Schena. “Instead it keeps the video traffic at the edge of the network until you need to access it.” 

This approach also means back office and control rooms for video processing or pre-production are unnecessary. “It’s high definition, not the normal grainy closed-circuit television stuff that people are familiar with,” said Schena.

In the courtroom in Media, he added, “the audience reacted pretty dramatically when they saw the high definition evidence. With this kind of video you can count the number of hairs in someone’s eyebrows.”

With the extra computing power inside the wireless node, other features are available, including facial recognition and reading license plates.  There are also  applications to facilitate node-to-node hand-offs.

“The network can be smart enough to ‘follow’ vehicles,” said Schena. “You can have one node hand off a car that it’s been following ... to the next node.  There’ a lot of things you can do once you marry computing and video capability.”

In the public sector arena, one of more critical of those features is the ability to authenticate electronic content and video records created over the network.  

“One of the things that will come up as police move toward video capture of arrests or anytime they’re interviewing someone is that somebody arrested is going to say, ‘that’s not the real video, that was ‘Photoshopped,’” he said. 

The CacheCrumb technology is capable of creating an affidavit of the number of pixels in an original image, said Schena. “We can assure that we know how much information was involved in creating an image, count pixels and then make sure the image someone sees down the road has the same number of pixels.”

Looking ahead, the firm anticipates developing more uses for its mesh and edge processing services based on its expertise in handling applications in motion.

“Our first competitive advantage is that our network can move,” Schena said. “It can be in vehicles; when three vehicles drive down the road they can create a network; the vehicles moving can be connected to nodes on poles, or they can be connected to drones flying overhead.”

“And that allows us to anticipate going in all kinds of police vehicles, fire vehicles, buses," he continued.  "And as they move around they all will maintain network connectivity.”

About the Author

Paul McCloskey is senior editor of GCN. A former editor-in-chief of both GCN and FCW, McCloskey was part of Federal Computer Week's founding editorial staff.

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