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Mark43's Cobalt software platform unites a set of law enforcement tools securely...


Demystifying the Convergence of LTE and LMR Networks for First Responders

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Originally aired: Thursday, December 6, 2018 -- 11:00 AM PT/2:00 PM ET

Narrowband Land Mobile Radio (LMR) networks and user radio equipment have been the cornerstone of mobile communications for First Responders for decades. The trend from traditional analog to more robust wireless broadband networks in recent years has improved the overall accessibility but questions remain on whether the new networks can provide all the required capabilities First Responders need to do their job.

Increasing demand for bandwidth intensive applications such as video, advanced mapping and analytics, alongside critical voice communications has been driving adoption of broadband LTE cellular networks, such as FirstNet.

Join our panel of industry experts for this insightful 60-minute on-demand webinar as they discuss the critical differences between LMR networks and LTE networking, how these technologies can successfully co-exist, and explore the future of critical communications for First Responders.

In this session, you will learn:

  • Current and future industry trends for LTE and LMR technologies
  • Challenges and obstacles with the convergence of technologies
  • Real-life examples of successful hybrid communication strategies for First Responders
  • Recommendations for future proofing your agency; adoption of new technologies and how to bridge the gap


Tony Morris, VP North American Sales, Enterprise Solutions, Sierra Wireless

Jesus Gonzalez, Analyst II, Critical Communications, IHS Markit

Ken Rehbehn, Principal Analyst, Critical Communications Insights

Andrew Seybold, Senior Partner, Andrew Seybold Inc.

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6 Key Findings of Incident Reporting

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Originally aired: Thursday, December 13, 2018 -- 11:00 AM PT/2:00 PM ET

An exceeding number of police departments and law enforcement agencies, whose officers spend upwards of 3-4 hours a day completing incident reports and other time-sensitive paperwork*, are turning to smarter tools, such as speech recognition solutions, to help transform their police reporting workflows.

View this on-demand webinar to hear why these law enforcement professionals are embracing smarter tools to complete higher-quality reports and move mission-critical information within the CAD/RMS faster and more efficiently – all by voice.

This discussion will provide you with an understanding of:

  • What law enforcement has to say about current reporting processes
  • Why officers, especially recruits, want smarter tools to help with police paperwork
  • Why manual reporting has a negative impact on report accuracy and productivity and can hinder criminal proceedings
  • How departments can speed up data entry within the CAD/RMs and move mission-critical information more accurately and efficiently
  • How speech recognition technology can help increase officer safety and improve situational awareness and productivity on patrol
  • Why embracing smarter technology increases community visibility, and minimizes costs

Learn how your department can make incident reporting faster, safer and more complete by viewing our on-demand webinar today.

*Role of Technology in Law Enforcement Paperwork Survey 


Eric La Scola, Product Marketing Manager, Dragon, Nuance


Finding a Face in the Crowd

A new class of police software lets you identify subjects in seconds, even when they're disguised.

October 01, 2002  |  by - Also by this author

As a group of passengers exits a plane at Toronto International Airport, a security camera scans the face of each person deplaning. The camera scrutinizes a short, gray-haired lady, then a tall blonde. Finding nothing, the camera focuses in on a handsome clean-shaven man with short, cropped hair. Just like it did with the two women, a system locates the man's eyes and nose and then measures the distances between key features on his face. Special software compares his image against a database of thousands of mugshots and, unlike with the two women, a match is found. A warning message appears on a screen alerting security that a match has been made. All in a matter of seconds.

A security guard looks at the images on the screen in front of him: a video capture of a clean-shaven man with close-cropped hair next to a mugshot of a convicted American drug dealer with a beard and shaggy long hair. They look different, but the guard confirms they are definitely the same man. In minutes, the positively identified man is apprehended.

If facial recognition works this well with known drug dealers, imagine what it could do with known terrorists entering an airport.

How it Works

Facial recognition software scans a picture of a face-from a photograph or a video freezeframe-looking for identifiable features. These features are then encoded into a string of numbers that represents that person's image. This set of numbers is compared against sets of numbers in a database until similar images are found. The computer will alert the officer conducting the search of a match or near match.

The officer can then view the images the computer has identified as possible matches and verify a match. Many prefer facial recognition because a human can double-check a computer match, unlike fingerprints or retinal scans, which cannot be verified with the naked eye.

Because it stores simple lines of code instead of memory-intensive images, facial recognition software can search through millions of people for a match and get results in seconds. This can even be done from a laptop or handheld while on the street.

The Software

All facial recognition products work in pretty much the same way, but there is more than one way to map a person's face. Each company has a slightly different approach and different terminology.

Face-It Argus from Identix-which recently merged with Visionics-measures  relative distances between the peaks and valleys of the face, using about 80 points to develop a unique image, converted into a string of numbers. Because the features in the center of the face are the most stable, Face-It Argus focuses on this central region, according to Frances Zelazny, director of corporate communications at Identix.

With a different approach, ID-2000 from Imagis Industries uses "light reflectants" to recognize features across the entire face, explains Imagis President and CEO Iain Drummond.

"ID-2000 finds the two eyes and the tip of the nose. It then looks for about 200 features in the face. A feature is a curve, such as the hollow of the cheek, the shape of the cheekbone, the curvature of the eye socket, that type of thing. What we do is we detect it by changes in light reflectants, which is how human beings detect facial shapes. For instance, you see a difference in shading as you look at the hollow of a cheek.

"Having found these 200 features, we then transform them mathematically into a digital string that's about 400 bytes long. And that string becomes your unique facial signature."

GeoMetrix’ FaceVision uses two still cameras to produce a 3D map of a person’s face. This is much less expensive than 3D cameras.

Viisage uses yet another formula for its two facial recognition products. Both FaceFinder, designed to identify faces in streaming video, and FaceExplorer, most often used for still photographs, are based on what the company calls the "eigenface" template. The template consists of 128 different facial measurements between the chin and the middle of the forehead and from ear to ear. Michael Mazzu, vice president and general manager of public safety for Viisage, calls it "masking off the area."

Mazzu explains, "A template is just a series of 128 numbers. That template of 128 measurements, each one of which is basically a number, is compared to other sets of these numbers in the database."


With so many different makers of facial recognition software, one might wonder what happens when different police departments choose different software.

Every police agency in Alameda County, Calif., uses facial recognition software from the same company, which makes sharing information easier. But it is not necessary for police departments to use exactly the same technology in order to trade mugshot information.

Imagis Technologies’ ID-2000 is used to identify criminals by comparing a photo to other coded face images in a database of mug shots.

Many facial recognition systems are also sold with booking systems and CADS software. But for those agencies that only want to buy the facial recognition software, this set-up can work equally as well.

Drummond of Imagis Industries says facial recognition software is made to work with any booking system or database, even when agencies have the software  customized to their specifications, a service offered by most companies.

"If the mugshots are in a different database, then as long as we know where those mugshots are in that database, we can point the facial recognition system at the mugshots and it will use that database rather than our own. It can use both companies' databases at the same time."

And even if departments have different facial recognition systems developed by different companies, they can search each other's databases of images.
According to Viisage's Mazzu, "Although all the photos are done in a standard format, we're not going to utilize another company's coding of images. But there's no need to if you have access to the images themselves."

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