The winter cold in Boston can cut through you like a knife, so when I had the opportunity, in late January of 2017, to travel to San Diego to see my first security robot, there was no hesitation on my part. The company was doing an early demo, to local buyers, in a parking lot of a strip mall. As I pulled in, I saw the caution tape securing an area of the parking lot, and saw the five-foot-tall, 400 lbs robot patrolling that area. It was an impressive sight. I introduced myself to the engineer and told him, “I was there to meet Jack.” He politely replied that Jack will be here shortly. About 15 minutes later I saw a black convertible, roof top down, with golf clubs hanging out of the back seat, and a guy waving to me, pull into the lot. That was my introduction to Jack Schenk.
That day he showed me, and about 15 other people, the first generation Knightscope K5 autonomous data machines (ADM) or what is more commonly referred to as a security robot. I watched as it did a simple “L” shaped patrol of the area, stopping as we blocked its path, and finding a new route to navigate around us. Its presence was recognized not just by its size nor its flashing strobes, but also with a polite but annoying music playing and a vocal broadcast announcing its presence. The robot provided a strong, and somewhat intimidating, audible and visual security presence that was intended to deter would be Ne’er-de-Wellers. All impressive, but, to me, it was the time we spent reviewing the user interface portal to the data gathered by the robot’s sensors and cameras that made me want to learn more about this technology. It was here that I first realized, as impressive as the robot looked, the technology attached to the robot could make the security officer working with it a powerful resource to Chief Security Officer, Security Directors and Corporate Security Managers. I thought, “This is a game changer!”
It hasn’t even been 24 months since that day, but the technology has already developed at exponential pace. Moore’s Law is holding true within the security robotics industry. The changes are coming fast and furious and quickly changing the idea from “nice to have” to “this must be part of my security program”.
In the podcast Jack and I discuss how the technology has changed since the early challenges they faced with just basic navigation, to the lessons learned, and how the sensor capabilities are truly just developing now. After recording the AI & Security Podcast with Jack, I have come to realize that the experts within this developing industry are really just novices to where this technology is headed.
Today, Jack Schenk is the Executive Vice President at Turing Video, where they focus on creating the software backbone that ties together multiple IoT devices such as robots, drones, and video cameras, into a single platform that supports the security officer, providing actionable intelligence, while he or she monitors and secures the facility—or as it will more likely be, facilities. Founded in 2017, Turing intends to develop the space between multiple security technology platforms and the human operator by developing complex, deep-learning software. Their initial platform has a focus on robotics and video, but they are also integrating drone systems as well. Turing has brought to market a robot, powered by Segway, that integrates their own proprietary machine learning software to create an integrated security robot that works with multiple security systems and human security officers. You can see more from the video below.
To get where Turing is today didn’t just happen. Twenty-four months doesn’t seem like that long of time, and although there may only be just over 100 security robots operating commercially in the USA, there has been significant data gathered from the experience. From the first robot on patrol needing to learn how to navigate around people, to today’s still novice world of security robotics, the data gathered has moved the needle from 0-65 quickly. Now the goal is to move the needle to Mach 1.
In today’s podcast, Jack Schenk talks about his experience with early stages in navigation, the development of deep learning platforms for the sensor packages, and where he thinks the next advances in the technology will bring us. If this interest you, please listen to the podcast here, on iTunes, now on Spotify, or where ever you get your podcasts. Enjoy.
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