Parking Network’s Interview with Chris Scheppmann
Parking Network’s Manoj Hedge interviewed EnSight Technologies’ Managing Member Chris Scheppmann, where he discussed the unique value of the EnSight Ecosystem and why EnSight sees an opportunity for parking operators to leverage cameras for a variety of applications, not just space counting. Watch the video here or by clicking the thumbnail below. Enjoy!
Chris: We use cameras, machine learning analytics, and the software we’ve developed in-house to identify objectives, specifically vehicles, as they’re moving into or out of parking assets.
Manoj: Hello and welcome everyone for another Parking Network video. Today, I’m joined by Chris at EnSight. Chris, how are you doing?
Chris: Doing fantastic. Thank you for having me!
Manoj: Thank you for joining. So, as a new member of Parking Network, what does EnSight do? Can you provide a brief introduction to the company, and to yourself, please?
Chris: I’m Chris Scheppmann, one of the co-founders and managing member of EnSight Technologies. At EnSight, we are a software technology company that specializes in vision systems to track, scan, and count cars. Delivering solutions for garages, surface lots, traffic studies to identify vehicles and traffic flows into and out of parking assets to enable parkers to better understand, through very accurate machine learning and AI-based vision technologies as to what is the best parking locations for the parkers. And then, taking that data, understanding the metrics of how cars of moving, where cars are going to present that business intelligence to parking asset owners.
Manoj: OK. So, what is this EnSight Ecosystem?
Chris: So, the EnSight Ecosysem… we built what we call a “Smart. Simple. Scalable” solution. Everything starts with our vision systems. So, at the core of our ecosystem, we use cameras, machine learning analytics, and the software we developed in-house to identify objects, specifically vehicles as they’re moving into or out of parking assets. And, within our Ecosystem, we have a number of modules, since we do use cameras, those cameras not only identify the traffic movement, counting the vehicles, between various entry and exit points, level changes of garages, zones within surface lots or garages themselves, and that data is then passed to digital signage to enable parkers to understand where the best locations to park. But, since we are using cameras, we wholeheartedly believe that vision systems are the way of the future. Not only with the advent of machine learning and AI technology to very accurately identify objects, but with cameras it’s really the eyes to the operations. So, we leverage that to understand what’s going on. We can layer on surveillance modules, so as we are providing parking occupancy management systems to our clients, those cameras can naturally be turned on and tuned for surveillance. So by increasing security with those cameras, what we believe, can be the unique identifier of understanding the unique traits of vehicles. So, license plates, color, make, model, all of those important characteristics of vehicles and the unique identifiers can provide paramount value to our clients to understand not only how many cars are moving where and what are the traffic flow patterns, and identify who is going into a parking asset. So, we have cameras, signage, surveillance modules, license plate recognition, we have an open API platform. So, all the data and analytics that we collect, inherently, we can connect to third-part applications. Whether that’s for cities to pass over these traffic and parking asset metrics to larger platforms to be part of that smart city ecosystem. And, really, it’s built in a way where we have clients that are very small, who have small garages or surface lots, but then by layering on cameras and additional signage at key decision points for parkers, it’s very simple to bolt-on these modules to scale it as granular as the client wants. So, we really got out start and the reason why we spun up EnSight Technologies was because traditionally when you’re counting cars, there’s really only two options. There was your very entry level system, which was your conductive loop sensors and ultrasonic sensors in the ceiling to count cars when they moved in or out. So, that was like your base entry system. And then, you had the full-scaled operation of lights, sensors, single-space cameras for those larger enterprise-type clients airports or casinos and what we found was on the entry-level systems, conductive loops or ultrasonic sensors, inherently, well one, they’re inexpensive. So, when things are quite inexpensive, at a really attractive entry price point, the value of the system as traffic picked up or the occupancy of a particular location was reaching peaks, the technology was inherently inaccurate. So, although you saved a lot of money investing in these technologies it actually didn’t provide any value when you needed it. On the flip side of that, you then had the lights, the sensors, the single-space systems that are expensive. So, there’s kind of a void in the middle of providing a flexible scalable, module system that’s very intelligent and accurate, but at a price point that’s reasonable for the masses. So, our history, we had a software company that we deployed vision systems internationally for ports and intermodal facilities globally. So, we were in 14 countries worldwide where we put up cameras to track containerized cargo as it when into ports or intermodals facilities globally. And, when we sold that software company, we came into the parking business, and I have a dealer-VAR company local here to San Diego and Arizona; everyone wanted to track, scan, and count cars. But, as I mentioned earlier, you had an entry-level system or a very expensive system. Most people couldn’t afford the very expensive system, and when you deployed the entry-level system with loops it was inaccurate. So, I called up our software developers and product team after we sold the business, and said, “Hey, we tracked and scanned containerized cargo on a global scale using vision systems. Why don’t we take that technology and create an ecosystem using vision and the advent of machine learning and AI, which is the latest platform for vision technology, to provide a solution that is not only cost effective, but very smart, accurate, and intelligent to provide technology for the many and not the few. So, that’s kind of our slogan. So, we want the intelligent technology that can be deployed for the masses and not technology that’s either very expensive so you only have a small percentage of that market that can invest. Or, put in systems that were inexpensive that weren’t smart. So, that’s how we launched EnSight Technologies. The company was founded at the tail-end of 2018. With the pandemic, of course, all of us in parking understand the ramifications there. So, in earnest, in business for the last two-and-a-half or three years now, and getting a ton of traction in many market verticals.
Manoj: So, what are those verticals? Where would you say is the focus with the company, where you stand out?
Chris: You know, so, when we launched, our slogan is “Providing technology for the many and not the few.” So, really, it’s applicable to any market vertical and we’ve successfully penetrated most of those—universities, university campuses, corporate campuses, mixed use, retail and malls, we just landed our first airport—so the Boise Airport will be leveraging our technology to provide accurate data for the airport and are not investing in single space technology. So, we’re really tapped into all these market verticals. Anyone who is interested in understanding their traffic flow metrics, providing valuable data to their parkers as to where to go to optimize that traffic flow, but also to mine that business intelligence of understanding where people are going, how much time they’re spending at those locations; then we bolt-on things like our EnSight Plates, or our license plate recognition module we can get granular to the point to who is parking, taking those unique identifiers and integrating them with solutions for digital, frictionless payment, in addition to driving occupancy management and traffic flow data.
Manoj: So, I have one last question for you. You’ve already hit on a lot of interesting topics. You mentioned 14 countries. Where would you say you’ve really succeeded and where you’re really growing?
Chris: So, that was our prior software company called APS Technologies, where we were tracking and scanning cargo. Currently at EnSight Technologies, we’re laser focused on the US market, got our first few accounts in Canada, and we are having conversations for deployments in Australia and Europe. Right now, our current footprint has us in 14 states in the US and then a couple deployments in Canada.
Manoj: Well, Chris, I wish you all the best with the development and growth within the US market, and good luck!
Chris: I appreciate that, thank you! We’re excited.
Manoj: Thank you for joining today.
Chris: Thank you and thanks for having me.
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