Noam Maital is the CEO and a Co-Founder of Waycare Technologies. Prior to Waycare, Noam led global strategy projects in technology implementation, growth strategy, and financial due diligence. Noam holds a BSc, Summa Cum Laude, from Babson College with a dual degree in Economics and Strategic Management. Prior to his studies, Noam served as a First Sergeant in the Israeli Special Forces.

 

[02:13] Rekor

Eric: I was following up on our Richard Ford podcast on Log4j. Yesterday, CISA made an announcement that all the major government agencies were patched and good for Log4j. Then I read this morning that they have a list of affected software vendors and products. This afternoon, a couple of open source developers came in and said, "Hey, we've updated this on GitHub. We made it user-friendly, so you can actually use the list." And I'm like, "Log4j is not going away anytime soon," even though we're cured, supposedly. We'll follow up from before the holidays. Who do we have?

Rachael: Noam Maital, who is the CEO and co-founder of Waycare Technologies, a subsidiary of Rekor, has joined us. I feel like this is the first time we've ever broached the topic that he's about to share with our listeners.

Eric: We've talked about smart cities before.

Rachael: This is different, apparently. Noam can explain why. Welcome to the podcast, Noam. A lot of people would love to know about Rekor and what you guys do. It's a really fascinating sector.

Noam: It's emerging a lot in 2022, speaking of a new year. A big focal point as part of the infrastructure bill that was just passed, is going to be really around revamping our entire infrastructure. It’s not just the physical infrastructure, like we think about the roads but also the digital infrastructure. Rekor is in the intelligent infrastructure space.
 

A Dumb Piece of Metal for City Mobility

Noam: We’re thinking about how we bring both software and hardware solutions to bear, with advanced AI using the data around us. That includes both the data from the infrastructure, so the cameras, the sensors that are in these cities, or state agencies. But more importantly, also broadening out into the vehicle side of things and the data that's coming from outside the infrastructure.

We like to think about our vehicles as these dumb piece of metal. But in reality, they're connected all around us, whether through our phones or through the vehicles themselves. They’re providing an immense amount of data that is extremely useful for understanding context on what's happening on the road, traffic safety, and incident management. But all that data has to be processed together and then used in conjunction with one another.

So synthesizing the data using artificial intelligence and then providing a workflow and analytics platform for traffic management to these cities. In order to manage incidents better, to think about proactive traffic safety congestion management, all of these things that cities have done traditionally only through the lens of their own infrastructure. It’s typically on an Excel sheet scenario-based modeling, moving into the 21st century of how we think about managing this complex system.

Eric: Bob would sit there and say, "Yes, this should be a two-lane highway. We'll make that one a one-lane because Eric lives down that road." Yes, I got you. To give an example, one of your technology partnerships is Waze. You get information and you deliver information to Waze and Waze consumers.

 

A Long-Standing Strategic Partnership

Noam: We have a long-standing strategic partnership with Waze where it's a two-way data feed. They're sharing with us anonymized raw data around what's happening on the road, whether that's incidents or congestion. We're using that as one data source of many, along with other data partners, in our algorithms, to be able to better understand what's happening. Then surface that up to the operators in the city to make better and faster decisions.

One of the things we're using is for automated incident identification. To be able to move away from this manual process which exists today across the US, of waiting for a 911 call, at that point starting response to an incident. You're talking about delayed response, the golden hour of getting someone to the hospital. More congestion for every minute of the delay, versus using AI to automate the identification of the incidents. Being able to respond faster to that incident, and all the benefits that come from that, congestion, saving lives, et cetera.

The flip side of what we do is we share that data back via API into Waze. It allows them to provide that information faster and more accurately.

Eric: They might redirect me off of the road where there's a traffic accident, which helps me. It also helps the local authorities and people who are dealing with that accident by keeping the congestion down.

Noam: Even more so, it could be that they're aware of the incident. But there's a road closure following our reaction to the incident, that they're going to close two lanes. So being able to be aware of that, now they're going to make an algorithm decision on their side and the routing and ETA that will be smarter based on that information.

 

City Mobility Helps Everybody

Eric: That helps everybody in the free world. We can all relate and we have a relationship with Waycare Technologies, except for Rachael.

Rachael: Because I don't use Waze. Last year, you were doing an interview, Noam. You said a stat, but you had improved response time by nine minutes or something, which was incredible. Literally every minute counts in these situations.

Eric: When I'm late and there's an accident, every minute counts.

Noam: There's follow-on derivative statistics from that. First of all, we've been able to show, with our customers, that we're able to identify incidents faster by nine minutes, which is dramatic. When you think about the very first thing in importance, I would say, is life and saving lives.

Eric: I was thinking my 45-minute commute, nine minutes either way is a benefit.

Noam: That's number two. Actually, it’s called secondary crashes, which we don't think about as drivers. But one thing that happens often, you probably have experienced this, where there's an incident that occurs. Right behind it starts to be an abrupt driving behavior because people are either slamming the brakes quickly, swerving. That's creating risk of a secondary. That happens very often. There's some estimates between 15 to 25% of the time, very often when that occurs. It depends on where it is on the road.

So by responding quicker, you're reducing that crash from occurring, a secondary again. Both of those together, combined to congestion. So for every minute that the road or a lane is blocked, there's some estimates that say you're creating eight minutes of congestion following that. The faster you're able to reduce it, you're able to save minutes of congestion for the entire public that's coming behind on that corridor.

 

[8:02] City Mobility Is Benefitting the Consumers

Eric: You're benefiting the consumers because they are able to be rerouted. Or they can at least call somebody and say, "I'm running late because of an accident," which I now know about. They're safer because they know about an accident, so they know to take some precautions as they approach it. But you're also helping the municipalities and the first responders and everybody else. You're increasing awareness of something abnormal.

Noam: There's two parts to what Rekor does here that's also important. One is the algorithms and identification. That's like half of the picture. The second part of it is, in the municipality side today, each agency has their own siloed system. So the police will have their own environment. Traffic management will have their own systems. None of them talk to one another. Literally the way they interact today is either no interaction at all or through radio systems, which have been around for hundreds of years.

One of the things we've been able to do, as a cloud-based infrastructure system, is allow for these agencies to start collaborating. As information's flowing into one system, it's quickly moving through the cloud to the other system. They're able to communicate back and forth, which means that the police can respond faster. They can share information from the road back to traffic management, so they can change the signals when they need to.

Some of this stuff seems very intuitive to us from the private sector. But when we go to the government sector, things that can be intuitive aren't always intuitive.

 

The Stovepipe Nature

Eric: I was telling a story to one of my employees today about the ability to call in air support in the army. It's almost impossible because the radios are different. They're just different organizations, so that stovepipe nature is crazy. The first responders aren't necessarily telling the city. Generic example. We have a problem. What they're doing is they're updating their systems and the city's going and seeing there's a problem.

On the radio, I'd be like, "We've got a problem on I-270." But we're not doing that. What I'm doing is reporting there's a problem on I-270. Someone’s sharing that data in the same system, and is seeing it. 30 different parties could see it. I don't have to call 30 parties. It's a one-to-one relationship almost. I update the master system, everybody's using it, and everybody knows.

Noam: 80% fair. The 20% of that is not just coming from a central system that's seeing the information. We’re also enabled when there is identification from the field. A good example is the service patrol. They're in charge of cleaning up the highways. When there’s someone stuck, getting them off, getting them some fuel if they're stuck, towing them off the freeway.

What they typically have done across the US is they have these routes, and they're patrolling them over 30 minutes. There's no awareness of an incident. No one's calling in to say, "Someone's on the side of the road." If it's not fatal or an injury, usually you're not going to get a call in. So they're just seeing people and stopping as they see them. What we've enabled them to do now is to be more proactive in identifying them, rather than just doing their long 30-minute routes.

 

A Multi-Way Information Sharing

Noam: Once they identify the incident, they're reporting it back to the central system and they are creating a new alert. It's a multi-way information sharing that's happening between each agency and new information coming in on each one. You even have the fire department involved and stopping when this gets too much in the weeds. But we don't realize, a lot of times, that when there's a hazmat event, anything that spills on the road, the fire department gets involved.

Then you have a whole orchestration of road closures and things like that. So they're adding more information into the system as well. Each piece adds onto the puzzle, if you will.

Eric: Through your partners, you're one of the central collection and dissemination components?

Noam: Yes. There are three pieces to it. One is the data aggregation and synthesis of that. So that's multiple partners in a data agnostic way. The second part of it is the algorithm side. The AI, where we're making sense of all this data and inferring out from that, what's occurring based on traffic safety congestion. Then the third part of it is on the platform side. Building that into very simple workflows for the operator, to give them the, "So what?" What does it mean that the algorithm alerted of an incident? What's the workflow now that you want to do on top of it?

Eric: We talked about AI a lot on the show and in the industry. I usually call BS on AI and cyber because I've yet to see any significant material capabilities.

Rachael: It's fair to call it a marketing term.

 

AI Will Be Big in City Mobility

Eric: Everybody loves it. I know RSA was pushed this year, but AI will be big there. This is an example where we don't have a human redirecting traffic in Waze. The system is making calculations based on hundreds or thousands of data points in real time to make the road safer. To get people where they want to go faster, the redirection, and the like.  That's true AI.

There's a machine of some sort, a computer, essentially, making a determination, "This road is closed. Take these four and go around it. Your arrival time is increased by four minutes." It's also informing me there's no human necessarily saying, "Traffic accident ahead."

Noam: The key to this is like what Churchill said, that history repeats itself. When you're using AI, you're using a lot of the historical data, at a very granular level, to understand what typically happens. This is where AI excels, and it has a lot of places that it doesn't excel. But where it does excel, it's faster and smarter than the human brain in terms of learning repeatable processes at volume.

And so, it's able to take years of crash data, years of congestion data, and hit the algorithm on that as the training set. Then you tie that in with real-time data. In milliseconds, it's able to identify how that reflects against the historical pattern and track whether that's an anomaly or not. That's where the use of AI comes into play, the benefits in terms of getting that nine-minute faster identification.

 

[15:15] Hacks to the Signal System

Eric: I'm in an ex-Soviet bloc country, and I want to create disruption in the Washington DC area. We'll go to Houston. How do I alter the data so that the AI creates an accident that isn't there, or traffic conditions? What are you doing to prevent that alteration?

Noam: It's a really good question. What can and what is happening, to some extent, in some municipalities is that there are hacks to the signal system or ransomware of sorts. 

But it's actually easier to do and manipulate when the systems are binary or scenario-based, meaning the legacy type of formatting. There's less brains behind the decision point, so it's a binary.

Eric: Single data feeds.

Noam: When you change it, there's very little way to track whether that change was the right one or not. It's on-off switches, versus when you're using AI. The way you build the right safeguards to that is continuously monitor whether the data is within the trend of what the data should look like. For example, if someone's manipulating a dataset to say that there was an incident, but every other data source on our congestion feeds from the diversity of data source we're bringing in is showing us that there is no congestion there.

Even as it's coming through the algorithm that's being trained on that data, it will say, "Okay, this one data point seems off from the rest of the datasets." And so, think about almost like pieces of the puzzle. One piece doesn't give us the full picture. But if you have all the pieces together, then you'll know.

 

Building City Mobility That Have AI Capabilities

Noam: Now, obviously, you have to build around those safeguards and everything. One of the important things when you're building systems that have AI capabilities, so they don't get taken advantage of, is make sure you diversify your datasets. So you have multiple types of similar datasets that you're able to compare one another. You're not relying on one or the other as it's manipulated, that could flow into the outputs of the algorithms as well.

Eric: It's really the diversity of the data, but also the scale. The amount of data you would have to co-opt, essentially, to falsify it and the difficulty. Because you've got that historical view, that would make it really difficult to do.

Noam: Let's put it in context. That's actually a good point. Right now, within a traditional traffic management center within a city or state that we work with, we'll see about half a million data points per month. Data points being any event of a congestion or incident. When we work with our connected vehicle, this is only from the infrastructure, meaning the sensors, the cameras, things that traditionally have been there. Once we start bringing in the connected vehicle data, we're looking at about one in 10 vehicles on the road, in real-time.

It’s growing every day. Again, it's important not to confuse this with autonomous vehicles and how we think about connectivity there. Connectivity today, from within the vehicle's almost everywhere. It is not rocket science. It's just a chip within the vehicle that allows you to be connected, or even your smartphone in some cases.

 

City Mobility Brings Massive Growth

Noam: But my point is that when we look at that amount on a monthly basis, we're seeing about two billion data points per month coming in, compared to 500 million. So half a million data points. Massive growth, which to your point, makes it a lot harder to manipulate two billion data points that are coming in real-time. If you manipulate one data point, that's not enough to affect the entire picture as you're using it in a cumulative manner.

Eric: I'm going to play the adversary for a second here. This is a good news, bad news story for Waycare Technologies. Instead of attacking Waycare in the systems on the back end, what I'd probably do is try to get into a vehicle autonomous driving system and cause an accident or something to create disruption. It sounds like it's a lot easier. The benefit to your tech is, you'd be able to report on it quickly because you'd see that accident.

But it doesn't sound like there's an easy way to create disruption in the environment through you. It would actually be more direct. You would want to turn the power off or impact a water facility, something like that instead.

Noam: A way to put it is that Rekor is like a system of systems. So we're using multiple data points and operating as a system at a level above. One of the big risks, as we move to a connected car environment, is the individual car level where you can hack it and manipulate it.

Eric: It’s much easier to attack.

 

Get In Your Own Tesla

Noam: I have a friend who's in a startup in this space. One of the ways they would pitch to investors is actually have them get in their own Tesla. Of course, every VC partner has their Tesla. Then they would hack the location of the Tesla and the navigation system and have it make turns that it wasn't supposed to. So that's a very real scenario that we're talking about. It's one that OEMs, the automobile companies, are putting a lot of money towards trying to safeguard it. A lot of cyber security companies around that space as well.

Eric: But you've got to protect each and every individual car where your system, because of its scale and number of data sources, has inherent resiliency in it.

Noam: We have responsibility to both, but we're treating or focusing more on a missing piece, in our mind at least, that the industry hasn't talked about enough. Which is, sure, let's advance and move forward onto connected autonomous vehicles. It's one thing for the vehicle to be able to interact with the vehicle next to it, or even the ones beside it, within an intersection.

But if you zoom out three or four times, that vehicle has to interact in the space of a city of 12 million vehicles now, that all have to be moving along in unison. Right now, the systems we have just aren't adept for that type of methodology of managing our transportation network.

Eric: Rachael, I know you wanted to talk a little bit about ransomware in the space.

 

[21:03] Autonomous Cars for City Mobility

Rachael: I do. But I love autonomous cars. I can't wait till I have an autonomous car. I’ll just sit in the back, maybe watch a movie, read.

Eric: You wouldn't even need a house  if the gas or electric is cheap enough. You could just live and sleep in the car and drive around all the time. Have someone drive you around, have the car drive you around.

Noam: A new category for homeless people.

Eric: Rekor will be tracking you the whole way, anonymously, of course. "Oh, there's Rachael circling the beltway again."

Rachael: Even my dogs love going in the car though, and sometimes I'm a little busy. Problem solved. They can hang out the front window and do their thing. I'm in the back working, multi-tasking.

Eric: You could even put them on the steering wheel, let the car drive you around, and make it look like they're driving.

Rachael: Anytime we're talking about data, especially data of this magnitude, there's always ransomware picking up in the world. It is circling in your world or becoming a more looming threat.
Noam: It definitely is. Last year showed us that there's two things that are really important to think about. One is that the cloud in the government space, I'll talk specifically about the traffic side, has been still in an evolution phase or a newcomer, developing or emerging technology.

Eric: They're early adopters, is that politically correct?
Noam: Let's call it that way.

Eric: Well, actually they're late adopters. But they're early in the adoption phase for the government.

 

Why We Have To Accelerate

Noam: That's a more correct way to put it. They're early in the adoption phase, and this actually means we have to accelerate. The reason it means we have to accelerate is, because on one hand, the amount of data that I just referenced here, there is no way to do it on premise. The costs and the complexity would mean that every city has to turn itself into AWS. I don't think any of them have that desire or capability.

But the flip side is, if you are only emerging in cloud technology, then you're more susceptible to the threats of ransomware because you have less safeguards.

Eric: Which we're seeing across the landscape with cities, city and state governments, towns. They're heavily targeted now.

Noam: While you could hack AWS or others, that's much harder to do even though they're bigger, because of all the safeguards that are in place. One of the decisions we made early on in the startup life was to invest to put all the safeguards that the big companies would have. Even though we were still early on, whether that's SOC 2 compliance and all these different measures that we took. That's really paying dividends as Rekor scaled up.

We've been able to give our customers not just the comfort, but also the knowledge of how to build their cloud environment in a way that scales, but doing it safely. It's something that this year has to happen much quicker. The threat is actually moving slowly on the adoption curve of these cloud solutions. Puts them more threat as they're less mature on the safeguards that they have in place.

 

On the Adoption Side

Eric: Their risk is going up because they're moving more slowly on the adoption side.

Noam: Think about it this way. It's like the risk of your four-year-old or five-year-old learning how to bike on a bicycle, learning how to ride. For him to fall off the bike is higher when he doesn't really know and he's just starting. Even if he's going slower, he's still going to fall, versus when he's 10 years old and has been riding for several years.

Eric: He can go blindfolded.

Noam: That's the equivalent.

Rachael: Cloud is tricky. It really is like an art form. You have to have the right talent to do it well. We've talked about that on the podcast.

Eric: It's a new generation, a new way of thinking. A lot of times you get technology laggards that are definitely inhibiting the migration tool and adoption of the cloud. I'll tell you, the best is probably what I see in the government, the cloud. You spin up resources when you need them and spin them down. In the government, what I mostly see, they spin up resources and then they spin up some more. But they never spin them down. We're not using it. Amazon will keep billing you. They don't get it. It's a different mindset.

Noam: The problem is, when you talk about the data from the connected vehicle side, it's not even a reality to do that. You're talking about such amounts of data. There are estimates looking at, from autonomous vehicles, up to four terabytes of data. So if you take millions of vehicles on the road, one vehicle, four terabytes of data per day.

Eric: Over what period of time?

 

What a City Mobility Vehicle Has

Noam: A per-day basis is the estimate on that. Every vehicle has LiDAR, video, sensors, and massive amounts of data that are expected to come.

Eric: They don't have the communication infrastructure to deliver that.

Noam: No. What you need to do is disseminate the important information from four terabytes. Even at the vehicle level, you have to narrow it down to what matters, shoot it out to the cloud. But still, massive amounts of data. What you need is to build processes for scale at the government side. They don't have the skillset nor the budget to do it yet. That’s where the appropriate part of a third party like Rekor or other vendors in this space really come in and work in partnership.

That's a lot of what's missing here. It’s not just selling a solution, but also education on how to build this environment that brings the government agencies forward in their cloud capabilities.

Eric: I clearly see the need for it. That way they can benefit from the data, but they don't necessarily have to figure it all out on their own. I'm just thinking of some government customers. If they had to build a system like this from the ground up, it would never get done.

Noam: Fair to say, some government agencies believe they can, and they are taking it. Time will tell whether that will happen or not. But most likely, if you were to look at the base facts of the budgets they're able to put forward to it, or the type of personnel they have, usually, what you're going to need is some marriage of the private and public sector coming together. They have the know-how of running the municipalities and the systems.

 

[27:46] Working in Unison for City Mobility

Noam: Private sector's coming in with that technology. It's working in unison together to bring that forward. Part of it is the infrastructure as well. We haven't talked about that. But one of the things that Rekor is doing is bringing in the physical infrastructure as well. So computer vision at the edge with the cameras and using that data as part of their own data ingestion. That's their own data that they can use. Also, it’s a whole other field that's new to a lot of these cities.

Eric: They have to be able to receive or do something with the data, once you even pull it together. Like if they don't have systems linked in, they know there's traffic construction on this road at this point. But the rest of the other government entities in that region need to be able to receive that information. Take it in and understand what it's telling them, there's traffic and construction there?

Noam: Right now across the US, the base case is that they don't. You would be amazed at the lack of interoperability of systems and the analytics across the space. I was saying this earlier to you guys. It's behind the curtains of everything we do on the road and the transportation space. We don't think about it, but it's going to rear its ugly head in the next five, 10 years, if we don't do anything about it.

As we move forward to more automated systems of connectivity and autonomous vehicles, we're going to rely on the infrastructure, not just physical, but digital, to make smart decisions for us. And yet, we have smart cars on dumb roads. That is going to come to bear if we don't take some bold action.

 

City Mobility Smart Car

Rachael: I don't want it making decisions for me because I think you speed too. I can get from Houston to Austin in under two hours. It's amazing. But I don't want my smart car to be told the speed limit.

Eric: I'm sure there will be a Rachael override. Speed limit plus 25. That feature will be there, I'm sure.

Noam: That is a great, though, stepping point to a question for you, on that optimization. Now let's say you do that trip 10 times a month. On rare occasions, you do it at 2:00 AM when the road's empty. You can do it in two hours. But on other occasions, you have traffic. Now, what if I told you, okay, you won’t be able to go the speed that you wanted at 90 miles per hour, but you'll go at 65. But we're going to adjust all the speeds dynamically so that you're not stopping and going and congestion is less by 20%. It will actually reduce your arrival time by 15 minutes.

Eric: You'd have a fight with Rachael and you'd have to prove it to her. She wouldn't believe it. She’d just want to go fast in the back of the vehicle while sleeping.

Noam: You would be skeptical until you actually arrive 15 minutes earlier, the first, the second, third time.

Eric: If you can synchronize, if we had those smart systems leveraging the data, everything would be faster. It's like that person who's zigzagging in traffic, stop and go. The 50 cars behind him or her are massively disadvantaged because of that erratic behavior.

Rachael: Or the person driving too slow. That's what we see on 290.

 

Speed Harmonization

Noam: It's called speed harmonization. You've each experienced this. You're driving on the freeway and you're going at 70. All of a sudden, you go to 45 and you press the brake.

Eric: Somebody's texting and they slam on the brakes. You almost hit them because they weren't paying attention.

Noam: Now what happens? You press the brake, but your brain has a delay between your thought and pressing the brake. The next person has the same delay.

Noam: The next person has the same delay on breaking and so forth, repetition of hundreds of times. You're adding cumulative minutes of congestion back and back. 

So if you're able to actually affect that and build systems that are able to interact together in harmony, you're able to remove all that congestion, or at least harmonize in a much better way. That's what I'm talking about here in terms of building smarter systems.

Eric: I observed this firsthand. I was probably 18 the first time in the army. A division level run, which is 15,  20,000 people, probably on sick call or busy or doing something else. But if you're in the front, you set the pace. If your pace is erratic, the people in the back are either stopped, in some cases, or they're sprinting as fast as they can to catch up. The further back you are, the more that it ripples back and almost multiplies. It's not synchronized, harmonized running. The exact same thing happens on the road.

Noam: It's what we call the snake that builds out. There's a lot of ways that you time it. But it's a real thing, as we get more vehicles on the road, and we're not going in the positive direction here of getting better utilization.

 

Autonomous Vehicles

Noam: So autonomous vehicles won't solve that, actually. It doesn't make more people get in the same vehicle, and COVID doesn't help that either. So single-usage vehicles are going to continue going up. You're just going to get more of these delays that's backing up and we're going to be stuck in traffic.
So both on the safety front, but also on the congestion front, it's not enough, even with this infrastructure bill. It puts forward billions and billions of dollars to build more roads and infrastructure. All that's great. But we can't build our way out of it. There's too much demand and vehicles on the road.

Eric: We need to optimize.

Rachael: We have to go up, is what we have to do.

Noam: If you ask Elon Musk, it's time to go under the ground.

Eric: You were talking about the government not having the budgets, the capability, to put the road systems in place. I'm assuming things like harmonizing street lights with the pace of traffic and things to make flow better. That's a government function.

Noam: But to be accurate, they have the budgets, and probably one of the biggest misnomers is government budgets. They have the biggest budgets in the world. It’s bigger than Apple, Google, and Tesla and all these companies combined. They have the most consistent stream of revenue on this planet, which is taxpayer dollars. But the challenge is that they don't have the allocation on things like data science and whatnot to do internally. It has to be something that comes out from the external partners that come in.

 

[34:33] A Massive Boost To Invest in City Mobility

Noam: This infrastructure bill of 1.2 trillion gives them a massive boost to start revitalizing, and invest in it. It's three times the amount that they've had in their budgets. They have to spend it in the next five years. We should expect to see really big changes if we act correctly in our transportation network, hopefully for the better.

Eric: The governments have the budgets, they should have the capability. The infrastructure bill's driving them in this direction in some fashion. Let's assume they don't move fast enough or they spend it on ferries or something. Do you think that society may accommodate that anyway?

We were talking about Waze. I’ll change my driving behavior. I can program in when I'm going to leave. Waze today, based on your data in part, tells me that it's going to be an hour 20-minute drive if I leave at 8:00 AM. But if I leave at 6:00 AM, it's a 35-minute drive.

Government lately has lagged the modernization on the IT side, things like the cell phone. Consumers buy this tech and we just use it and we become more efficient. Could the same thing happen on traffic safety roads where the governments just don't move fast enough? But because of technology like this, you drive the benefit out regardless of the consumer. It still helps Rachael get from Houston to Austin faster.

Noam: Only someone that holds a crystal ball of the future will know the absolute answer. If you think about what is required, what's the fundamentals in that question, systems may be smart enough on their own on the private sector side, to optimize their own route for themselves, or even their own drivers.

 

A Regulator To Manage City Mobility

Noam: Your drive now to optimize itself, goes through a school zone where lots of kids are just going to school. It creates a 50% risk of a crash that includes pedestrians, and one of them is going to be a kid.

Now, here’s the fundamental question. Do we believe, at the macro level, that we need a regulator to manage a network of our road systems in our cities and our communities? The role of the city in general is to manage our general services. Or is it a free for all where everyone is optimizing for themselves and there isn't this general rule maker, regulator.

Eric: Which is what we have today, for the most part.

Noam: Today we have a regulator. When you're on the road, you have a speed limit. If you go over that, you're going to get a ticket. Now, the way it's orchestrated, it's archaic, I guess, is a good point to say. But if we don't have that, in my mind, if we don't have some level of a regulator that thinks about the communal benefit of everyone, and maybe you get 5% less benefit, but everyone gets 20% together benefit on their road environment, then we're not going to actually reach full autonomy, in my mind.

What we're going to have is this hodgepodge of systems, each OEM choosing their own systems, each technology optimizing for its own services. We see that a bit today. You see how that operates today and the challenges of it. And so, we're going to have to build this smarter infrastructure. I do agree with the risk though, that the government can sometimes move slower.

 

The Importance of Shifting the Speed of Technology Adoption

Noam: It only brings the importance of us shifting that speed of technology adoption and penetration. That is why I'm excited about the opportunity. The timing with this infrastructure bill gives these government agencies a lot of the leeway to do things from a technology side, that they haven't been able to do in the last 10, 15 years.

Eric: What I heard you say is, without government, we'll get marginally better, for a period of time, at least. But we need the government to reach full optimization. The infrastructure bill provides them the capabilities to do that, should they be able to.

Noam: As simple as this. Right now, autonomous vehicles are using technology for computer-vision, to look at the road at the lane markings, the painting. Who's in charge of painting the lines? The cities, the government states. So unless they have a smarter system of doing that and regulating that, unless they upkeep that properly, the vehicle isn't going to know where it's going. The intertwined nature of it is inseparable.

Eric: If they paint different types of lines, the car systems which were designed for one type may be spoofed and not be able to recognize them. So there's that yin and yang there.

Noam: Most people don't realize how intertwined it really is.

Eric: You'll be speeding for a little bit longer behind the wheel. At some point, we think you'll be able to speed while you're sitting in the backseat, reading a book or taking a nap or hanging with the dogs.

Rachael: By then, I probably shouldn't be driving. That would be really good if it worked out like that.

 

Coming Together

Eric: It would. But it's going to take the infrastructure bill, the cities and states, and everybody doing this and coming together with the data.

Noam: The utopia is that we're smart enough to build out, just like we're thinking about our physical infrastructure. An entire digital infrastructure ecosystem where all of our roadway systems are digitized. 
So we have what's called the digital twin. We're able to replicate our physical environment with a digital environment, turn it into data, which is using AI, to optimize our network. Then we're moving on our roadway system in an optimal way, both from a safety and travel time perspective.

Eric: That seems difficult. I take it back to security. A lot of organizations, the government especially, do physical security so well. Because they've been doing it for a hundred years and this is the way it works. Fences, cameras, guards, the like. When you take them into the IT space and they have to do cybersecurity and they're dealing with less tangibles, there's a chasm that doesn't get crossed many times.

It's just hard for people to tangibly understand that it's a different world. I can enter and steal a truckload of information. Or I can just keyboard in and steal a warehouse full of information. Which one's easier?

Noam: I was in the military and I learned that rules are written with blood. In a similar way, governments will probably learn the hard way, once some of these threats do become real. The good news for the cybersecurity industry is that there's going to be massive demand from the public sector side to build in some of these systems that are starting to be built, in the banking system, financial systems. That's going to come soon as well.

 

[42:06] Additional Security For City Mobility

Eric: I was engaged in an effort with a manufacturer at one point. It was a couple pennies to put some additional security into their devices. Devices were not that intelligent, by the way. They were like washing machine type concept devices, and it just wasn't worth it. So I hope so. I hope we do see that there's a benefit to better protecting things in the future, our assets.

Rachael: Like secure by design. If you're getting a chance to build something new, like what you guys were doing, thinking about it at the beginning versus trying to bolt on at the end, lots of goodness there.

Eric: Tesla is a little different, more dangerous than a washing machine.

Noam: 100%. The challenge is hardware versus software too. Hardware is going to be a lot harder, no pun intended, to modify as the penetration happens. When someone finds a way to hack the hardware systems, it's harder. Versus software, yes, you can hack it, but you can also modify it. Fix it and build patches. It's going to be a really interesting next three or four years in this industry, because it's at a tipping point.

Rachael: I'm so excited for what you guys are doing. I would love to stay in touch because I just see this going all kinds of cool. Finally, we get the infrastructure bill and like, "Let's go do this," and how do you figure it out? You're in an exciting space.

Eric: I just appreciate you making our commute faster and safer. I love the fact that smart people are working on that.

 

City Mobility Is Such a Big Challenge

Noam: People always tell me it's such a big challenge. It's such a challenging industry. What I often will say is the biggest opportunities in the world are often masked by the biggest challenges.

Eric: When I see a big challenge, it usually gives me a hint that there's a massive opportunity behind it. We wish you and your team at Rekor a whole lot of luck.

Rachael: Thank you so much for joining us today. I learned a lot too, that's why I love security. Every day I learn something new. To all of our amazing listeners, happy new year! It's going to be awesome. What's even more awesome is when you smash that subscription button and then you get a fresh episode in your email inbox every Tuesday. Until next time, stay safe.

 

About Our Guest

Noam Maital is the CEO and a Co-Founder of Waycare Technologies. Prior to Waycare, Noam led global strategy projects in technology implementation, growth strategy, and financial due diligence. Noam holds a BSc, Summa Cum Laude, from Babson College with a dual degree in Economics and Strategic Management. Prior to his studies, Noam served as a First Sergeant in the Israeli Special Forces.