 What I wanted to talk about today is a more practical approach to digital twins, from the perspective of the land surveyor. So again, I take NAC, and we're a little bit about TopoDot. We are an application as a software that is dedicated to realizing the value of point clouds. That's what we do, the extraction from data collection. We're the bridge between data collection to the deliverable, the topography, the digital twin, what that might be. Extract features, extract assets, extract anything from basically mobile LiDAR data, point cloud data, any point clouds that any data that is collected. We're located in Florida, Orlando, Florida. We have offices in Europe, the UAE in China. And we have about 6,500 users now, 750 companies. And we do most of the mobile LiDAR processing, basically transportation processing is done with TopoDot in North America and much more in Europe now. So it's a little bit about us. So we're talking about digital twins. And it's interesting because if anybody's had interest in digital twins, everyone knows what they are, but no one knows what they are. They know they want a digital twin. I need a digital twin. What digital twin do I need? Nobody knows. So I went back to the beginning, and I talked about this. I said, OK, let's look at the definition because it becomes clear. A digital twin from the Digital Twin Consortium, it's the best definition I could find was it's a virtual representation of real world entities and processes. Synchronized as specified frequency and fidelity. OK. So it can be anything. It's a representation. I like there's a saying from an old British statistician, all models are wrong. Some are useful. If you have that in your mind, you can understand digital twins a little better. So the question is, and this is for the, again, from the perspective of the geospatial technician, the geospatial expert, the geospatial professional, how do you organize your operations to meet this demand? That's a key. That's a question. So basically the question is this. The real digital twin challenge is, how do I synchronize digital twin production frequency with extremely dynamic processes? We typically, our customers work in construction environments in planning and things. And it changes all the time. Anything along a transportation corridor changes. What digital twin do you need? When do you need it? How do you optimize digital twin fidelity? And fidelity is actually, how much do you model? How accurately do you model it? What do you model? You can't just ask for a digital twin, no one knows. And no one digital twin will meet everyone's requirements. And the gentleman here was speaking about digital twins that are nothing like the digital twins we talk about, which are topographies and things. Yet they're both called digital twins. So how do you do this? How do you assure quality control of digital twin production? So how do you know that the digital twin is coming out that someone's going to make extremely, especially in this environment, extremely expensive decisions that digital twin has met requirements? The idea of a single source of truth, who's heard of that? The single source of truth, you go and everyone, every engineer can go to the digital twin. No, I can give a point cloud, I can give a point cloud to five engineers, the same point cloud, they'll measure in it and get five different measurements. And if we're within a meter, I'll be astounded. You have to have another process. How do you optimize a schedule and cost? Digital twin production is not inexpensive. There are people extracting the model, there are people processing the data, there are people doing this. You can't just say I want to model everything into the best fidelity possible so everyone can use it. No one wants to pay for it and it'll never be ready. And it keeps changing. That's the real problems with digital twins. So in TopoDOT, we have a solution. And this solution to meet the digital twin challenge is called TopoShare. Now, let's go back to the TopoDOT model. Now we, again, our fundamental process is how you extract value, how you basically extract digital twin, whatever that might be, from point cloud data, from mobile data, from airborne data, from whatever data you have. So in TopoDOT, we start in the orange is outside of our world. That's where you acquire data. We deal with point clouds. We don't care where it comes from, points or points. Inside of TopoDOT is the green. That's the process. How do you manage the data? How do you assess its quality? How do you extract what you need? And then how do you assess the model that you've extracted, the digital twin that you've extracted? And how do you make sure it meets your requirements and that you can then deliver it? So at this point, we have a tool, TopoShare Basic, inside of TopoDOT that will let you organize your data in the cloud and access it very quickly. And you integrate our quality control process with geospatial operations. And basically, you support whatever the operations may be. So you have a deliverable request. The deliverable request goes to an administrator, the geospatial operations. They say, you need this. This is typically what happens today, in 90%, 80%, 90% of the projects. You access data. In the TopoDOT users, we'll access data like this. They'll find their data, and this will be their interface to their data. They'll click on a particular project. They'll have that at their desktop. They'll select, I need this tile. They'll bring it in. And with this environment, they can share it with 10, 20 processors. They all go to the same place. They all pull it. It's very simple, very straightforward, and it's a file-based transfer and storage, which makes it very inexpensive. Keep in mind, once you leave file-based storage, file-based transfer, it becomes expensive because you use processors and RAM in the cloud. So everything you'll see is file-based. There's a reason for that. And then you extract and deliver your project. And that's what happens all the time. We do all that. Our customers do that every day. However, there's something missing. This is a pointer? No. OK. The supported operations now have no way they don't know anything about the data that's up here. It sits there. Gigabytes, terabytes, petabytes. No one knows. And if someone has a question here, they don't know where this geospatial guy is. He did this six months ago, a year ago. It's needed now in design, engineering, operations, construction, maintenance. So everyone wants to make that data valuable, but no one uses it. And then we see many times this in the supported operations, they just go survey again. They send somebody out and go measure something. It happens all the time. And there's a reason for that, too, because this geospatial operation doesn't necessarily want to hear, hey, can you give me a clearance from a bridge that you did two years ago? It's a lot of work. It's not a happy call. So how do you do this? Well, we created Toposhare Enterprise. Now, Toposhare Enterprise is a web portal. And what that does is just a website that ties this access. So basically, all your supported operations can now see into the data warehouse. They don't have access. They can't change anything, but they can see. We give them the portal. And project data and metadata can flow to them as controlled by the administrator. When they find this data, they can actually go and say, can you give me deliverable requests? I need something from you. I need this product. I need this answer. I need this digital twin of volumes. I need clearances. I need a level one survey topography from this point to this point. So they have access. And you create this ongoing usage of the data with that access. So the question is, so this is digital twins delivered on demand. That's our concept. It's impossible to do a one-truth model. It has to be what you need, when you need, where you need it, at the lowest price and the quickest possible. That's what we're looking for. That's what we're achieving. That's what our customers are doing in the US now. And it's working. In this particular case, there's unlimited access because this sharing is through a URL. You're in just Google Map. You see everything. Everything you see, you look into this. It's a browser interface, any browser. So there's no cost. Give it a URL to 1,000 individuals. Doesn't matter. It's not costing you anything. Now, what does it look like? This is what you look like. You put TopoShare into this access. You might want to see the city of Perry, Foth, where this was laser scanned the entire city. This is what an engineer might have. An engineer can have access to hundreds of projects that you give him access to, all controlled by the administrator. So what we see is, we see here is that we might be able to download the point cloud, but we create rasters in Topo.earlyon and upload them as metadata. So now this comes in in seconds. It's not 500 gig of data that costs maybe five, six euros to take in and wait 20 minutes. It's a raster. An engineer sees what you have. OK, that's a good first step. An engineer sees all the line work. This is road condition on the main road. They wanted that in this city. He can look at all this. This was done in Topo.ar. The process, the quality control process to extract it. The line work is there. There's some interesting. We're not S3, but we can put some text in there and tell you some things. But then there's also images. All the mobile lighter systems have images now. Well, we use those very effectively. You can click here and say, I'd like to see what's there. OK, I see what's out there. And I can also measure because Topo.ar allows you, in the pre-processing stage, to take data and attach it to the image. And then the image you can measure in the image. It's a layer of point cloud data. Now, the interesting thing here, I'm going to say again, well, first, and then right now, this is the work order request. So what our customers are doing now is you click. You can email the project manager in the geospatial department and say, I'm Mr. Engineer. You don't know me. You did this six months. I see you have this data. Can you give me this? And then the geospatial administrator can say, yes, I'll give you what you need, but what requirements do you have? Which is missing in the whole, everyone goes to the truth model. What requirements do you have? Will this data meet those requirements? What do you need? How do you need it extracted? So this is a quality control process. That's what we meant. So the bottom line, again, we just see it as not practical that all data will go to some truth model because it's very difficult to. We spend a lot of time training people how to do this in point clouds. And if it's that easy that you can just give a point cloud, everybody can do it, we're wasting our time. Although we don't. We keep training people, hundreds and thousands of people. So that's our process. Now, the other question might ask, well, and this is typical. This is one of our customers who we let you look at, create your own page. And this was about five, six months ago. So they had about 500 projects now. They have 700 projects. They can access any one of their projects. They can find an intersection, a point cloud, in their environment within a minute from over 600, I don't think, now it's maybe 750 projects, they said. They said even the interaction with engineers and their clients is excellent because their clients can see this also. But they said just the fact they can find this data so quickly is worth every penny because it's sitting on before, it's sitting on SharePoint drives, it's sitting on things. And if I have to find one bridge, it can take three hours. Now it takes a minute. And it's there on their desktop. This is all available. Now, someone might ask, everyone knows they've seen the immersive viewers. We like the immersive viewers. We think they're cool. The immersive viewers are, let me say some names, Point Terra, what else, UGrid. Well, even RGIS is not immersive viewers. Actually, it's a GIS database. But the bottom line is, how did this all fit in? Are we trying to displace this? No, we're different. We're organizing your data inexpensively. We basically support all of these. Because the reason is, and the main reason is, we meet these requirements. We don't compete with them, but this is what TopoShare, the TopoDot process, accomplishes. Comprehensive data governance, what that data looks like, what its features are. Supporting digital twin production, yes. You can't do that with an immersive viewer. You don't know where that data came from. It's laid on top of each other. You don't know anything about it. We always go back to the original provenance of the project data. Where did it come? What was its accuracy? What I extract from this? What can I sign off? Because the geospatial expert has to sign off and say, this is what I'm saying. This is the volume. I will sign this off and say, this is the volume. So the engineer can say, OK, here's the contract to move this much material. This has to be done. This is necessary if you're going to have a quality control process. Fast and efficient access to the original product data. OK, I talked about that. And then all of this digital twin production is now under geospatial operations from the extent that you use the point cloud, raw point cloud image data that's acquired with mobile lighter. You're in control. You organize that. Someone else may make a simulation. You might help work with someone else to make another type of digital twin. But the geospatial excerpt will be the start of all digital twins because we have the spatial data, and it starts with us. OK, implement execute at low cost. Yes, point cloud apps, not so much. They're expensive if anybody's priced them out. And then the most immersive viewing experience? No, it's not immersive. It doesn't panoramas and everything you want to see. And yes, and that's useful. But again, when you look at the price, what we're proposing in the way we do it is that it's 150 times less expensive than immersive viewing solution. In this particular application, we're showing you just one mile, so about 1 and 1.5 kilometers of data is 10 gig. In an immersive viewer tickable price, I looked around. I don't want to concede it's just a different technology, but all this streaming and storage and accessing a live interaction, it's $500 to upload that. In our solution, it's zero. You upload to your account in your Amazon Resort cloud. You upload that project. Storage price is $3 per year for that. I'm not sure how it works there. There's a locate data 2000, measure 2000. I don't understand it quite. It's a little complicated. But the TopaShare site visit, when you go into TopaShare, it's about $0.05 to look at raster data, look at things. And you can give them access to the data. So if you want to give them access data, you want to download it. That entire project can be downloaded on a desktop for $0.80. This is scalable. You can put, as I showed you, our customer 700 projects. It's not costing any money. But how does this fit in with the immersive viewers? Well, it fits in very well. You have this process, and you say, just feed it. If someone, you organize your data like this, the administrator, if the supporting operations say, I want to look at 10 kilometers of data along this transmission, and I want an immersive viewer to measure, you say, OK, where do you want it? Here's how much it costs, probably $4,000 or $5,000 a year, viewers a year. OK, good. If you need it, great. And when you're done, you stop. You feed it with the original data, and you make sure they get the data they need, where they need it, in this immersive viewer. We think this will work. We're seeing it work now. It's taking a while for the market to grow. But we're seeing now it's expanding. In the US, because they're starting to understand the usage of just this approach. And it's comprehensive. So you get the digital twin, where and when you need it.