 Good morning. Before starting my presentation or introducing myself, I want to just ask, how many people here have used Google Maps to get here? Please, yes, with your hands. I see almost 90% of everyone attending here have used it. And this is something I really want to emphasize about professionalism in our industry. It's reliability. Google Maps has been used by most of you because it's a reliable source of information consistently. And this is something I want to emphasize. So I think it's not working. Sorry, thank you. My name is Firas. I'm a project manager at CTO. And if usually I am called, it means there's a problem on precise location in construction sites or in GIS hazard problems. We work with multiple groups of constructions. And yeah, basically, if you have a position problem, I am here to help. I'm not here to sell anything today. I'm here actually to just present a big project that took a lot of efforts to do. So our mission, as I started saying, is fix problems anytime, anywhere. And we are based in the city of Nazareth. But we work all over. This project is in Jerusalem. But we also consult internationally to many companies that also face some of the problems that you'll see here. Yeah, that's an interesting video. So I'm going to mention a lot of stuff today. One of it is going to be VRS because it's what is most commonly used in our country. You see, there are three providers for virtual reference stations. I'm going to mention the size of a project and the accuracy and everything related to the project itself and how we're moving an old city to a smart one. Let's start with what makes it so hard to map the city of Jerusalem. And this is something that I've been facing for the past year. We're talking about, in a way, a hard terrain. We have a lot of gradients, ups and downs, which makes the terrain model not always precise. We have a lot of jumps in height. When we're speaking about buildings, we have a lot of high buildings and narrow streets between. And that makes connectivity to GNSS networks problematic. When we're speaking about really crowded areas all over the year, 24-7, we really tried walking at 2 AM and there were hundreds of people around the street strolling. I know it's not very common in Germany, but it is common in Jerusalem. We're going to talk about accessibility. And when I talk about accessibility, it means the way of bringing the equipment into the sites and to just measure. Because we're here talking about a really, really precise precision, high precision requirements. We're going to talk about security a bit because there are a lot of stuff that we were restricted to do while we were working. So it made our job much more difficult. And it all is, at the end of the day, can be seen in cost and efficiency for the project itself. So why did I mention VRS, as I said? Because most of the servers in the Middle East region are using virtual reference stations. And it is good for most parts. For 80% of the job, you can rely on that. And you see that when someone is going to order a job for surveying, they're going to ask for some requirements. But you see, when you work with the vendors all over the year, they're going to need something that they can rely on every time, every day, no matter what is the situation. And this is one I'm going to explain here. You see, as I said, if it's a narrow street, you're not going to see the satellites from the station that you're working with. And the base stations around you are going to be, even though they're going to have that connection, you're not going to have it. If, in a magical case, you're going to have that connection and you don't have internet connection, which is common around the city, it is also a problem. So we're speaking about multiple hazards concerning high and low terrains with dense high buildings and narrow streets while the area is crowded. Now there are VRS-based solutions and non-VRS-based solutions. And as we know, laser scanners and total stations or multi-stations are part of it, which can be the solution for part of the problem. And while the other VRS-based solutions are like mobile map is drawn, the RTK can be problematic as well on other aspects. So let's see when and how can we use what in different problems? See, when we're talking about total stations, multi-stations, the acquire of the data is very low in a matter of time versus costs, because you're going to probably be able to do 200, 300 meters in one day while using a mobile mapper on your car is much more effective in collecting various amounts of data. But the question is, how reliable, accurate, and its value is in the same project? In this specific project, and this chart of people, it's only available for this specific project. We do it for every project. And the reason I'm mentioning this project is because this chart was the most different than all the other charts and other projects due to the complexity of the project. So we wanted accuracy. We've had to work on a one centimeter level accuracy in the alleys and in the crowded areas. So we must have used multi-stations to measure the details and to have quality control on the site. At the same time, we needed a huge amount of data. We needed the landlines, everything. So we needed to go through the city using a mobile mapper. While mobile mapper and not drone, because it's a very restricted area for the use of drones, even if it's for the municipality of Jerusalem, you can't fly drones. You need like five or six authorities to sign your paper just for the same specific day. We are specialized in getting those signatures. But on this project, it was literally impossible. So this is why. Easy to capture on drones, it was this slow. But you can see that the value of it would have been really high and also the cost efficiency, as you know in drones. You collect data for very cheap price in a very fast time. So we did create stations using LandRTK. We did use the rover and base method for a couple of stations. And then we went by the total station and just mapped what we needed to map for quality control. And afterwards, we just went with the mobile mapper, not relying on its VRS RTK data acquired, but by the connection between the cloud points themselves and creating and using, actually, the points that we measured with the total station to make that cloud really much more accurate. And afterwards, you see that I haven't mentioned laser scanners in this chart. Because in this kind of project, it's an added product. Like, you use it to just add a specific point or specific stuff. And it's not something that you need, but you use it to just make your life easier, I guess. So this is the size of the project, actually. We're talking about six kilometers radius. I think it's bigger than that. But you can see that we had a lot of alleys. We needed to walk all these streets and the alleys between them, which made this project much more complex. I should have put another map to show the height differences because I know this street is 100 meters higher than this point. And yeah, yeah, yeah, I see that surprised face. But we had a really high ups and lows there. And it was very difficult. I'm going to show you an example of the use of the total station data overlaid with the point cloud in multiple places to just show different cases of the geodeculation. Using it, you see how crowded the streets are from both sides and how many cars there are. So this is an example where mobile mapping just failed us in this street, in a way. So we had to go by total stations and laser scanners to just add the different data that we needed that was missing. On another case, another street, we can see actually a different kind of perspective by seeing, when it's an empty street, how the data really helped us to just cut costs and do it much faster and much smoother. And this is a really good example where the mobile mapper have really just cut us a week or two of just hard measurements. This third example I'm going to use to just mention and show how the data that was extracted could have only been by mobile mapper in this case. Because if I used drones in this and we had the trees, we would have not seen the wall under the tree. And this is a crucial part for quality control on our overall project. So if to mention, there's also the problem of using photogrammetry for cable lines. As you can see, all these cable lines would have not been seen in drone photogrammetry. And it would have been really, really, really hard to measure them using total stations. We've had projects where we needed to just measure, because of the heat, how much the cables hide differ during different periods between summer and winter. And this made our life much easier. Because sometimes you do need that one centimeter accuracy, and sometimes it differentiates, depends on the need in the same specific project. Now, why did we need all this data so accurate? Well, first of all, it's a very good foundation for the GIS system. When we're talking about smart cities, we can't not mention digital twins. You see, a lot of the construction companies we work with are starting to demand much longer. If we are to talk about digital twin, it's like starting speaking about what we use Google Maps for. See, if we have a reliable source of real time data going from the user and back to the user, this is one of the pivotal foundations of the digital twin. So let's see what is the use of the GIS mainly now. This is actually surveyed by a surveying company. Also, it's to mention that what we use in GIS system mainly is Orto Mosaic, which is Orto Photo. We go search for street names, for buildings, and very few utilities. We're talking about the IEC and stuff like that. So what we need is to shift from this perspective to more autonomous live data for smart cities. And this is what we're actually starting to do with the electricity company and other companies inside the city of Jerusalem. We can use the data we already have for much more. See, if we know in real time that there was a hazard in an electric line, we can just send someone to fix it. We're not thinking about digital shadow, but a digital twin, where in real time, you get data to the center, and the sender sends data to the point of work. And in this specific project, we started for the parking spots. It really started there, because as you saw one of the roads, it was really dense, and there was nowhere to actually either park or the people can move. And it's a problem many tourists see every year. So it started with actually allocating different kind of parking spots. And as you know, in malls, we have that system where you can see how many parking spots are left open or unavailable. And sometimes it's also common in cities. But what database does it report back to? Can you see it in your ways or in your Google Maps? And it moves from there to, I mean, I know it's a simple idea, but if you have smart trash bins and we took this from a project that was conducted in Dubai, that if the garbage bin is filled or has some weight inside of it, in the GIS system, it would have been alerted, and there would have been someone sent to just keep the check and everything, really everything. Traffic data, it's already been used, but we're talking about a higher level of it because you can use stationary points inside the project for sensors to make stuff actually much more reportable. We've seen that it's been used actually in some cities, but not in the old city of Jerusalem. So the progress of the project, we're talking about, I've mentioned about the parking spots and the accessibility and that it is being a foundation for the future. We've been through a lot in the past year and a half. All the data that was collected is going to be going to the planners to actually, it is being used not just for GIS, and for construction. We have a big amount of data that is being used for multiple reasons. So we're talking about cost effective for the clients themselves also as well. And this is actually what we're actually trying to achieve in this project. So for summary, I'm just gonna say, for big scale projects, the reliability that the client had in us was what made this project different. If we can be more professional on every level and not just count on the technology to do the job for us, but to actually add the value to the technology or take the added value from the technology and extract what we can take to the future, this is what we're gonna have. So I am going to say that anticipation was really one of the key factors of this project because we had to anticipate the crowds, all the problems that I mentioned in one of the first slides and having an open head to this project and just being open to having different solutions to different problems and even seeing them really made this play special. Thank you very much everyone.