 I'm Mr. Prashant Dalaghi from Prashant Advanced Survey LLP. I'm the owner of the company. I had presented it last year in Intrigia as well. So the agenda for today's speech will be about our company, Prashant Advanced Survey LLP, about mobile LiDAR technology, data captured by Leica Pegasus to mobile LiDAR system, LiDAR data processing, methodologies, softwares used for generating the outputs, use of LiDAR technology for highways and railway projects, case study of the LiDAR survey for the Vishakapatnam Airport. Key factors affecting the accuracy of mobile mapping data sets, GNSSs, GPS base stations, or the ground control points. So we start with our introduction of our company. I would like to rush on this because you can always find all the information on the website. But even then, it's a 30 years old company founded by my father, Mr. Sivanandalaghi. So it's a family business. We use all the advanced technologies. This is our management team. Myself Prashantalaghi, my father Sivanandalaghi is a co-founder and chief technical officer. D.N. Jadav is my father's friend, and my wife Deepalaghi. About me, I'm a PhD research scholar. I've done my civil engineering in 1999. After 13 years, I did my ME civil, stood first in college and second in University of Pune, masters of engineering, certified by the subsurface utility engineering, having 25 years experience in the advanced engineering and mapping, speaker in 26 international conferences worldwide on radar technology. Of course, we have successfully completed more than 30,000 kilometers of highway surveys. I told you the statistics have changed now. As present, these are the values. 3,000 kilometers of railways and two airports in India. And one of the international projects done by us was in Saudi Arabia for 700 kilometers. That was for highway 65. That was recently completed this year. Yeah, my father, he's a founder, I told you. He's having 49 years of experience. He's aged 70, still comes into office, sits in the office. And we are the first in India to have the Leica Pegasus 1 mobile mapping system in the year 2015. In 2016, we upgraded from Pegasus 1 to Pegasus 2. And in 2017, we bought one more Pegasus 2. So you can say that we are the proud owners of two Leica Pegasus 2 systems. And last year, I've cleared all my debts. So we are free of all the loans. We also have drones, as I told you. We have survey grade drones with us. So where our mobile mapping cannot go is not accessible area. So we do it by drones. These are all the set of instruments which we have, including all the DGPS, Pegasus 2, drones, the softwares. These are the list of accessories and the processing computing power. An office owned office in Pune, based in Pune, we are based in Pune, India. And these are the services provided by us. So we do a lot of mobile mapping for highways in India. And these are the list of events and conferences where I was a speaker. It starts from Hong Kong, China in 2015. That was in Hexagon Live 2015. So you can see, again, in US, Hexagon Live in 2016. Literally, I'd been to all the US Hexagon Live programs as a speaker. And then it was in, again, you know, Las Vegas, Hyderabad, then Amsterdam. It's a geospatial world forum. Then again, Stuttgart, Germany, integer TV. Then again, a lot of conferences. And last but not least, it was Hexagon Live last year in 2022 as well. And here I am. So now, with this introduction, I start with my session about mobile data technology. So mobile data is an advanced mapping solution used to collect survey-grade 3D-point-clouds data quickly and accurately. Incorporates the most advanced leader sensors, cameras, GNSS, GPS receivers, and the IMU. IMU stands for the Inertial Measurement Unit. Mobile mapping is the process of collecting geospatial and pavement-distressed data from a mobile vehicle, typically fitted with the mobile data system. Output after processing includes georeferenced 3D-point-cloud data, digital 3D maps in Atokat, DWG, RGS-shaped files, pavement-distressed images, panoramic views, and videos. So the data captured by the Pegasus 2 mobile data system, what does it compromise off? Like a Pegasus 2 mobile data, mobile data can capture 3D-scan point-cloud data in 360 degrees. That's using Z plus F9012 scanner. It's a profiler. It scans about 1 million points per second. The high resolution photographs in all directions and the pavement as well. Trajectory file or the positioning information or the GNSS information. So these are the three basic information which is captured by any mobile mapping device. About data can be captured for about 80 to 100 kilometers per day, depending on the site and the road conditions. So if you're working in the city area, it can be 50 kilometers. If you're working on a highway, it can be 120 kilometers in a day. GPS base station observations ensure the accuracy of the data. The base stations are very essential, at most important. Requires proper logistics planning because you're doing 100 kilometers in one day. So you have to have a good logistics planning. My people start from one city. They end the survey and the halt in other city and, again, keep on moving. So you cannot be stationary at one particular location. Absolute accuracy of the data is about five centimeters, plus minus five centimeters. Precision of Z plus F90 laser profile is less than one millimeter. The data captured by mobile data is processed in the following softwares. We follow the workflow, which is quite robust. The data first goes into the WavePoint Digital Explorer for trajectory preparation at Lycor to be for the point cloud generation and registration. Then the data goes to the Lycor map factory for ArcGIS for feature extraction of point line and polygon features. Then it goes to the 3D reshaper for dem and contours if it is required by the client. And, of course, the ArcGIS at the MSX for drawing and data display. So on the left-hand side, you can see the picture, which is the camera data. And the right-hand side shows the point cloud data, the little data. The typical screenshot of the urban area, the point cloud data, how it looks like. It's a very good and crisp data because it's having a Z plus F90 onto profiler in the Lycor Pegasus too. This is a typical view of the rural area, rural road. And the front camera of the rural road, same rural road, which is quite clear. I told you this is the map factory advanced software. Left-hand side, you see the synchronized camera data. And the right-hand side, you have the point cloud data. You can rotate the point cloud data in any angle view. You can zoom it, zoom out. This is the trajectory corrected or the trajectory file. Everything is green. That means the data is processed. And it's within permissible limits. If you usually don't get the data accurate, then it will be red flags will be there, or it will be in a different color. So here you can see it's centered like green. So that means the data has been processed properly. This is how we prepare a 3D plan out of the data which is captured. We usually have a lot of layers, about 110 layers, for a typical highway project, which contains all point line polygon features. It's quite dense. You can see here. Sorry. Yeah, you can just see here, all the building structures, trees, electric poles, line features, polygon features. Yeah, you can see it more zoomed. And we put it all in different layers so that it becomes very easy for the designer to make a geometric design of it. Now I come to the railway project where we had mounted the Pegasus 2 on the railway, which is the engine at our tower wagon. It's called a tower wagon. Of course, it looks very simple, but it's difficult to mount it on there because the height is too much when you stand below. And the weight of the instrument is 50 kilo, 50. So you have to typically mount it. It requires at least seven to eight people to mount it on that platform. So when the tower wagon is not available, still we can do the survey. It is done by using the motorized trolleys. This is called a typical motorized trolley. It runs on diesel. And it has a speed limit of 25 to 30 kilometers per hour, but still very good, good enough. So this is the point cloud data of the railway tracks. This is a feature extraction once you do the from the railway tracks. The uses of radar technology for highway, railway, and airport projects. Mobile network survey is very fast. Since 50 to 100 kilometers of the highways or railway network can be captured per day based on the traffic and flight conditions, we can capture dense data, typically about 1 million points per second using the laser line 012. The data captured by mobile radar also gives 360 degree panoramic views and the street views. The process is mostly automated, hence less chances of human error and better quality of data is obtained. Airport railway can be captured within few minutes without any major interruption to the air traffic, very effective in creating the 3D digital maps or HDJS maps. I don't know, it's stuck. Is it not moving ahead? Oh, yeah, got it. So case study. Mobile network survey is very fast, as I already told you. Yeah, you can do the case study. Now, case study of the topography survey of resurfacing of runways, taxiways, and development of associated infrastructure for Visakapatnam Airport. So this is the defense airport in India, defense as well as the commercial airport in India. The total length was 5.6 kilometers of runways and taxiways. Time period for data, site data capture was only 30 minutes. Time period of delivery was one week for data processing and delivery. Instrument use was like a Pegasus II. Scanner was Z plus of 9012, which sits inside like a Pegasus II. Digipest base stations used were like a GS-14. Accuracy of data was plus minus 1 centimeter. It's very important because it's all open. There's no canopy at all in the airports. So the deliveries of the projects, soft copy of the topography survey data, 3D maps, autocad drawings, shape files showing the existing roadside features or the runway features, point line and polygon features, soft copy of registered 3-point clouds in HPCO last format, and DTM, TINs, contours generated from the captured database to know the topography, cross sections of the runway at every five meter interval for the width of the runway. We can also generate at one meter interval, but it was too dense, so five meter was sufficient for them. Soft copy of the images captured by six sets of cameras in various directions along the roads with all camera views going about 360 degrees and the free, like a viewing software. Runway condition distressed in a mortgage format. So if there are any cracks or port holes, usually you don't have any port holes, but you have something on the taxiways. So that's very important. Google KML file of the survey runway and the taxiways, just as a complementary service. And you can see Google image, which has been superimposed on the runway. So the red portion is where we had done the survey, actual survey, and the remaining is extracted from the Google Earth. So yeah, you can see some of the screen shots of the point cloud data of the runway, actual runway. So it's a beautiful runway. I mean, it's a defense runway, so they are having a number of crisscrossing runways. So this is the camera data of the typical runway. And yeah, so this is again the camera and the point cloud data. The left side is the camera data and the right side is the point cloud data of the runway. Okay, now I come to the ending of this. Key factors affecting the accuracy mobile mapping data sets. So what we discovered is that there is one key factor which is affecting the accuracy and the performance of the mobile mapping device. So what is it? The major factor affecting the accuracy of the mobile mapping data is the obstruction to the GPS signal on the mobile mapping instrument where the data is captured. That means on the mobile mapping device, there is an inbuilt GPS. So if this mobile mapping device is running below a canopy or below the trees or some lot of obstruction like tall towers like in New York City or Mumbai City, skyscrapers are there, they're obstructing the GPS signals. The more the obstruction, the more you lose the accuracy. So I've made three site scenarios. So this is in site one. You can see the Google Earth image with minimum obstruction to the GPS signals. So you can see this is the road. So this road is there and it's not having more of obstruction. There are no more trees there. So there you get a very good accuracy about one centimeter. So accuracy about one centimeter X, Y and Z coordinates with a good exposure to GPS signal that is minimum obstruction. So you can see the parameters. I think it's readable, nine millimeter, 12 millimeter and 17 millimeter. So it's very good. That's the maximum parameters. Average is four millimeter, three millimeter and eight millimeter. So you can get it. And this shows the red one is the graph of easting, the green one is the northing and the blue one is the height. So these are the accuracy parameters. Okay, so now the second site condition with medium obstruction to the GPS signal, you can see there are a lot of, there are a row of trees besides the highway. So this is the medium obstruction. So in this case, we get an accuracy about 10 to immediately eight to 10 centimeters. All right, so you can see the factors here. Average is eight millimeters, seven millimeters, but when you have the trees, you have the spikes there. All right, so when they have spikes, that is up to 10 centimeters, eight to 10 centimeters. Now this is the third case. It's very difficult, it's full of forest area. So you literally cannot know where the road is, but the road is actually coming like this and it's going like this. So you can have max the GPS point also there. So the road is going from here, it goes here like this and the road is going here. So this is the road with huge canopy. And in this condition, you get a lot of graphs which is up down and relating. And then you have an accuracy about one to two meters. So it's in X, Y and Z coordinates with heavy obstruction to GPS signal. That's a dense forest. So what is the solution here? Generally, you have to have a control points, a lot of control points either by totalization or any other device, fix the control points and then bring the control points to the processing software and then adjust the trajectory file again and then process it. Then it will be within permissible limits. So this is the usual practice which is to be done for canopy areas. And what is this DGPS base stations? You can do it using any GPS, survey grade GPS of course. And it should be dual frequency of course. And it can be done on, it can be established on so many points like existing features or if there's no feature, you can have your stones around or the rectangular stones and you can have the control points. So this ends my presentation.