Citywide Reality Capture for Infrastructure Design Using InfraWorks and AutoCAD Civil 3D

STEPHEN BROCKWELL: Can people hear me OK? I had a flu a couple of weeks back and my voice hasn't fully recovered. With the mic it's OK?

AUDIENCE: [INAUDIBLE]

STEPHEN BROCKWELL: OK. All right.

AUDIENCE: [INAUDIBLE]

STEPHEN BROCKWELL: Well for a while-- I should have come and done it about two weeks ago because I had a total Leonard Cohen kind of base level voice. I could have been a radio DJ for about two weeks of my life when I had this thing in the start. But, yeah, now it's sort of normalizing.

AUDIENCE: [INAUDIBLE]

STEPHEN BROCKWELL: Probably should have that tomorrow.

Ready to go?

CREW: Yeah, you're good.

STEPHEN BROCKWELL: OK. Perfect, thanks. All right so this is all about Citywide Reality Capture using a particular approach that's used by a number of companies. It's sort of using a vehicle to drive it with spherical cameras and capture both photo realistic imagery plus LiDAR at that scale. And the integration issues around using it within Autodesk products, and also thinking about how such a workflow and how such a kind of data collection methodology fits into the bigger picture of collecting data at the full city scale, but also for specific projects.

So we're going to talk about the issues, in general, in the current collection trends, most of which many of you will know. And then we're going to talk about, specifically, a tool we've used with Pete who now works for a company called CycloMedia. They're a Dutch company that has a US operation. They have a kind of borderline revolutionary approach to it that has some fantastic tools and APIs that you can use.

I'd like to thank Shaun Kinahan who is our developer here. He's done a lot of the work on the product that we have that links the two together. And then we'll just conclude with some final thoughts on priorities and challenges that we faced putting this in place.

So that's essentially the class summary. So hopefully you'll come away understanding what, specifically, this kind of method of data collection and capture can do to reduce costs and increase quality of the data you're collecting. It can show you how the photorealistic aspect of the data plus the LiDAR together, can be really great for measuring for new projects and for engineering.

We'll learn, specifically, how to use it in AutoCAD Civil 3D. Essentially our plug-in works in all versions of AutoCAD. We have a prototype that's working in Revit. And we were unsuccessful in getting our thing to work in InfraWorks. So we'll talk a little bit about that. So that last one, which is what we sort of originally pitched for this class, we did not fulfill that and I'll explain a little bit why toward the end.

So, bios. Stephen Brockwell, that's me. I worked for a company called-- well, actually, I started-- there's some ArcGIS Esri folks in the room here-- I started working at Stats Canada in '87 doing automated districting on VAX VMS, if you can believe it, with ArcInfo 3. And I was like I'm-- just incredibly wonderful challenging project. So welcome to the Esri folks in the room who really defined this space, you have to say, the geospatial space, really.

Anyway, and then we had a company in Ottawa that was building their own, sort of, 100% Oracle-based GIS system called Vision and I joined that. That was acquired by Autodesk. I was a director of product management there for a number of years with Map Civil 3D. And then moved into a sales role.

And then started to say, hey, I would like to do this on my own, and started a small company called Brockwell IT. Where we do consulting with utilities, telecoms, municipalities, just in broad terms of how to strategically plan data collection, design engineering efforts, and also specific implementations around this kind of technology.

Pete. Please introduce yourself.

PETER SOUTHWOOD: I didn't actually do the bio, because I was silly and I didn't get in to Stephen in time. So whatever Stephen's written up there, I believe it to be the truth, and I haven't seen it so I can't really comment on it. Pete Southwood. The accent, by the way, is from England. So please don't wonder what part of Australia I'm from, because I'm English. So we'll get that out of the way to begin with.

Formerly with a company called Autodesk, 20 years, predominately is the early stage of my career there as the GIS evangelist for Autodesk. For the last 16, 17 months, I've been working for a company called CycloMedia based in Berkeley. I'll let the solution and how it interacts with the Autodesk based solutions speak for itself a little later on.

But I've had an interesting juxtaposition over the last, almost two years, where I've predominately been dealing with Autodesk customers. But actually in the last two years, it's been almost solely Esri customers. So it's nice to actually be in both camps, both huge amount of value on both sides. I'm not sure what else you put in there.

STEPHEN BROCKWELL: No, that's fine. That's perfect.

PETER SOUTHWOOD: So I think that's fine. I'm going to sit down.

STEPHEN BROCKWELL: Essentially, like me, Pete has been doing GIS things and founding companies like Convergent, being a founding partner in that, for 30 years or so. So he's been around. He was in Ask Pete. He had his own kind of blog and he was someone that people would go to inside the customer base to get solutions to problems with Autodesk GIS world for a long time. He's a great resource that's been a great colleague for many years. I'm glad to be doing this with you.

PETER SOUTHWOOD: Thank you. Me too.

STEPHEN BROCKWELL: OK. So typical options for collecting this kind of stuff-- most of us know them, I mean all of the technology out there to do it is ubiquitous-- but the key thing is asset management it's incredibly useful. Sending crews to the field back and forth with web apps and phones is fine. It can be very expensive. It can be somewhat unpredictable. Data quality can be variable. And even data collection techniques, like some people will get GPS coordinates close, some have different level of skill sets in collecting that data. So there's some issues there.

But to asset management, which is becoming more and more critical-- I'll give you a quick case in point, which is what drove this customer project that this is based on. City of Alexandria, Louisiana, has a fire rating which is at risk of changing because their collection data on hydrants is inadequate and out of date. So they don't know the full inventory of their hydrants. They don't know the fire flow at each hydrant. And they don't know the quality and the age and all of the conditions of the piping that is feeding all those hydrants.

So, as a result of that, they're at risk of dropping one or two fire insurance ratings, which could mean liability problems and also just vastly increased insurance payments, and especially serious problems if there were an incident. So that's what's driven Alexandria to embark on a really massive data collection effort. And that, fundamentally, is an asset management problem at the full city scale. So that's the kind of thing we're talking about here.

But also planning, assessment, Pete will go into some of the details here. Emergency management, as well, and public safety. Are right of ways being obeyed. Are there encumbrances to pedestrians, to traffic, these kinds of things. This is a perfect way to do a objective survey where you can intervene and look at the state of affairs at a certain point in time from a desktop or mobile environment. But not have to be in the field at that location to get the very close picture of the reality of the site you're working on.

Transportation and road condition assessment. That's another major opportunity that we're working on together. CycloMedia has actually already closed that opportunity in the City of New York for-- one of the applications there is pavement marking data quality. So the pavement mark-- well not the data quality, the quality of pavement markings. Some of which, as you'll see here, for DC area, too. You can see in temporal view the difference in quality year over year.

So the data that is available now, there's a workflow to collecting it, to putting it together, to stitching it, and then to making it available. So that tends to be a sort of cumbersome and time consuming process, especially at this full city scale. It's not bad at a project level, like let's say you're doing a substation, a water plant, or something. Some single specific project, it tends to be perfectly fine. But at the full city scale to get a decent consistent data quality across the whole thing can be an extremely expensive and time consuming operation.

And I want to emphasize the time consuming part, because a lot of municipalities they just don't have resources to get into the field. So that at a certain point in time, like within a window of a week or a month or something like that, they can get the whole city inventoried from a high quality LiDAR point of view. That's just not something they have the resources to do. They wouldn't have the people they could send into the field to get that done in a timely fashion.

The imagery processing can be time consuming and cumbersome. And you need, often, very expert resources to be able to do that. And often, those are not available or you hire an engineering contractor to do that for you.

So, at the end of the day, you've got a perfectly fine solution using this technique for small areas or pockets that you're assembling. But not necessarily one that is at the full scale.

The other aspect of this is, of course, the limits of the point cloud data that you're dealing with. And this is going to turn out to be one of the challenges that I talk about at the end of it. Because, for just the city of Alexandria, which is about 80,000 people, there are 100,000 or more, I think it's 300,000, which is going to shrink because they were changing the tile size. But 100,000 files of ReCap data, if you can imagine, right. So if you had to manually process that ReCap data, you would never finish. So there's a tool we'll talk about later that allows you to do that. But, fundamentally, processing that volume of LiDAR data is something that is really difficult, if not impossible, for a municipal scale organization to undertake.

And, again, the second part here the positioning and data consistency, different people, different crews doing it are going to get different data qualities. How you reconcile those data qualities. How do you ensure that the measurements that you're getting off of the resulting data are going to be accurate and reflect ground truth in a consistent way across the municipality.

And then, again, the stitching. One of the nice things about what we've got here, as you see, when you navigate in AutoCAD it's pretty seamless. So you're going from spherical image to spherical image. It's fairly continuous and seamless. And it has incredibly extensive metadata about it, too.

OK, so these are the familiar ways of doing it. Of course, terrestrial data capture, drones, which are actually really useful in concert with this. Because the one thing is, when you drive your collection, you're looking up. Which is incredibly useful.

I'll show a screenshot of how in Civil 3D, you can actually capture the underside of a bridge or an overpass and take measurements of that. So that street level view is incredibly useful. But it's not giving you the roof, it's not getting any assets that are on the roof, any kind of other things that are on aerial level: antennas and that kind of thing.

So it's important that you look at this, not as a single mechanism of doing it, but as a sort of really great baseline mechanism for establishing-- in a very cost effective way, I want to emphasize that-- a complete ground truth for the entire city that is affordable and usable across a wide range of applications. But it's not necessarily complete. That's not to say-- you know, gaps where there's large park land and these kinds of things. It gives you a full picture of the driveable area, not the entire city. So aerial, LiDAR, and other things, it's part of the whole picture.

Now there are other solutions for this. And we have done some work with them. So Google Street View has really cool API. It's extremely easy to implement and put into AutoCAD or anything. If you have any ObjectARX type developers or autoless developers, it's actually really easy to do. But it's limited in functionality.

The metadata that they have inside Google Street View is kind of limited to yes, there's data there and this is where it is. It's not data quality metrics that are in there. It's not kind of pickable, measurable imagery that you can use in that way. But it does give you sort of a site level view of what's going on.

It also isn't as inexpensive as you might think. If you're going to use it on a large scale for large scale projects you can end up spending money for data that you don't control the collection of. You can't control when it was collected. And you don't necessarily know the vintage and whether certain data was collected at certain points in time. But it is still a viable approach.

So CycloMedia has a really unique way to do it. I'm not going to get into all the details, but the panoramas they have are incredibly detailed. They're about the highest density of any vendor in the industry. And the way they represent the application to partners and developers-- of course, Esri is one of them. They have some really great integrations on that platform, as well as, now, AutoCAD Map. So the kinds of things you can do with this data are really pretty impressive.

So I'll let Pete take over from here. And then I'll come back to talk about some of the implementation details.

PETER SOUTHWOOD: Thanks Stephen. This isn't meant as a commercial for CycloMedia, but I think it's just important to highlight what we do as an organization. Berkeley based, fairly young in the United States, but what we do is capture professional-grade street level imagery.

And I want to just share a couple of examples, I guess from Esri. You might recognize the screen there. We got ArcGIS-- I don't recognize that screen. Is ArcGIS-- Online, thank you. Who said online? Good man. ArcGIS online.

But more importantly, just emphasizing the client itself. In this particular case, customer is Washington, DC, DDOT. At about four years ago, they decided they wanted to capture the whole of DC to manage their Department of Transportation based assets for a complete asset capture for the city.

Now in this particular case, they were so enthralled with the imagery, they've continued capturing every year for the last four years. And this year alone, they actually requested that we capture information about the street level imagery. Sorry, street level signage. That might be better. So using our imagery we actually extracted 350,000 street signs that matched with the MUTCD database, the National Signage Database. DDOT actually thought they had over a million signs.

So now we're getting into the situation where we have this real world situation, a real world source of truth, where you've got an organization that actually thought and budgeting around certain assets. But reality, that I consider really, also took on board parking meters and parking bays. So just in the way of Washington, DC, street sign imagery, but taking it further through to-- I should've practiced this. Is it a shift key or an enter key?

STEPHEN BROCKWELL: Hit enter.

PETER SOUTHWOOD: Enter. That's what I thought I did.

[INAUDIBLE]

There we go. Down arrow. Even better. But in one of Stephen's previous slides, he talked to organizations wishing to recover costs.

Now I'm going to be very, sort of sensitive talking about this. But a number of our customers actually use the imagery to reassess properties around the United States. Anyone here lives in Maricopa County? I know you two, both [INAUDIBLE]. Well, your taxes, unfortunately, are assessed based upon our street level imagery. So I'll buy you a drink later. But I'm not sure I can make up for whole amount of taxes.

But this is an interesting screenshot of an important integration. This is actually Esri's tax assessor. A solution that comes out of Esri, Canada. And our little contribution is this tiny little bit in the bottom right corner of the screen. The rest of it are coming from pictometry, other vendors of Oblique and Ortho Photography. But putting that source of truth together, this is where Brockwell IT does that extremely well. Pulling the source of truth together. That people like auditors, tax assessors, can actually go through the process of recovering tax dollars.

We do other special things, but I just wanted to highlight that for you. Not so special, unfortunately, is when we get into situations like this. Understanding that real world source of truth. Couple of years ago, I think it was two years ago, the regional municipality of Wood Buffalo in Alberta. Got to get that right. The township of Fort McMurray had a pretty awful-- Was it classified as a natural disaster?

AUDIENCE: It was, absolutely. It's one of the worst national disasters [INAUDIBLE] Alberta history.

PETER SOUTHWOOD: A number of homes were destroyed because a wildfire went through. By the way, I live just south of a place called Napa in Sonoma County. We had a, just a little fire a month or so back. Similar sort of carnage that happened. But we were asked to actually drive this by the township. Because they wanted to have a full understanding of what was actually physically left. Show us. We need to understand this. Because, guess what? All sorts of, respectfully, crazies come out of the woodwork. Well, you know, I lost my Ferrari because it was burnt and--

You know the Canadian equivalent of FEMA having to deal with all sorts of different requests to help and money. But truly, what's happened there-- And also taking the situation because there's a lot of contaminants here. They're having to remove all sorts of information-- Remove all sorts of terrible stuff that's there, contaminants from properties and all sorts of things.

So as within that of source of truth, understanding exactly what's going on within that environment. With some minor irony we, as a company, captured a place called Monroe County one week before an event called Hurricane Irma went screaming through. And if you know Monroe County-- Anyone here from Florida? Monroe County is from Key Largo down to Key West. So we were actually engaged by the county to actually-- usual things with a look in assessment and looking all sorts of different departments, public works, to understand what assets they have within the county. And about a week, week and a half later Irma went screaming through. So what we have now is a complete record of pre-Irma. And they want us to go back in and look at post-Irma because, again-- I shouldn't say that-- but the crazies are coming out--

AUDIENCE: [INAUDIBLE] it is a liability and management issue for municipalities is really serious because you're paying more than you need to pay.

PETER SOUTHWOOD: Absolutely.

AUDIENCE: It's a substantial thing.

PETER SOUTHWOOD: Absolutely. You're miked by the way. Because you're coming up with some valid observations. But please, mic.

So if I may, I'm just going to-- like I said, it's not a commercial-- but I'd like to just spend 10 minutes helping you understand how we actually go through that process of capturing street level imagery. Stephen, quite rightly, mentioned Google Street View. Fantastic solution. Please be careful around with licensing because you can use it, but it can be not as cost effective as you thought. But there are other ways, again, Stephen alluded to them with sort of hero, handheld based cameras through to drones, and such alike. We use things slightly differently. We use almost exclusively Ford Escapes. We have the spoked five camera system that sits on top of the vehicle. GPS. IMUs. So we understand if the vehicle's tipping over on its side. We run Dead Reckoning. We actually drill in to the axle of the vehicle. So if we can't get proper GPS coverage, for example, we just captured the five Boroughs of New York. Urban canyons can cause problems with GPS coverage. So we actually drill into the axle of the vehicle and can run on Dead Reckoning. So speed, distance, and things like this. So getting that sort of calibration of the imagery straight off the bat.

The driver sits in a vehicle. He follows, or she follows, Pac-Man. It's following a screen for the recording. Obviously me holding up my hand pretending to be a Pac-Man. But follows the route on the screen and just captures the imagery that the client wants. So the camera on the top-- we capture it, by the way, every 15 feet, approximately five meters. And you'll see that imagery in play in the integration with the AutoCAD based solutions, momentarily.

But imagine as a recording location, I mentioned the five cameras on top of the vehicle, each of those, as they pass over that one recording location takes top, left, right-- top, left, right, front, and back images. We take those images, and we don't stitch them, but we've got algorithms to actually pull the images together. So when you're looking at other solutions, just be aware. Anyone ever seen Google Street View with crooked people, crooked buildings, parallax? None of that occurs in our particular environment.

So we take those captured images, we stitch them-- I shouldn't use the word stitch because we don't actually physically stitch. But take the images together, put them together, and we end up with our four 360 degree, 180 degree, 106 megapixel, sub four inch positional accuracy, sub inch measurement accuracy to 19 millimeters.

So now, imagine this solution in your Autodesk based environment. We've happily been in an Esri environment benefiting from that for a while. Then have to deliver that sort of level of precision, if you wish, to that Autodesk based desktop solution. I don't like that image, Stephen. We'll have to change it.

STEPHEN BROCKWELL: My apologies.

PETER SOUTHWOOD: That's all right. But a full 360 image. The fact that I can be in a car, hold my left mouse key down, and read the asset tag on the side of a transformer. Being able to validate addresses. Being able to measure ramps for ADA compliance. Anyone here going through the ADA saga within their municipality? Slopes. Percentage average on that slope. Areas. Things like this. Again, being able to take the imagery and being able to gather all that information from the imagery.

At the same time, our camera system can also capture point clouds. There is no, "Hey, the imagery is more accurate than the point clouds." It's either captured with the imagery or not captured with the imagery. It's purely as per request by the client. Stephen's client at Alexandria, city of Alexandria in Louisiana required point clouds because they're able to use that to take in to consideration-- Rick if you're going to ask me a question, you hold your hand up.

RICK: [INAUDIBLE] If you don't mind.

[PETER LAUGHS]

PETER SOUTHWOOD: OK.

RICK: Is it actual LiDAR or is it Fodar?

PETER SOUTHWOOD: Sorry. Repeat that. I'm not sure-- The question--

RICK: Are you capturing that [INAUDIBLE] with a scanner? Or is it Fodar from the [INAUDIBLE]?

PETER SOUTHWOOD: All right, so the question are we capturing actual LiDAR or Fodar? I've not heard that. It sounds like false chicken or something like-- [INAUDIBLE].

STEPHEN BROCKWELL: It's photographed.

PETER SOUTHWOOD: No. It's proper LiDAR.

STEPHEN BROCKWELL: Oh, is it?

PETER SOUTHWOOD: Yeah. We use the Velodyne, high-end Velodyne HD32-- and a whole bunch of other number on the back of it-- LiDAR unit. It's like a very expensive baked bean can that sits on the back of the imagery. Exactly the same positional measurement accuracy. No different. In fact, what we do is we benefit from the LiDAR imagery, because we do a couple of extra things which benefits ReCap Autodesk users and in this particular case, an Esri user using ArcGIS Pro were taking that LiDAR.

We also incorporate additional attribute information and, in particular, the RGB value. And we get the RGB value from every single pixel on the 106 megapixel image. You're looking at a screen shot of the city of Redlands in California. They've just recently completed-- I need to talk to our friends at Esri, because you need the benefit from this data, too. City of Redlands in California wanted to capture their complete city. Including the local city of Redlands airports, their wastewater plants, things like this.

That was Stephen's clients city of Alexandria LiDAR imagery that they took straight into ArcGIS probe because they had the RGB value. Instant colorization. You need to see this on a proper screen, but it almost looks like a photograph. You can see leaves and bits of dirt, some snow on the left side, and slightly to the right. 'Cause I only gave a small subsection of LiDAR, so some of the data is actually missing. And using tools within the Esri platform to actually do line following, asset extraction, capture of information.

So we capture imagery plus LiDAR. Like I said, it wasn't, necessarily, supposed to be a commercial. But more importantly, and maybe in this situation is taking that same LiDAR with that same RGB value, so you get instant gratification-- that sounded wrong, but you where coming from-- where we're taking that LiDAR into an AutoCAD based solution. And seeing, hey, if there's a stop sign there, guess what? It's a stop sign. It's red. It's got the word stop on it. If it's a tree, it's green. It's maybe got sort of multicolored speckled barks. But you know what you're dealing with.

And it's where Brockwell IT bring immense value to this whole workflow, in, well, what can you do with this afterwards. Rick, not necessarily just for you, but if anyone's interested, it is the high end Velodyne unit that's used by the likes of-- Who are the autonomous vehicle companies I should notice? Who are the ones that went in San Francisco that went to--

AUDIENCE: Uber?

PETER SOUTHWOOD: Uber. Went to Phoenix immediately had an accident because somebody t-boned the vehicle. Great. But, again, you got your same positional accuracy as the imagery. No different. But we have that ability to capture LiDAR on behalf of our clients, as well. So I'll leave that there just for a few seconds. [INAUDIBLE] returned, by the way, so these things just flash through extremely quickly. And truly, the unit itself just looks like an oversized baked bean tin for goodness knows how many hundreds of thousands of dollars.

So taking all that lovely imagery-- and thanks for not hopefully too much of a commercial-- but just the fact there are other ways of extracting content from the field that doesn't necessarily need to be a handheld device or a drone. That can complement the whole workflow, don't get me wrong, I'm not asking you not to do that. But then what can you do with this in Autodesk based solutions? So, Stephen, I'm going to pass this over to you.

STEPHEN BROCKWELL: All right. Thank you, Peter. Great. We'll go into the integrations we've done with various different AutoCAD products, or Autodesk products. And then we'll talk about just some closing thoughts on experience from this project. What we learned, you know things to change next time, challenges that some of you probably had with ReCap on really large, not individual data sets, it's fine if you have enough memory for a single data set. But processing hundreds or thousands of data sets in an automated fashion is not the easiest thing to do.

So Google Street View, as I said, it's pretty easy to integrate. It's got a very nicely documented JavaScript API. I am providing the link for it there. So I suggest you have a look. It's a really easy to use JavaScript API. With AutoCAD you can create a form, pop that thing, you know the JavaScript viewer into a form, and then just use it right there. So this is actually just inside AutoCAD Map. And it's fully navigable, too. But, again, it doesn't have the same quality of measurement tools or metadata that allows you to do engineering right off of that image. But it's got some of the same features.

So for knowing sort of a current state of affairs at a site. That's very useful. So some of our telecom customers use this to sort of see, OK, what's at a particular site. You know, their data is in different states of repair. So it's not worth it to them. They don't do the same degree of physical engineering that they need to capture the level of detail and imagery that someone would in a municipality. So that's something that's really quite easy to do and we can talk to you about how that's done.

Now, within AutoCAD, we put in place a number of different things. So it's just a dockable panel that has the Cyclorama on it. You can see there, there's a measurement being done right on the surface of the pavement. It's integrated inside the Autodesk environment and there's a bunch of tools on it. So the toolbar's not showing there. There's the toolbar. So you've got the ability to sort of follow. There's a tool that's not showing up in here. Is this one on that video one. No, I don't think it is.

But anyway, so you can navigate. You can show the view cone and shrink it and stretch it inside AutoCAD. You can rotate it in AutoCAD. When you rotate it in there it stays synchronized. And then you can go into measurement mode which is where the real power of this comes in for an AutoCAD user.

So here, for example. I love this one. I'm glad Shaun did this because you see you're measuring the underside of a bridge. So let's say you have a concrete condition problem or something like that, and you want to get some estimates of the size of that problem and what you're going to have to do for it. Or even, let's say, you want to take the underside of a surface through a 3D model. You can actually do that from there. So that's a great perspective. And there you see the view cone, it's under the overpass there. And you can see the sort of view port. So you can stretch that and everything like that.

And even though there's multiple cycloramas, so you see here, it goes into-- there's a depth of field to the image, which is actually quite substantial. Those measurements can be made right into the deeper parts of it. So it's actually an incredibly powerful tool for that kind of thing. Oh, in this case here, we're creating a circular arc for a curb, measured right off of the actual imagery and getting both-- And when you're using the 3D side, the image is underpinned by the LiDAR data, if you've collected it. So you can actually collect the 3D elevations of those points as well. So you're not just collecting 2D vector data, you're actually collecting 3D elements.

So this is an example of using it in Civil 3D. So it gives you a better idea of it. This is actually in an area where there's no mapping data that's been collected, it's a shopping mall parking lot. But let's say that we wanted to collect alignments and that kind of thing here, this gives you an idea of the user experience. So you just choose which kind of measurement you want to go in.

And you can collect surfaces. You can actually measure 3D surfaces off of this, or points for blocks and attributes, text and that kind of thing. Or you can do 2D or 3D vector polylines. In this case here, we're just doing a simple straight alignment from one end to the other.

AUDIENCE: [INAUDIBLE]

STEPHEN BROCKWELL: Yeah, exactly. Yeah, yeah. And it actually will create a real Civil 3D alignment right in the drawing from that.

AUDIENCE: [INAUDIBLE] one of those pictures [INAUDIBLE] by views from the camera? [INAUDIBLE]

STEPHEN BROCKWELL: At any point, in any position, they're all unified. So it's full 360 orbit from that position.

AUDIENCE: [INAUDIBLE]

STEPHEN BROCKWELL: Yep, absolutely. He's doing that now. Yeah, yeah. No, no. So in that one photo, you're measuring into the distance, but using the other cycloramas. But you can actually switch cycloramas, move to the next one, to get more precise at the endpoint if you want to do that. And that happens all seamlessly. And it can even be done inside the viewing tool or inside the AutoCAD part, whichever way you want to do it.

PETER SOUTHWOOD: So may I add?

STEPHEN BROCKWELL: Yeah.

PETER SOUTHWOOD: You're hearing a term bandied around called cycloramas. That's just purely the 360, 180 degree image. That's what we call a GeoCyclorama. But you hear exactly right that it's recording locations thats taken every 15 feet. Thank you. 5 meters [INAUDIBLE] roughly. So you can see this is the recording locations of those blue dots. So you can actually pick a different recording location. It becomes particularly useful for clients that have assets, that have considerable distance between them.

As an example, San Jose Water [INAUDIBLE] is banning clients around the San Jose Water. It was very important for them to know the distance between hydrants. Because they're going in doing remedial work, need to understand the materials they needed to go in and put new pipes in, what information, materials they needed to repair the roads with, things like this.

But being able to go between one image and another and just get that, again, sub-inch accuracy measurement and is feeding Civil 3D, as you can see on the right of the screen. Thank you, Stephen.

STEPHEN BROCKWELL: Yeah. Thanks, Pete. So this is actual Civil 3D alignment features. We haven't really expanded beyond alignments, because alignments are so fundamental. But, in principle, that's something we're looking at doing for the future. And you can see how you're collecting data here that is very accurate.

And the other thing about the CycloMedia data that I really like is it has metadata on your measurements, too. So the image itself has a certain level data quality, but every point on it also has a level of data quality. So it will tell you whether the data quality on the point that you're measuring is sufficient to be able to use it. And that's incredibly important from a kind of engineering and design, if you're calculating areas or that kind of thing.

PETER SOUTHWOOD: Forgive me. May I add again?

STEPHEN BROCKWELL: Yeah, please.

PETER SOUTHWOOD: I promise not to be too much of a jack-in-the-box.

STEPHEN BROCKWELL: No, no, this is great. This is the whole idea.

PETER SOUTHWOOD: On the left side of the screen, just above that measuring bar that appeared, you will see a date. Stephen talks about the metadata. It's become actually surprisingly important.

STEPHEN BROCKWELL: There's another example.

PETER SOUTHWOOD: There you go. Metadata is surprisingly important to organizations that want to use this in litigation. There's some weird things that happened to trees in Washington, DC that I didn't know could happen to trees in DC. Somebody's apartment, the sun doesn't come into the windows because, guess what, there's a tree in the way. It's been known the trees disappear over weekends. This truly happens. And tiny little urban gardens appear where the tree used to be. So now you've got neighbors complaining there was an oak tree there, it's now gone. The owner of the property complaining, hey, there was never an oak tree there. Because everything's time and date stamped. Litigation. Hey. There was a tree there. You're lying. You should have got a permit. And such alike. So it's actually some strange cases where we're using that for litigation purposes. Stop signs going missing because some drunk has run them over. Question.

AUDIENCE: How long does it take to get this set up [INAUDIBLE] I mean, basically compared to [INAUDIBLE].

PETER SOUTHWOOD: So the question being, how long does it take to set this up. I'm repeating the question for the audio people. Good question. One vehicle, on average, can capture 40 linear miles per day. And it captures everything. And we have to abide by speed rules. We don't have drivers just going nuts, terrorizing down the road. I shouldn't have said that word--

STEPHEN BROCKWELL: No, but I mean, it's so important because if you think about, again, that idea of having consistent data, right. So I mean, climate conditions, temperature, all of these things. You know, that you're gathering the data at a consistent time has a huge impact on the data quality that results from that. So that's really important. Yeah.

AUDIENCE: And not to hit around too much, but I mean, the same vehicle following you for five miles or directly in front of you for five miles, do you find a need to go back out and pick up that data again?

PETER SOUTHWOOD: So the question being, and I'll paraphrase, you know strange things happen with the vehicle driving along and all sorts of things happen. Yes. Not a commercial, but we quality assure. We make sure that the best possible product gets in front of the client. But we do have crazies. I got to-- I'm sorry.

[LAUGHTER]

I'm pointing you now. That gentleman who sat in the front who is from Cleveland, but Ohio, our drivers in Columbus had to be deputized. And I got a great photograph of a member of the public who is drawing a gun on our driver. So we had to go back and re-drive that area, because the driver had to move out quickly.

But people throwing themselves on vehicles. Strange things in alleyways in DC, which is a mixed audience. I really don't want to go into now. But, yeah, we get some strange-o stuff-o that we have to go back and re-record.

STEPHEN BROCKWELL: Just to reiterate what Pete had mentioned about dates, too. This video clip has been played. But in this image here, you can just very briefly see 'cause it's too bright, but you see the date at the top of that slider. So you can slide that down, that's what we're doing.

And in this case, this is really useful because this is one of the problems, it's pavement markings, right. There were no pavement markings here the year before and they put them in. So they can say, yeah, that problem has been addressed. So that ability to do temporal examination of your data. And then measure differences between last year and this year for degradation and other things. It's a lot of different applications of that temporal aspect.

So we've also got a prototype of it in Revit. And we're working on how does it all fit in, how does it work. But the idea would be, for example, if you've got an existing building, what are the surface areas. What are the measurements, if you're using it as a starting point.

Or let's say you've got some baseline construction foundation, that kind of thing, you want to measure off of that. This is the kind of tool that would allow you to do that. But this is a bit of a work in progress, to be honest. But the idea is the same.

And I'll talk a little bit more about the significance of doing it and what some of the issues were that we were facing. But this is absolutely one of our top priorities now that we have all of the AutoCAD kind of things. And, you know, it wouldn't work for specific plant features. But this is something we've been talking about here, like water plants, airports, other facilities that are reasonably accessible.

Even, like in Los Angeles, all the canals and waterways, drainage, doesn't have to necessarily be a public roadway. Anywhere where you can use it to get a decent legitimate scan is something that is possible to do. So there's a lot of possibilities here from that perspective.

AUDIENCE: [INAUDIBLE]

STEPHEN BROCKWELL: Well you know, the data's real-- this data is not in Revit, per se. It's in a container that's using the cloud service to visualize it, right? So that's true in AutoCAD, too. So, in fact actually, one of the beautiful things that we've done about it in AutoCAD, which Shaun's going to-- he's just worked on the ArcGIS white paper that we're going to be showing tomorrow about some other integration issues with ArcGIS online and how to do that. But Shaun will be writing up a bit of a white paper, some of the technical issues in doing this.

But the nice thing about AutoCAD, we leave nothing around. So that widget that moves around and, you know, the WMS feature service where you're showing all the recording locations, we use transitory graphics to do that. So we're not leaving any features behind in your drawings or anything like that. We leave them completely clean at the end of it. And we're going to try to do the same thing in Revit. The only thing you're left with, as an artifact, is a 3D surface of that wall and a proper Revit object from it. Yeah.

AUDIENCE: [INAUDIBLE]

STEPHEN BROCKWELL: Here we're reading measurement content. And we're going to be creating, in the future, this is a prototype, but an actual wall, or depending upon the level of the architecture that you're dealing with, the discipline and so on. There's a lot of user interface issues to that because the Revit model itself for data creation is so much more complex, than the one for just vanilla AutoCAD, really. Obviously.

OK. So concluding remarks. Some of these are really important, I think. Just the, sort of, this project, what we learn from it collectively. 3D data collection. I mean, the thing is this customer of ours, we've been working with them for at least, I think, eight years now. 2D cost estimates for data conversion, the old fashioned way, they literally come in in the half a million, million dollar range for one discipline, like gas, water for the whole city. To vectorize data from all sorts of paper records and all of this stuff.

And what's the real benefit of that after having done it? Can they engineer off that? Well, yes, but there's still uncertainty in data quality issues in that. 3D data capture is so cost effective. Like a 10:1 difference and I'm not joking about that, cost wise to collect data at the entire city scale. Of course, limitations, it's visible, it's street level, and that kind of thing, sure. But 99% of infrastructure in a municipality is at street level anyway.

So it is a process, not an event. And what I mean by that is a lot of data collection that takes place right now is for a project. The LiDAR files that get captured, the imagery that gets captured if you're using something like ReCap Photo, which is the sort of photogrammetric way of getting LiDAR, or you know, point clouds anyway. That data tends to be sort of used, and then is it discarded? Is it archived? How is it accessed in the future? Is the temporal thing there? What's the metadata?

So, process-wise, this is a very helpful way to look at it because it changes it from just an event-based, sort of project-level thing, to a sort of system-wide, kind of change in philosophy about how you use 3D reality capture data at a scale of the city. And it is possible to do, and it's possible to do very cost effectively. For the price of some drones, you can get this data collected in a small city scale.