>> We are trying a new concept here,
starting with a film.
Thanks for inviting us here to the Epic Games,
to this Epic Build.
It is very inspiring to be here in front of this crowd.
My name is Eric Jeansson, and I am a Geo Data Strategist,
the city of Gothenburg in Sweden.
And this is Harald Karlsson, engineer.
And we are going to talk about,
tell the story about our digital twin, Virtual Gothenburg.
That, you have already seen.
How do we face the challenge of building
a smart and sustainable city,
with new ways of living, new ways of meeting,
new ways of transportation, and new energy solutions?
How do we face the challenges of climate change,
segregation, the new transport needs,
and the amount raising,
raising data amount in the society?
One way is to build a digital twin.
We have seen an example here earlier.
We called it Virtual Gothenburg, and it will be finished in 2021,
when we have our 400 years anniversary of Gothenburg.
You are welcome to visit us then.
A digital twin is not just a visual copy of reality,
it is also the information which is connected to it.
This is very important.
And in Gothenburg, we see, as a smart city,
we share data with each other,
more processes in the city share data.
And in central, this circle, we have Virtual Gothenburg,
which will act as a platform for that kind of data.
We can visualize, analyze, and demonstrate.
Okay, you can divide, you say, the data in the digital twin,
and then what you can use this digital twin for.
You can first talk about the present data,
which could be used to understand the city,
how it works.
And then we have real-time data you can use to control the city,
like the traffic and flow of people in town,
pollutions and so on.
And for the third, you have simulated data,
or scenario data, which you can use to predict the future.
We have large investments,
to say about 10 million Euro in West Sweden
concerning this kind of digital twin technology.
And one project that is led by Chalmers Technical University,
it is about building a platform
based on Unreal Engine for digital twins.
And Virtual Gothenburg, our digital twin,
will serve as base for that kind of research.
But now to the tricky question, Harald,
how do we make this happen?
>> Yes, that is the tricky question indeed.
So, my name is Harald Karlsson.
I work on this Virtual Gothenburg project
as bringing it into Unreal, and how that pipeline will look.
So, the basic concept of our pipeline
is we start with all this data, right?
There is data scattered all over the city.
So, some people have the roads,
but someone else has the traffic lights,
and some data does not even exist that we need.
For example, we did not have database
covering rooftop materials for all the buildings,
and that is kind of essential to building
visually pleasing model of the city.
So, we have to generate that ourselves
by looking at photographic images of the city,
and building the AI that looked at all these rooftops
and calculating what kind of materials they can use,
and stuff like that.
So, you get all these kinds of different data
held by different people,
and the next step from collecting that data
is to process it into a database that we can control,
and actually look at all the data
and have it in one place,
we can actually use it for something useful, right?
That data is then pushed into ESRI's CityEngine
that was mentioned before to generate procedural models.
So, if you have the attributes of the number of floors,
how the windows look, when the building was built
and all the kinds of interesting data,
you can put that into a 2D space and generate the building.
Very simple, and very interesting.
But there is a lot of buildings in the city,
so this requires a way of looking at them
at the same time, right?
And that is where Unreal comes into the picture.
So, Unreal system will bring all these assets
with LOD levels, collision boxes,
all the good stuff,
and put it together so you can actually look
at the virtual version of the city in real-time.
Then people are able to use this digital twin to
train autonomous vehicles,
or may flood it with a bunch of water,
or any kind of innovation,
science thing you can come up with.
They can use a virtual copy of the city.
So, to do all this, we use World Composition.
It is an Unreal feature that basically splits up the map
into a grid to get these tiles.
And this is one of those tiles. It is one kilometer across,
and I want to focus on this colorful,
happy texture over here.
We called it semantic segmentation tile
or something cool like that.
If you have a cool name for it, you can poke me later.
This texture can contain thousands of data points,
because we can segment the colors,
so dark green can be where to spawn mushrooms,
and light green can be where to spawn blueberries.
But the real bottleneck is to actually have a database
that contains mushroom
locations for Gothenburg or something like that.
So, we need a bunch of data that we can put it into this texture
and drive the environment.
And this texture, or sorry,
this tile is one kilometer across,
and that is usually about the size of the projects
we usually work on.
And we are making 700 of these tiles to make up this grid.
So it is a huge undertaking in scale,
but also in level of detail
we are hoping to achieve on this project.
So, to finish this off, hopefully we have a lot of
Unreal interest in people here.
I just want to highlight this feature called Call in Editor.
Since you are working with all this data,
it kind of puts a lot of pressure on our workflow.
So, we can't really work in editor in a normal fashion.
We can't click things and move things around,
because it is too much.
So, Call in Editor allows you to run Blueprints inside editor
when even starting the game. So, you get these buttons.
So, if we want to import thousands of buildings
and place them in the world,
we can just press a button and it does it for us.
Very useful if you work with large data sets.
And the funny thing is you can make a button
that presses these buttons for you.
And then you can make a button that presses those buttons,
and it is super cool.
And then you can end up with one big button in the end,
and that is, everybody who has worked with data
and stuff like this knows that it won't really work,
but it is at least a vision, right,
to have one press of a button,
and then it generates all the data,
puts it together, names it, catalogs it,
and updates it overnight.
And we want to finish by showing you
a quick look at our progress so far,
and thank you for listening to us,
and I hope you enjoyed it.
[APPLAUSE]