Streamlining the Design Process CO2e Footprint, Cost, and Time Assessment

MORTEN ANDERSSON: Welcome to this session about streamlined design process for CO2 footprint reduction and the APS APIs. We will go through this. I am Morten Andersson. I'm Digital Director of Artelia Denmark. I have been working with digitalization and optimisation for the last 20 years in Artelia. Together with me today I have Abed Aarabi, who is the Principal Project Manager of this application. He has been doing all the design of it.

We are very happy to doing this presentation. Yes. The learning objectives for today-- we have four, and of them-- the first one is how the application assesses the information about CO2 cost and time to make it being a decision-making tool.

The next objective is diving a little deeper into the principle of the application and how the APS APIs works and how we have to complement it with our local data hub to make it even more effective. And then we will make a sneak peek, I would say, on the possibility for IA and ChatGPT because there are actually some very nice possibilities with this application.

The last thing we will dive into is that if you have a 3D model in ACC, you will always miss some data to be able to do the correct calculation for CO2 or cost. So we need to complement it with some local data hubs, yes.

A little about the Artelia-- we are a engineering consulting company international. In Denmark, we are around a thousand people, which make us in top five in Denmark. We have a nearly 100 years of experience, so think we have something to build on. We are all in Denmark.

Going to worldwide, we are part of Artelia Group. We joined it five years ago. From Denmark, we are 8,500 people worldwide mostly Europe, where we are in France and Denmark, but also quite a bit of offices in Asia, and newly, in Canada now we have around 1,200 employees.

We are a full service engineering company, and we are having three major pillars, buildings, energy and industry, and infrastructure, and we are doing all kind of sustainability consultancies, but we also do hydraulic and nuclear. And so we are full service companies.

We-- I would like just to say a little on our values-- we have five values-- because this is very important for us. And essentially, the expertise is very important for us, but making complex things simple is one of our major issues. And we would like to share our knowledge because we think we need to and we optimize it because we have the possibilities.

We are independent, meaning that 3,000 of our managers, employees owns the company, which make a lot of possibility for us to choose what our drivers are for running our company. Just a few of them-- of course, sustainability, environmental impact, and making innovative solutions is very much on our agenda for these years. And we have been a CSR pioneer for quite some years in Denmark and in France, and it's important for us. But being multidisciplinary, we feel that is an important part of being a good consultant, where we can be full service for our client.

And the last one I will take ahead of the presentation our company is to bring an innovative hub on the global level because it's necessary to attract the top talent from the world to be able to do this kind of application and being able to fool our goal of designing solution for positive life, which we are quite proud of.

ABED AARABI: Well, my name is Abed. I've been with Artelia for around five years. I've been leading multiple digital transformation initiatives. Today I would like to walk you some of it before we enter the core of the application.

A way back, when Forge back then exist-- and today, of course, it's called APS-- we started with integrating with the first API to retrieve the data directly from cloud and present it in a nice color and chart, which is giving us better insight.

But we didn't stop there. We wanted to move a bit more forward, so by integrating the 3D viewer and finding a way to classify what type of parameter we needed, which is a verifying accepted value in the 3D model, and that turned the model to different color to give us a better visual.

After that, we decided to look into IoT and digital twin. So we've been also using as well the apps APIs, where we learned how to retrieve live data from HVAC system directly, and that will give us better insight to evaluate pressure, water flow, and airflow, and all of it, actually.

But to be honest, not all those solution went implemented at the house. Some of them, of course, went false, but it was steps, so in each steps we learn a lot. We learned a lot to start thinking differently. We start thinking on-- we know already a lot today about the geometry and what is inside the 3D viewer, and we learn what we miss at the house to complete the missing data at the 3D viewer.

So we decided to build something called a data hub. Data hub-- the main focus was to provide additional parameter that might be missing in the 3D model. And of course, we learn much more about the integration of APS with Autodesk help, with all the developer. They were step by step with us in this process.

So what I'm trying to say, if we put it all of it together-- so we have the 3D model, we have the data hub, we have the APIs from APS-- we achieve a cohesive data connection. But let me go a little step back, and what's exactly the data hub today at Artelia? A data hub-- it's built on multiple databases, and each database interact with different APIs, so it's very resilient to retrieve data from different data sources.

So for example, everybody, I believe, familiar with EC3 or different APIs or even Excel sheet. So by doing that, we try to create something called centralized data. We were trying to centralize the knowledge of our engineers, of our experience in one place, and doing so by the integrating with APS. And as you can see at the screen, the 3D viewer start visualizing itself, so instead you having a PowerPoint that you can see the color by reflecting on number, now the geometry starts speaking. The walls start saying, I don't accept the value. I'm not compliant.

So the 3D geometry become as a nice chart color. And from here, I would like to handle it to Morten to understand why we are doing that.

MORTEN ANDERSSON: Exactly. Why are we investing so much resource and money in developing these tools? That's because we have to. If we go back to the Earth, the planetary boundaries, this is just to show and share the understanding that in the green circle, that is the boundaries where we can live on our planet in the way we know.

And as you can see, in many areas climate change, biodiversity loss, change of lands, we have exceeded the limits of the boundary of the planet. I believe most of us think that there are something about this that we have to take care of. I also know that some people don't believe in it, but I certainly do believe that we need to be very careful. So that's why we're investing so much money.

But we also are doing something because in Denmark, the regulations are quite strict on how much CO2 there must be embedded in a building. This is an example of a housing building where the regulation just now is 12 kilo CO2 equivalent per square meter per year. And it will go down in the coming years. It will go down to 7 kilo.

We have an example in Denmark called Living Places, which is a building that are now for real, and we have been involved in this project with a very foreseeing client. And we succeeded going down to 3.5 kilo, and that is the best achieved in Denmark so far. We are quite proud of that.

But if we look and believe that the Paris Convention of 1.5 increase in temperature is the limit for our planet, we need to go down to 0.5 kilo per square meter per year. So there's a lot of way to go, and that's why we need to do something. And I believe we have the skills together with Autodesk, together with some of you guys in the audience because we need to collaborate on this.

But this example show there are possibilities, and so that's why we have invested quite some resources and we have put the Abed as principal for developing this data hub and the application where we have been focused on CO2 because we have to. And the clients-- they know we have to, so we need to provide some tools where we, in the early design phase, can help ourselves and each other to make the right decision.

And of course, cost is important for the client and therefore also for us and time in doing the production of the projects. So that's why we have been focusing on these three areas in the beginning, but we can add other items if that should be necessary. So please, Abed, continue with the description of our application we have been working for the last years.

Yeah. Well, thank you, Morten. Of course, CO2 and time and cost-- it's the most important parameter nowadays in the AEC project phase. But putting all of it together, we ended up with building a very beautiful platform that allowing all the stakeholder in early project design phase to have an better insight on each element, to see how much it cost and how much time would take to be built.

And of course, it's visualized by-- as I said in the beginning, with a color schema from green to red, would reflect low to high values. So basically, we could group by any parameters included in the 3D model or it's coming from outside the 3D model because we are working on something called injecting data at the 3D model.

So for instance, we could inject the total gross area to the model. We could manipulate the data before we insert it to our local database. So here we can group by the category, see all the walls with all types how much CO2 and how much does it cost and how much time it needs.

And of course, the platform-- it has the power to visualize or simulate not only on a 3D model, of course, on the 2D models as well or 2D sheets. That's giving also a better insight for the stakeholder or the project owner. Of course, as you know already that a client sometimes is not willing to pay for every component at the 3D model, so we don't design everything during the project phases design or technical phase.

So me and the team-- we developed a functionality to incorporate manual inserting component or element from outside the 3D model. So basically, you have a model with maybe 100 radiator. But we model only one of them, but we know already there is 100, so just to get better insight on the total price or time.

Of course-- as you, of course, heard about today, we have a hype about AI and ChatGPT. So basically, we were thinking, me and the team, of course, we have all the data we need today by the collaboration between the 3D model metadata and the data hub from our local house. Why we don't use the AI just for trying something new?

Of course, before I continue, I know there is-- we have a very high data privacy today, so basically, this is not open. This is only for internal use and just for the proof of concept. So I would like to leave you with one-minute video demo here.

[VIDEO PLAYBACK]

So here I'm asking how many windows at the 3D model. Of course, the AI select it and try to write me all the type. And now I would like to see the price for each of them. The price, of course, is not included at the 3D model, so the AI start querying data from our database in order to learn how much is it. And now also I'm asking how much the carbon footprint for the most expensive window, which is-- yeah.

It's pretty cool, isn't it? It's a great assistant, at least for me. Yeah. And here I would like, as promised the team, to talk a little bit about our sequential API diagram. I'm going to speak very high level, but I'm happy to take it if there is a detailed question afterwards. So basically, the main technology we use is very modern. We use React, Redux, Nest, and GraphQL with Apollo server.

So the app infrastructure-- it's work like that way because the app is built entirely on top of Autodesk technology. So here we log in through Autodesk. We get the access token. Then we gain the user details to know who's logging into the platform and what project working on, and then afterwards we query all the data from the 3D model. And then we aggregate it with the data hub in order to build a price list, which I'm going to speak about in the demo.

And of course, as a back end, as I mentioned, we use GraphQL and Apollo server because it's helped us a lot in optimization, and of course, we query very, very large data usually from various data sources. So GraphQL-- it helps us much better, and it's better for environment since we're talking about. So you don't need to do a lot of computational power and different servers here.

And of course, I was so happy to hear that Autodesk-- already they going this path, and they are developing a GraphQL. So we are looking much forward to collaborate more with them and see how we can improve this technology.

And now is the product demo, as we say, the moment of truth. So I had made a short video to explain the [INAUDIBLE] and I will be speaking a little bit through the process. So I hope you will enjoy it.

[VIDEO PLAYBACK]

ABED AARABI: So here we log in, as I said, and using Autodesk platform because it's built all of it in Autodesk. We have access to the ACC or BIM 360. We can see all our hubs, the projects, the folders. It mirrored the same structure so user-- they don't get confused. And of course, we developed functionality to add them in favorites so easier to access.

Here we load in a model. Of course, we group them by category. You can see the total CO2 and the cost and of course time for this group. Of course, you can group by any parameter, but we use category for the simplicity. You can see all the types of it here.

So let's try to run a simulation between those three categories, wall, floors, and foundation, and let's use CO2. By doing that, you can see the 3D model start coloring that. You could see which element has the most high CO2 or the low and, of course, the time, which one it takes more time than the other to be built.

And here also is the same, the total price, because we know already the location from the 3D model, we know the type, and we have an advanced relation between the data hub and the 3D models in order to start doing this operation.

So here, of course, let's say we would like to build a price list for a client but we would like to manipulate the data at the 3D model before we build this, so here we can edit it. Let's say this wall-- it has a bigger area. So we can change it.

And of course, we can fix the volume number as well. And when I save, it's automatically recalculate everything. And here I would like to build a price list for floors. I build the project in advance called AU 23.

So now I go to the project type.

Here we dispatch the data from the 3D model and the data hub, so all the data sources-- it become one in one place. So basically, you can get the total if each parameter already we decided in advance and those parameters. Of course, as I mentioned in the beginning, here we can incorporate element that it's not exist, so let's say, take this window. It's very smart to know how to calculate it to bring all the materials, so here let's say by piece, which is [INAUDIBLE], so I want six of them.

And then when I add it, it calculate the price and the CO2 and everything and show it in different color. So I could see that this wasn't exist at the model. I add it manually because it has a green color. Of course, we can export it to Excel to share it very fast between colleagues, and then we can copy from project to other so not repeat the job.

And, well, this is actually the most top functionality as I promised the team to bring to you to today. I just want to mention something. We were facing a big challenge in this application was to bring a lot of data on the browser and how to run all the data same time smoothly. So that was very advanced work, and I would really thank our team because they were doing tremendous advanced work to bring all of it in the browser. Thank you so much. I would like to hand it again to Morten.

MORTEN ANDERSSON: Thank you, Abed. I think it's pretty cool, and I'm quite proud of what Abed and the team have achieved. Now, you could think that this is only a prototype and a demo application, we assume, but actually, we have implemented it in our production.

And I have three quotes here from some of our colleagues, our CEO, Alex Frankel, who-- he knows the power of a data-driven company and approach, and so we have been working with this. And his goal is that we will be in top five in the Nordic working with applications like this. So he absolutely support the work we have been doing.

And Petras, who is working with custom manager on a daily basis-- he has been testing this, and he has been working very close together with Abed, developing the tool, and he already use it. And he estimate that the time he spent on doing the cost management is-- there is a lot of effort, a lot of advantages.

And Rune also has been part of the development. He's head of our department. He is looking ahead, saying, now we have this tool. And he can see the possibilities on making the decision-making process even smoother for the client and draw the client into the design process in a much more advanced way. So we believe that we have quite a powerful tool here.

So as said before, now we have achieved to prove that we could create this application, but we don't stop there because it's only the beginning. We are looking ahead even further develop this tool, and we would like it very much to do it together with the colleagues in the branch, together with some of you maybe because we need to share these kind of innovative hubs because we need to. We have to do this to make it easier for us to live on the planet.

So please get in contact with us. We will be happy to discuss and to develop together with you. So yeah.