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AEC Futures Briefing: Water

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Curious about the road ahead for Autodesk's product and service offerings for designing and maintaining water systems? Join Autodesk product and strategy managers to learn about new features and functionality supporting the capabilities and workflows you need to design and manage water systems and resources more effectively. Learn about the strategic insights and decisions driving development directions, and see early demonstrations of features and workflows yet to be released. Peer into the future of the products you use every day, and engage with Autodesk to help shape those products to better meet your needs and the needs of your company, project teams, and clients.

Principaux enseignements

  • Learn about Autodesk's development priorities for improving and enhancing software capabilities for the design of water systems.
  • Learn how new and prospective features on AEC product road maps will better support industry workflows and outcomes.
  • Engage with Autodesk product development teams to provide feedback on features in development.

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      Transcript

      BRIAN DEELY: Well, good afternoon, and welcome to today's futures briefing on Autodesk's water solutions. My name is Brian Deely. I'm the Director of Product Management for Autodesk's Water Infrastructure Solutions, and I'll be your host today. I'll start off with a brief safe harbor statement. Is that presenting? It's supposed to be up here.

      MIKE MALONEY: Yes, it's not.

      BRIAN DEELY: There we go. So I'll go through this really quickly. Just you've probably seen this before in some of the sessions earlier. But of course, this being a futures briefing, we'll talk about things that are going to be happening in the future, making forward-looking statements about the future of our products, and our services, and our solutions. And so we just want to let you know that this is just about our intent, and that there's no promises or guarantees that these are going to be things that you should be making purchasing decisions on.

      So with that, I'd like to introduce Roy Otero, who is our Strategy Manager for the water industry. And he's going to go and give us a brief look at our strategy and the future of the industry. Roy?

      ROY OTERO: Thanks, Brian, and good afternoon, everyone. It's a real pleasure to be here. As Brian was saying, my name is Roy Otero. I'm a Water Industry Strategy Manager here in Autodesk, and I want to just spend a few minutes introducing our strategy for water before handing over back to the Water Lifecycle Product Team for their really exciting updates on the products for the water industry.

      So I want to start by really quickly providing some context in terms of what we're seeing around global trends impacting our industry. And we really live in a very different world than what we had five years ago. The industry is changing around us at a very rapid pace, and we can see several themes emerging there.

      There is a really unparalleled demand, something that we've never encountered before, coming from multiple angles, hitting us all at once in a perfect storm at the moment. There's customer and regulator expectations that are increasing and are asking our industry to become more circular, become more sustainable, and also build some climate resilience in the process.

      There are also additional pressures that we're seeing coming from demographic shifts that we're seeing in population growth moving more mostly towards urban areas. And lastly, we have also challenges but also opportunities from the point of view of stimulus packages and funding coming through the pipeline to help with post-COVID recovery but also to upgrade infrastructure that has been perhaps endemically underinvested and is degrading fast.

      In the middle, we can see that also the way we work has changed. So remote or hybrid work has become the standard. sorry, where did I go there? Sorry. And the materials supply chain has also been through some disruptions recently. We also see in challenges recruiting and retaining talent. And perhaps our industry was attractive and is not so appealing for the younger generation as once was.

      And lastly, all this results in a need for accelerating digitalization that we're seeing from customers that are more ambitious and demanding more of us. And what that means is we are faced with a multiple array or an explosion of tools and also data that not necessarily translates into more valuable insights or better decisions at the pace that is required.

      We're also seeing demands from customers talking about digital twins or AI or generative design, but we need to recognize that everybody is on a different maturity journey, and those things mean different things for different people there.

      The bottom line here is that despite that challenging background, the water opportunity continues to be large. Water is one of the fastest-growing subsectors that we serve here in Autodesk, and it grows at over 5% CAGR projected until 2027. Continues to outperform GDP growth by a really healthy margin. And as I said, is one of the fastest industries growing worldwide.

      At the same time, a high proportion of that growth is coming from the utility space, where water utilities are investing really heavily to grow, to upgrade, and to maintain and operate all water infrastructure and thus helping to drive a very sizable ecosystem of companies along that journey too.

      So in every scenario, and whether we are faced with excess water and we're helping to manage flood risks, or not enough water and we're helping to protect our precious resource, or there's something wrong in our water. So we monitor and simulate and visualize how to manage and remove pollution or the need to respond to a continuous increase in demand for water. We can analyze the best way to ensure customers sustain supply.

      Technology plays a pivotal role in helping to understand and address those issues. That is the constant there. And it helps us to overcome the challenges that are impacting our industry, our customers, and the environment in every scenario, as I said.

      And our response to those challenges is articulated in a wide portfolio of water solutions that enable our customers to achieve sustainability outcomes across the different disciplines and throughout the lifecycle, and also impacting multiple personas that work in our industry. Autodesk continues to invest in developing solutions that meet the needs of our customers of today. But more importantly, we're also looking to meet the needs of the customers of tomorrow.

      And it is this drive to transform and push boundaries that is articulated in our strategy for water and signifies the three areas we are investing on primarily. We're investing in many more, but these are the three key pillars. What you're going to continue to see exciting progress and my colleagues will tell you a bit more in detail after I finish.

      Firstly, we are looking to accelerate digital project delivery, and this refers to developing more effective ways of managing data and information, enhancing collaboration through multiple teams and disciplines that work in multiple locations all at once as well.

      Optimize life cycle processes means doing what we do well, better. And it's about continuous improvement to delight our customers with the power of automation, simulation, and analysis, and in turn to help us drive powerful insights and efficiencies all the way from planning and design into operations and maintenance.

      And lastly, enable an open ecosystem means augmenting the value of our solutions through leveraging partnerships and integrations, and also continuing to invest in open standards and connectivity to third-party solutions.

      So successfully executing on that strategy will allow us to realize our vision of delivering full water life cycle management for smarter, more resilient, and sustainable water systems. And in order to achieve that, we need to continue investing in making our products more accessible, more efficient, and more interconnected than ever before.

      So I'm now delighted to hand over to Brian and the water life cycle product team for what is going to be a really exciting walk through some key workflows and use cases for that you wrote to as water solutions can help you with. Thank you very much.

      BRIAN DEELY: Thanks. Thanks a lot. OK. There we go. Thanks, Roy.

      To begin our next segment, we'd like to talk about where we're going, what we're building towards in the future with our drainage design segment. And to do that, I'm going to introduce Brett Singley. He's our group product manager for our core hydraulic modeling products. And Brett, why don't you get started by talking about one of the great outcomes and projects that one of our customers is working on?

      BRETT SINGLEY: Yeah, absolutely. So I want to tell you a little bit about Charleston, South Carolina. The city was founded about 350 years ago. It has an abundance of water. It was built on a marshy peninsula. And with all that water comes a lot of opportunity, economic opportunity that can provide commercial access to the area, but it also provides a lot of opportunities to flood.

      We've seen a lot of that lately, especially in the eastern half of the US this last couple of weeks. And this project that I want to just describe to you all was such an inspiring use of some of our software. So traditionally, drainage design has been used to just get water away from where we don't want the water as fast as we can. Let's see where we can push it down and push it away.

      But new designs are really intending to try to keep the water where it lies. Let's use it. Let's get it into the ground where it should be. Let's store it for a time during the storm if we need to, and let it trickle back into our ecosystems so that we have a less impact on our natural systems.

      The innovation that JMT was able to use as they worked with the city of Charleston was-- we watched a whole presentation on it earlier this week, and it was fascinating to see the interchange between the hydraulics that were important to keep the seawall barrier firm and to make sure that when you create a seawall, you're not just trapping the inland flood waters inside. A wall works both directions.

      And so by integrating the drainage design as part of this barrier seawall, they were able to make a system that is projected to last them for the next 100 years instead of just the next 10 years, next 20 years. They believe they have increased the height in ways that will be valuable to the city and protect them for the next 100 years.

      There are several personas that are involved in a project like this. You have the civil designers, that are in charge of making sure that the whole project is done to code and is going to solve the problems that they intend to solve. You have the hydraulic modeler, that has that important piece to make sure that the road that's on the other side of the seawall is not going to flood and cause other problems as you've impacted the natural design. And lastly, you have the city, who's the one that's impacted the most.

      The intuitive way to work would be altogether. Until recently, it's been just files passed back and forth. But InfoDrainage, connected to Civil 3D, can provide the whole team working on the solution together. We've got some examples inside the software to show that off.

      So what you're seeing here is a screenshot. The first screenshot is just a really quick snapshot of the InfoDrainage. Apologize. The InfoDrainage. It will quickly jump over to Civil 3D, and we'll talk about it as it goes through the process.

      They've taken the hydraulic model, brought it into Civil 3D, but it's got attached parts. So the technical parts inside of Civil 3D are the same parts inside of InfoDrainage. In the example here, we're grabbing a profile of those parts. This is something that civil engineers do all the time.

      Civil designers, they need different ways to look at the profile of their pipe. But because this has been connected to InfoDrainage, we not only have just the pipe profile, but we also have the hydraulic information on every single element that has been brought over from your hydraulic model.

      This isn't possible with other software. And since joining Autodesk three years ago and this software being available, we've continued to innovate on the way that Civil 3D interacts. And it's mostly come from interactions with many of you in the audience, and some of you at home, probably. But it's finding out from you where we need to push the boundaries and where we need better connectivity because going back and forth, and trading files, finding out there's a clash, it's not sustainable. It's not the way we can work moving forward.

      Last year at the futures briefing, we introduced something brand new, our first AI into drainage design. So last year, we introduced this and what it could do, the deluge model. It dropped water on a ground surface, and then we use machine learning to speed up a process that used to take five minutes, maybe, to be a couple of seconds. And it was great, but it was just using the ground model.

      Since last year at the futures, we have enhanced this capability. We have made it so that when you put a pond, when you represent a pond in InfoDrainage, the rain falling now will understand that that pond is there and the water will pool to that. Moving forward.

      BRIAN DEELY: Or a swale.

      BRETT SINGLEY: Or a swale. Good. Excellent. Lots of different green infrastructure. What we have now, and what you'll see here, is where we're moving toward-- not just the fact that we can have the pond impact, but instead of moving the pond and rerunning a simulation or rerunning the drainage, it will happen instantaneously.

      Again, we went from five-minute simulations down to a couple of seconds, but you still had to keep going back and hit Run. Now it's an interactive model. This is not your final design. This is not. We haven't made simplified hydraulic modeling down to just drawing a line and then we know we've got a good design. But we have made that preliminary discussion much easier.

      Solving problems. When you get those the civil designer and the city planner, and you can do an initial estimate of where do we think it might work. Let's see. Just do some trial and error really quickly and move it around. It allows you to get to the starting point of a true hydraulic model much quicker.

      And what I'm so excited about is, we had a customer recently that reached out to us, and did a presentation for us, that said, he was able to use this in front of the customer. He was able to run the quick deluge, and they quickly produced a picture where he said that there was flooding. They showed a picture where it had flooded there recently.

      It's those kinds of interactions with various groups that make people more excited. It makes them buy in. They believe what you're doing, and they're more invested in the project. I'm just really excited to see that integration of the whole team working together so that they're working toward that same solution.

      BRIAN DEELY: Thanks, Brett. Really excited about what we're doing in the drainage area. Now I want to switch gears really quick here. And I'll introduce Mike Maloney. He's our senior group manager for product management for our SaaS solutions.

      And Mike, one of the things that we hear from a lot of our customers is that they're now finally able to move from being reactive in asset management to being more proactive. Why don't you tell us a little bit about what one of our customers, Bonton Associates, is doing in that area?

      MIKE MALONEY: Yeah, sure thing. So, hey, everyone, I'm going to talk a little bit about our asset management solution today. And particularly to start with how one of our customers is using our new cloud-based tool to do their job more effectively, to be more data-driven, and ultimately make more intelligent decisions around their asset planning.

      So for Bonton Associates, they're located in Louisiana. And they stand out for their proactive, data-driven approach to water management. And their strategic goal of eliminating sanitary sewer overflows certainly reflects their commitment to sustainable water solutions. They really focus on small municipalities, who often lack funding and require federal stimulus funds for their big projects.

      So Bonton Associates remains at the forefront, serving as a bridge between the community and the technical expertise that they provide. And they help ensure a sustainable water future for generations to come. So being a technology-first company, Bonton Associates looked to us for our latest cloud-based technology to help them make more intelligent asset planning decisions with the city of Baton Rouge.

      Bonton Associates actually was previously a desktop customer of ours for our asset management solutions, and they were actually one of our first early adopters of our product Info360 Asset. They used Info360 Asset to help streamline their inspection collection process, their condition assessment, and ultimately, building out rehabilitation decision tree for the city of Baton Rouge using Info360 Asset.

      So really exciting to see this case study out there for one of our early adopter customers and also see an impact made on actually a fairly large city in Baton Rouge, in Louisiana. And Bonton Associates is really excited about how easy the product is to use and how they can use it on both large and small sewer systems.

      So focusing on some of the personas, really, this is a focus today on the jobs to be done. How we're helping specific personas do their job better. I actually have four here for our Info360 Asset workflow. One of our main focuses when we started to build out our cloud-based solutions for asset management was to make sure that more personas could be impacted and have their jobs made easier with these tools being collaborative, cloud-based. And so in this situation, we actually have four different individuals who use our tools to streamline these processes.

      So first, we have the field crew. They typically rely on manual inspection methods when inspecting their sewer pipes that are buried underground. They have to be certified in coding standards based on whatever region they're working in. So in the US, that would be PACP or MACP. And they're really looking at collecting the data most efficiently and quickly to get their job done and deliver the work while also coding correctly into the spec of the contract that they have agreed to.

      Secondly, we have our GIS manager. They have challenges in integrating data from multiple sources. They have to manage large-- also a data manager here as well-- managing large volumes of CCTV data and providing it to stakeholders that need to use it in context. And they also need to provide the single source of truth for their GIS, in this case, for their water or wastewater utility, and providing that data to any stakeholders, again, who need it to use it in any given context to do their job.

      Next, we have an engineer/intern. They spend hours and hours of manually reviewing CCTV survey data. If you were just in the last session on our AI capabilities with the company Vapor, this is a really common persona actually in the industry, where they'll have an intern or an engineer come on board and actually review hours and hours of CCTV footage to check it for accuracy and make sure that it can be used for proper condition assessment.

      And lastly, we have the Asset Planner. They struggle with prioritizing projects based on the actual conditions of the assets that have been inspected. These condition data often isn't incorporated into the capital planning, and also they struggle to get model results and get data from their modeling and engineering teams to incorporate into their capital plans.

      So getting into one of the new and-- I'll talk a little bit about what we've launched this year, where we're going, and also what some of our main focus will be next year and beyond. So focusing on one of the new things we launched this year with one of our key partners in this space, Vapor, is really a brand-new transformative workflow for condition assessment and capital planning.

      So we've broken it down really into a six-step process, which is a brand-new workflow. First step is you inspect your pipe. And in this workflow, you can choose to code the pipe in the field, like it happens typically or is typically done, or they can just quickly do a pass-through of the pipe and capture that video in the CCTV inspection.

      The next step is to upload it to our cloud environment in Info360 Asset through a simple drag-and-drop process, which then, through a two-way seamless API integration, integrates with Vapor's AI engine. And I know Michelle is in the room somewhere over here. There she is. So Michelle is a co-founder at Vapor, actually, with Amanda, who's also her co-founder. We started partnering with them about 18 months ago or so to build out the integration.

      And what happens is the video is uploaded to our platform. It gets sent over to their AI engine, and those defect codes, rather than being manually scored in the truck or as the footage is being captured, are automatically scored using AI, which takes processes that were typically taking 30 minutes plus per video down to a quick pass-through with the AI. And then the user can step into the application, check the results, validate that it's most of the way there, and then accept that inspection or make tweaks as necessary.

      So data is uploaded to our cloud. The AI engine runs on the inspection. Generates a defect score. That defect score can then be used when calculating the risk score to do your asset management, which ultimately can feed your rehabilitation actions. And those plans can then be shared out within the web application.

      So if you think about the marriage between the two companies here, the partnership really Vapor excels in the left side of this diagram-- steps 1, 2, and 3. And then, with our integration, we pick up that data and we put it to use in a capital planning context. And here's just a little example of how that's working. So in this case, the users in our application they've chosen to use to enable the Vapor processing. They will upload a video to our cloud, it's going to run through the upload process, and it's going to get sent over to the Vapor engine.

      So currently, we have a video of record. It's currently processing in the AI engine. Within Vapor, you can see this is uploading, and the video is being analyzed seamlessly. So the AI is running on it currently, comes back to Info360 Asset, and the AI has been processed. And now the user can review those automated defect codes in our application or they can head back out to the Vapor platform to also edit in their platform.

      Two-way integration have all the changes synchronize automatically between the two apps, so you can make changes in either platform, and they will sync back and forth. In this case, they've completed the inspection. It's going to automatically be marked as complete in our app. You can see there the changes have been updated, and now they have a fully coded CCTV inspection, all created by AI and then checked by the human user.

      And so next we have, we've collected the inspection data. How do we put it to use? So we have a risk analysis module in Info360 Asset that can use CCTV scores that come in from those inspections. They can also use data from a multitude of other sources, like geospatial data, work history on the assets. And also what I'm going to show you in a second here is model results coming in from our hydraulic modeling tools.

      Super-flexible risk engine that we've launched, you can do a risk matrix analysis, you can set up your own categories and scoring, and really customize the answers that you get for your relative risk model on your network. And then just launched recently as well, is our integration to InfoWater Pro and WS Pro. So I'm showing here an example on the right of-- I think it's playing. Let me just. There we go.

      So within WS Pro here, you're going to export the results directly to the Info360 cloud. And in this case, they're exporting out the number of impacted customers based on the model run, the number of hours, and the total anticipated cost of that data. So you have the simulation engine generate the results, you publish it out to Info360 Asset, and you can use it in a planning context.

      In this case, they want to know what's the consequence of failure for this particular asset. In our simulation results can tell them precisely how many customers have been impacted and what the relative cost would be. You'll continue to see more and more of these integrations built out. We actually just recently launched an integration with InfoWorks ICM, as well, and you'll see eventually, our entire water portfolio fully connected in the cloud, delivering new results and benefits to our customers.

      And then here's taking that data and putting it to use in a rehabilitation decision tree. So within the rehabilitation decision tree, you can query all your work tasks, your CCTV data that was collected using AI. You can use your risk scores to really get a prescriptive rehabilitation action and associated cost for any individual asset in your network.

      And lastly, in terms of recent things we've launched this year, before I get into what our main focus area for the futures will be this upcoming year, is our two-way integration with our partner Esri. You've probably heard a lot of at various sessions, including some of the keynotes. Esri and Autodesk are both top-tier partners of one another. And we've actually put that to use by getting our development teams together here and building out a two-way integration with ArcGIS Online and the Info360 platform.

      So what we've built out here is a two-way integration. You can bring in your GIS into Info360 Asset. You can also publish results out to ArcGIS Online to build out dashboards and share out those web maps with other stakeholders. So in this example-- this actually came from a customer who just recently did a case study with us on some of the data that they've published out of Info360 Asset and into online. And you can see here they're looking at the scores coming in on their CCTV data, the CCTV inspections carried out, et cetera, Built out into dashboards.

      So let's talk a little bit about our future focus. And this isn't long-term future. This is actually near-term areas that we're focusing on for our asset management solutions. So I've talked a little bit about existing integrations that we've built out. We've integrated with Esri bidirectionally. We'll continue to enhance that Esri integration, including adding Living Atlas layers to our application.

      We recently launched Esri base maps within the Info360 platform, just doing better synchronization of their data as well. But we're also going to integrate with other tools that are out there from CMMS systems, from popular vendors like Cityworks and others, as well as inspection collection software, so we can integrate directly with the other cloud environments where that inspection data is captured and housed.

      And then, last but not least, certainly is actually publishing out an API. So that users and consultants that work with users who have the development expertise can build out their own custom integrations into our cloud platform, and really extend its capabilities and customize as needed to help customers get their job done.

      BRIAN DEELY: Thanks, Mike. I really enjoyed that because you hit on two things that we really hear a lot from customers. Number one is being able to integrate our workflows within the ecosystem. So obviously, you touched on that a lot. But also integrating our workflows between our different products. We have a large portfolio of products. And that's one of the things I hear from customers a lot is being able to integrate within our portfolio.

      So with that, I'd like to switch gears and bring Brett back up. And I think one of the things that we're historically known for with our hydraulic models is supporting master planning. So we'll touch on that. But first, maybe you can give us a little background on a great customer story from Fayetteville, North Carolina-- not Arkansas. I always mix that up-- but Fayetteville, North Carolina, and some of the work they've been doing with ICM to actually improve their stormwater management.

      BRETT SINGLEY: Excellent. So the city of Fayetteville, another Carolina, different Carolina this time. And I have another example in Carolina. I was very Carolina-heavy this presentation. But in Fayetteville, North Carolina, they also had flooding problems. Different problems than we were looking at before. But in this large area, they had several different regions of their system that-- pardon me. I think we're good now.

      They had several different regions that they had flooding concerns with, but they had a really hard time figuring out what data they needed and what data they had available to really attack the problem. The challenges of limited data, resource constraints that I'm sure many of you guys are aware of, and securing funding to help solve that problem was, it felt insurmountable.

      But they reached out to one of their consulting partners. I believe it was Freese and Nichols, and they talked to them about how much data they did need to create hydraulic models. They talked about what was the best tool to be able to use and start to create hydraulic models so that they could even begin to create a plan. Their plan in the end was that they wanted to do a worst first solution. So if they can analyze each of their different watersheds, they could find out which areas would have the biggest impact by fixing first.

      Just by creating those hydraulic models and having a plan, they've had some great success there. They're claiming that they've got nearly $25 million benefit over the next 10 years. And a lot of that was just achieved by being able to show what positive impact they were planning on having on in the various areas of their service area.

      The personas involved in master planning are hydraulic modelers. Again, pretty much whenever I'm up here, expect to see something about hydraulic modelers. That's my shtick. Master planners. So sometimes that's the same person as the hydraulic modeler. They're helping out with that. Other times, it's a different persona. But the person in charge of the Capital Improvement Plan. We've got a bunch of pipes and assets in the ground, and we need to be able to know what we're going to do with them next time we need to do something with them.

      And lastly, often, you guys know there's not necessarily a person in charge that's called a risk manager. In some places, there are. But someone that's in charge of managing the risk at the utility and understanding that a flood on a small cul-de-sac that has just a few houses on it is not the same as a flood on your main highway through your city.

      Someone's job is to help understand that. And it's not always an engineer. It's not always someone that understands the hydraulics. But we need to be able to bring them together. We need to be able to gain confidence in that hydraulic model as part of the master plan so that everyone's speaking the same language.

      Brief overview of what's required. So one of the big problems in this case study was they didn't know how much data they need. They didn't know what steps to take to start creating a hydraulic model. Building hydraulic model can take a lot of data. To make a really well-calibrated model, you need more data. But a lot of the data is freely available. There are sources, in most cases, that are good enough to get you started.

      And so, I want to emphasize that model-building process. We want people to just get started. If you have flooding in your city, we can start with what we have. We can start with some ground elevation data and some free storm data that might be available in your area and start to make progress.

      Once you create your model, make sure it's all connected and make sure everything's working right. Then, you're going to run a simulation. This is a pain point of all modelers. There's so many times I talk to customers that say, especially in other software, where we would often come up and say, all right, I know this run's going to take me several hours, so I'm going to wait till Friday afternoon to hit the button so that it doesn't disrupt my workflow. So simulations historically have been really intense on your computer CPU and GPU.

      Lastly, reviewing the results. So you run this simulation so that you can visualize the result and see what the impact of different storms are in your system. Again, starting, I think it was about a year and a half ago when we first introduced cloud computing, we got a lot of people asking questions about it, not really sure how it was going to impact them.

      But we've seen such great growth lately, with customers really pushing the limits, doing things that they absolutely have never done. Running thousands of simulations at a time and not having to do that on a Friday night before they leave for the week. And again, crossing their fingers that it actually ran while they were gone.

      A part of the beauty of the cloud is that it's not only allowing for better, faster simulations and better model management, but it's making that productivity. When we don't have to have a server that's dedicated to hold all the results to make sure everyone has access, it's just included in your ICM subscription. So anyone within your Autodesk team we'll have access to the model and can start to work on it immediately.

      In this video, we're also showing how the simulations can be sped up significantly. In this example, we've just turned on several different scenarios and done a full spectrum of rainfall. We're running those simulations. And in the past, if this was running on your own local machine, you're going to see these simulations start ticking off and being run in the cloud.

      But in the past, that would have been done on your desktop or maybe your remote server, if you were lucky one to have it set up that way. But on your own local laptop, you're going to have a simulation run, do its thing, preprocess, process, finally simulate, and then the next one can start preprocessing. And then, once that's done, the next one can start preprocessing.

      This is an example in the cloud. We've got access to more CPU power than you needed, and you don't have to wait. As soon as you come up with the idea of what you want to simulate, you can start simulating now. It's not going to affect your workflow on your local machine.

      And you can see the impact that can have here. We legitimately recently had a customer that ran, I believe, 12,000 simulations. Very short simulations, mind you. These weren't the hour-long simulations. But they were able to run those in a day and do things that they have never thought possible.

      And so, it's really exciting to engage. And I encourage you, as you play with it, to engage with us. Tell us the cool things that you're doing with it. We can get you on stage next day. But we just want to know what you're doing so that we can help you and build these workflows in ways that will help you moving forward.

      The next piece is integrating that with Info360 Asset. Again, part of our whole reason for bringing the model to the cloud is so that we can interact with others of our own products and of our partners. This is an example of the return period analysis that's in ICM. And you can see us working in ICM here, creating several simulations to look at different return periods, storms, and see how that impacts your system.

      You then can save that data and export it to Info360. From there, you will be able to use that in two major ways. So one, you can just look at the risk impact on your system. We're now not in a hydraulic model. Info360 Asset is significantly less scary for a non-modeler to interact with.

      That person at the utility that wants to just understand, where do I have the worst flooding and what's the difference between my main thoroughfare on a five-year flood, a 10-year flood, a 100-year flood, which we've been seeing lately. So someone without that background can go in there and assess the risk of how their city might be impacted.

      The other part is that it can actually be incorporated into your rehab planning. So if you know that you have a capacity problem, you can add that to your risk profile and your decision tree inside of Info360 Asset so that when you do know that you're working on that road in the future, while it's dug up, you're going to be designing a bigger pipe, or maybe some new green infrastructure that can help contain that water locally for a little bit longer.

      Creative new ways to work with the software. And it's so exciting that we are helping the asset management. The guy in charge of the CIP and the woman in charge of the hydraulic model can now talk the same language and can interact with those hydraulic results.

      BRIAN DEELY: Can you tell everybody what CIP means?

      BRETT SINGLEY: Yes. Capital Improvement Plan-- took me a second. Capital Improvement Plan or Program, depending on who you talk to. But that's just the overarching plan of how long are my assets going to live and planning to replace them with life size or larger size if your city is growing. And I'm going to stay up here. Do you have a little interest?

      BRIAN DEELY: No, I was just going to say. So you touched on it a little bit. But I think one of the things that I'm really excited about is that, we've been talking about using hydraulic models and helping engineers do better engineering. And I think one of the things that actually people have been asking for a long time is how can we leverage hydraulic models not just for engineering analysis and planning, but how can we really leverage those in operations. So, Mike, you want to help Brad out?

      BRETT SINGLEY: We've got both. Yeah, we'll talk about them together a little bit. So one of the items we have here, so our case study-- because we want to get through some of this pretty quickly so that we can have some time for Q&A-- this case study is Davidson water, the innovative thing they were doing is some surge modeling.

      So recently we've included surge modeling inside of all of our water distribution products Surge. I don't know if any of you are at a hotel where when you turn off the faucet really hard, you hear a clunk in it. I think we've all been to a shady hotel like that in the past. But that's caused by the pressure in the water and the momentum of the water abruptly having to change in. It's butting into things.

      So we have software that inside of our water distribution software, whether it's inflow InfoWater Pro or WS Pro, that helps you analyze that in ways that allow you to throw in different surge protection devices and see how it impacts. The big thing for us is that we're doing that on the whole system and not just a really localized problem. So on the bigger scale, this is when you lose power and a well turns off or a pump station turns off.

      The personas involved in hydraulic modeling on the water distribution side. And this is where my background is in. This is what I love to talk. So if anyone wants to talk later about water distribution, please come my way. But again, we're dealing with a hydraulic modeler. We're going to talk about operations a little bit more in this one and an asset manager.

      One of the great things that the products that Mike's team is working on with Info360 Insight, they've made it possible to be able to visualize a lot of this data in ways that we haven't been able to before. And you've been to some of the customers that are using this on a regular basis. What impact does that have when they can finally see some of their data?

      MIKE MALONEY: Make sure I get close off the mic here. I think just having this web-based platform where they can use all the same data-- charting, graphing, mapping capabilities that we have, time series data, any kind of visualization you want to see that we enable an Info360.

      Now the modelers are going to be able to view that data and use it in new and creative ways that they might not be able to do in the desktop. So this is a really good example of us leveraging our platform capabilities and the interconnectivity between our modeling products and the cloud to offer a bunch of new workflows and jobs to be done for modeling personas.

      BRIAN DEELY: Excellent. And so we will talk about the modeling personas and then he'll in a minute talk a little bit more from an operator's perspective. So from a modelers perspective, one of the big things that we all need to get wrap our heads around is how we can incorporate the live data coming in from your SCADA into your hydraulic model.

      We cannot live in a system where we've got a model that was done in a master plan seven years ago, and we're making operational decisions. It's the way it's been done for years, but it's not going to cut it. We need to be more proactive on saving energy and being more proactive in anticipating what the demands will be in our systems.

      These slides are here to just show you what this could look like. We've you've seen these visuals in the past, but we've got really interesting ways to show off the impact of a hydraulic model. my last slide will have a little video about it-- but how the modeled data looks versus the observed data looks.

      And one of the important steps to get those to match up, if you're on a live operational model, is actually projecting what the demand is moving forward. So we've worked with our AI team. We have a dedicated AI team for water, and we've been able to train the hydraulic information and the data that we're seeing from SCADA systems to help predict and forecast what that demand is going to be.

      We've had tools to do this in the past in our live modeling products, so this isn't a new frontier completely. But the way that we're doing it now is significantly faster, and it's ever, ever-changing. So we're really excited to be able to bring this to more people. And I guess from the operations standpoint, as a modeler, I know exactly what I would do with this and how to integrate it into my model.

      But have you noticed anything in the operations departments and the people that you've been talking about why they would even care about having the demand forecasted?

      MIKE MALONEY: Yeah. So if they can interact, again, with that data coming in from the hydraulic model with our AI technology and have that demand forecasting functionality at their fingertips, again, in this web-based application, in this case, Info360 Insight. We've launched this as beta recently. They can then use that to predict demand across 24- to 48-hour periods quickly without actually having to interact with the modeler in that case or ask for their expertise in those scenarios.

      So as Brett mentioned, we've had desktop tools in the past that have done this, I'll say fairly comprehensively. But to be able to quickly use AI, get an answer out to someone in an operational context, quickly, efficiently, and most importantly in a product that they can access in a web browser is something that we've gotten pretty solid feedback on, again, in a beta release of this.

      BRETT SINGLEY: And again, when you're all speaking the same language, looking at the same data, in the same web browser, it builds a lot of team unity. I forgot we had this full video. This wasn't working earlier, but it is working now. So we can actually just really quickly see what kind of an impact that might have if you're able to interact with historical data, but also look at forecasted model information. Again, this is the view that you'd be able to see it in moving forward. We'll try to save time and get through here.

      Lastly, we've got just some really quick examples, and I do want to go through these quickly, but we can really see how modeled versus observed data. This is an example where we had a pipe burst. So the flow was drastically different in the model than what was observed that day. And once we could pinpoint where that break was, we could make it match significantly.

      This is the tank levels that bottomed out after there was a break in the data. And really exciting to be able to see that inside of your hydraulic model and benefit the modeler, but also when you can connect to that same data that's coming into your SCADA. It makes everyone a little more excited and a little bit easier to trust the hydraulic model moving forward. And now we'll shift more to the operation side.

      MIKE MALONEY: Cool. So we just touched on how the connectivity between the Info360 platform and our desktop modeling tools can help modelers do their job more efficiently, get quicker access to better information coming out of the live data connections that we provide in Info360 Insight in the SCADA systems. We're going to flip that now onto our operator persona and talk a little bit about how hydraulic models can be put to use for various use cases operationally.

      So let's talk a little bit about the three personas here I'll introduce. And again, the first persona here is going to be your planning department or your modeler, but with a little bit of a different spin on it. So in this case, typically, the data that they produce in the simulation results don't integrate with other systems or other departments at the utility. They're sometimes physically disconnected from the operations group and don't have a good communication stream between those teams.

      And as such, they also get frequently asked for one-off deliverables by the operations team to help the operations team do specific jobs that require modeling data. From an network operations manager perspective. They're looking to continually provide optimal level of service under dynamic, ever-changing conditions to their network. They're looking to minimize and manage frequent failures and maintenance issues and also manage customer complaints and service interruptions that take place.

      And lastly, we have the field crew who want to help ensure rapid response, maintain safety, and diagnose complex issues while on-site. And they lack real-time data and updates and feedback coming in from operations while they're doing their job.

      So first, this will be short, just a few slides because I want to save some time for Q&A as well. We're going to talk about some of the current capabilities we have in Info360 Insight that leverage model data. So in this instance, let me go ahead and play this. There we go.

      So in this example, the user is leveraging hydraulic model data in a operational context to model the scenario of closing a valve. So they can ask questions like, if I close this valve, how many customers will be affected? And, what is the cumulative amount of time that they are affected? What course of action can they take to minimize disruption to their customers, and what action do they take to resolve the issue the fastest?

      So these exist today within Info360 Insight and they connect, again, to our modeling results that previously resided in the desktop that now are available in our Info360 cloud. So we have a dedicated interface for doing these types of simulations in "what-if" scenarios.

      And next, again within the product today. So advance the slide. Which one am I on here? There we go. Got it.

      So within Info360 Insight, we have an incident management module as well, where users can create simulated incidents and view the impact. So this involves a multi-step process. First, they're going to create an incident and manage the associated complaints, investigation, work, and impact assessment. From there, the user can create incident activities to track all the activities related to the incident by creating complaints, notes, investigation, work, or impact assessments.

      And in this example, here we have a pipe burst scenario, I believe, that we're simulating here. And with this functionality, users can assess the impact of the incident on their customers and create scenarios to explore the impact of mitigating actions they can take. So in this example that we're showing on the screen here, the user is creating a scenario where a water main break is being able to be visualized, and you can show the impact on your various customers of that break over time.

      So these exist in our software today. Again, it's modeling data being put to use within an operational context. But let's talk a little bit more about the future, about where we're going with this. So we have additional "what-if" scenarios that we're currently building out and exploring with customers currently that rely on the hydraulic model and real-time or historical operational data coming in from their SCADA system.

      So you're probably thinking, water utilities can deliver water easily under standard conditions. What's the problem to be solved here? Well, operating conditions are not usually standard or typical. They're often dynamic, and therefore ensuring optimal delivery in these dynamic situations is where scenario management or "what-if" scenarios, as we're calling them, come into play.

      So we're going to quickly explore a couple of different scenarios that our team is currently working on and exploring in our app, and they all involve, again, data coming in from the model, real-time data coming in from the customer SCADA system, as well as historical data. So the first one is the example of taking a pump station offline.

      So in this scenario, the user would disable a pump stations controls due to maintenance activity, and the remaining assets will follow their policies to operate without a pump station operating. This will give the operator confidence that the utility can ensure optimal delivery in a reduced pumping situation. So it's one example I'm going to list out four here.

      The second one is an energy demand response. In this example, the user adds a policy to pumps that pre-fill their water storage before 5:00 PM and deactivate their pumps between the hours of 5:00 PM and 8:00 PM. This gives the user assurance that there will be full storage capacity regardless of the peak energy demands.

      Next, we have an energy optimization "what-if" scenario. In this case, the user utilizes the Info360 Insight optimization tools to generate new operational policies or strategies for all pumps. This helps the utility operate their pumps more efficiently while minimizing total energy use. And lastly, and again, examples of some of many that we're currently working on is zone isolation.

      So in this case, the user deactivates all supplies into a DMA and reviews the hydraulics to report the time until water storage reservoir would drain to the target level. So look for these types of "what-if" scenarios that leverage, again, model data and data coming in from the user data system to help operators leverage model data and do their jobs better into the future.

      BRIAN DEELY: Awesome. Thanks, Mike. I'm going to close this out. I'm going to start by, as you seen, one of the things one of the things is we're moving really quickly into the future, supporting a lot of new workflows, connecting data across our products and the ecosystem. But we know that adopting new technology, and systems, and workflows that can be a lengthy transition for people.

      So one of the things that we're doing is we're extending the availability of some of our current generation of products to ensure that you all can have a smooth transition to the next generation. So we'll be doing this by making more of our products and solutions available as Autodesk subscriptions. And I'll give you a QR code in a minute that will allow you to see more information about that and actually sign up for our One Water blog.

      So the second thing is-- I'm sorry, I hit the wrong arrow there. There we go. So where to go next. Number one, you can explore more. We have public product roadmaps that you can explore on our website. They'll give you an idea of the overall strategy and direction that we're headed in product by product. That's awesome. We have a technical information hub that you can sign up for, that gives you training information about our products, on-demand training, technical notes, knowledge base, those kind of things.

      And then third, you can engage with us via our Ideas Portal. So if you have feedback on our products, ideas for new features, and those kinds of things, you can add to that. You can vote on ideas that are already in there, and you also get updates and notifications when as your ideas progress to become part of our products.

      Another opportunity-- and I'm going to go through this quickly. So if you don't scan it in time, I've actually got some cards as well that you can take and join our Autodesk research community. And it's an opportunity for you to see early iterations of products, provide feedback, and that sort of thing, so that you can help shape the future of our products.

      And then lastly, as promised, the One Water blog. If you want to scan the QR Flowcode and sign up, we have information not only about our product developments but a lot of the customer case studies that we talked about today. You'll see those as they come out, updates on conferences and shows that we're attending and those kind of things. And generally stay up to date and everything that I just talked about, the product roadmap, the technical information hub, the Ideas Portal, is also linked into that.

      So please, please do that. Please sign up for this. I want to see more and more people with their phones out. Come on. But definitely sign up for this if you haven't already. I love keeping up to date with it myself. So with that, we have a few minutes for questions. There's two microphones on either side of the room. If you want to come up and-- I know there's already a long line there of people waiting. That's for the people on line don't know that there aren't people in line to ask questions. Yes?

      AUDIENCE: I do process mechanical. What are you doing about water inside the buildings, wastewater, water treatment plants, that type of thing?

      BRIAN DEELY: So that's a good question. We don't have a solution specifically for that, but we'd love to talk to you offline afterward and talk about that a little bit more. More questions? By the way, I can't see in the audience, so.

      Well, if we don't have any more questions, we're certainly here to take more questions after the session. If you want to talk to us again, more information about the Autodesk research community as well. And thank you, everybody, for joining today.

      [MUSIC PLAYING]

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      Nous faisons appel à OneSignal pour afficher des publicités numériques sur les sites pris en charge par OneSignal. Les publicités sont basées à la fois sur les données de OneSignal et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que OneSignal a collectées sur vous. Les données que nous fournissons à OneSignal nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de OneSignal
      Optimizely
      Nous faisons appel à Optimizely afin de tester les nouvelles fonctionnalités de nos sites et de personnaliser votre expérience. Pour ce faire, nous collectons des données comportementales lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil, d'ID Autodesk, etc. La version de nos sites peut varier en fonction des tests de fonctionnalités. Le contenu, quant à lui, peut être personnalisé en fonction de vos attributs de visiteur. Politique de confidentialité de Optimizely
      Amplitude
      Nous faisons appel à Amplitude afin de tester les nouvelles fonctionnalités de nos sites et de personnaliser votre expérience. Pour ce faire, nous collectons des données comportementales lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil, d'ID Autodesk, etc. La version de nos sites peut varier en fonction des tests de fonctionnalités. Le contenu, quant à lui, peut être personnalisé en fonction de vos attributs de visiteur. Politique de confidentialité de Amplitude
      Snowplow
      Nous faisons appel à Snowplow pour collecter des données comportementales sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil et d'ID Autodesk. Ces données nous permettent de mesurer les performances de nos sites et d'évaluer la qualité de votre expérience en ligne afin d'améliorer les fonctionnalités que nous proposons. Grâce à des méthodes d'analytique avancées, nous optimisons également votre expérience dans les domaines suivants : communication par e-mail, assistance client et ventes. Politique de confidentialité de Snowplow
      UserVoice
      Nous faisons appel à UserVoice pour collecter des données comportementales sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil et d'ID Autodesk. Ces données nous permettent de mesurer les performances de nos sites et d'évaluer la qualité de votre expérience en ligne afin d'améliorer les fonctionnalités que nous proposons. Grâce à des méthodes d'analytique avancées, nous optimisons également votre expérience dans les domaines suivants : communication par e-mail, assistance client et ventes. Politique de confidentialité de UserVoice
      Clearbit
      Clearbit autorise les données d’enrichissement en temps réel afin de fournir une expérience personnalisée et pertinente à ses clients. Les données que nous collectons peuvent inclure les pages que vous avez consultées, les versions d’évaluation que vous avez lancées, les vidéos que vous avez visionnées, les achats que vous avez réalisés, ainsi que votre adresse IP ou l’ID de votre appareil.Politique de confidentialité de Clearbit
      YouTube
      YouTube est une plate-forme de partage de vidéos qui permet aux utilisateurs de visionner et de partager des vidéos qui sont intégrées à nos sites Web. YouTube fournit des indicateurs sur les performances des vidéos. Politique de confidentialité de YouTube

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      Personnalisation des publicités à des fins de ciblage

      Adobe Analytics
      Nous faisons appel à Adobe Analytics pour collecter des données comportementales sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil et d'ID Autodesk. Ces données nous permettent de mesurer les performances de nos sites et d'évaluer la qualité de votre expérience en ligne afin d'améliorer les fonctionnalités que nous proposons. Grâce à des méthodes d'analytique avancées, nous optimisons également votre expérience dans les domaines suivants : communication par e-mail, assistance client et ventes. Politique de confidentialité de Adobe Analytics
      Google Analytics (Web Analytics)
      Nous faisons appel à Google Analytics (Web Analytics) pour collecter des données comportementales sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces données nous permettent de mesurer les performances de nos sites et d'évaluer la qualité de votre expérience en ligne afin d'améliorer les fonctionnalités que nous proposons. Grâce à des méthodes d'analytique avancées, nous optimisons également votre expérience dans les domaines suivants : communication par e-mail, assistance client et ventes. Politique de confidentialité de Google Analytics (Web Analytics)
      AdWords
      Nous faisons appel à AdWords pour afficher des publicités numériques sur les sites pris en charge par AdWords. Les publicités sont basées à la fois sur les données de AdWords et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que AdWords a collectées sur vous. Les données que nous fournissons à AdWords nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de AdWords
      Marketo
      Nous faisons appel à Marketo pour vous envoyer des e-mails dont le contenu est ciblé. Pour ce faire, nous collectons des données concernant votre comportement en ligne et votre interaction envers les e-mails que nous envoyons. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil, de taux d'ouverture des e-mails, de clics sur des liens, etc. Nous sommes susceptibles d'utiliser ces données en combinaison envers celles obtenues auprès d'autres sources pour vous offrir des expériences améliorées en matière de ventes ou de service clientèle, ainsi que du contenu pertinent basé sur un traitement analytique avancé. Politique de confidentialité de Marketo
      Doubleclick
      Nous faisons appel à Doubleclick pour afficher des publicités numériques sur les sites pris en charge par Doubleclick. Les publicités sont basées à la fois sur les données de Doubleclick et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Doubleclick a collectées sur vous. Les données que nous fournissons à Doubleclick nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Doubleclick
      HubSpot
      Nous faisons appel à HubSpot pour vous envoyer des e-mails dont le contenu est ciblé. Pour ce faire, nous collectons des données concernant votre comportement en ligne et votre interaction envers les e-mails que nous envoyons. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil, de taux d'ouverture des e-mails, de clics sur des liens, etc. Politique de confidentialité de HubSpot
      Twitter
      Nous faisons appel à Twitter pour afficher des publicités numériques sur les sites pris en charge par Twitter. Les publicités sont basées à la fois sur les données de Twitter et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Twitter a collectées sur vous. Les données que nous fournissons à Twitter nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Twitter
      Facebook
      Nous faisons appel à Facebook pour afficher des publicités numériques sur les sites pris en charge par Facebook. Les publicités sont basées à la fois sur les données de Facebook et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Facebook a collectées sur vous. Les données que nous fournissons à Facebook nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Facebook
      LinkedIn
      Nous faisons appel à LinkedIn pour afficher des publicités numériques sur les sites pris en charge par LinkedIn. Les publicités sont basées à la fois sur les données de LinkedIn et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que LinkedIn a collectées sur vous. Les données que nous fournissons à LinkedIn nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de LinkedIn
      Yahoo! Japan
      Nous faisons appel à Yahoo! Japan pour afficher des publicités numériques sur les sites pris en charge par Yahoo! Japan. Les publicités sont basées à la fois sur les données de Yahoo! Japan et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Yahoo! Japan a collectées sur vous. Les données que nous fournissons à Yahoo! Japan nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Yahoo! Japan
      Naver
      Nous faisons appel à Naver pour afficher des publicités numériques sur les sites pris en charge par Naver. Les publicités sont basées à la fois sur les données de Naver et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Naver a collectées sur vous. Les données que nous fournissons à Naver nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Naver
      Quantcast
      Nous faisons appel à Quantcast pour afficher des publicités numériques sur les sites pris en charge par Quantcast. Les publicités sont basées à la fois sur les données de Quantcast et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Quantcast a collectées sur vous. Les données que nous fournissons à Quantcast nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Quantcast
      Call Tracking
      Nous faisons appel à Call Tracking pour fournir des numéros de téléphone personnalisés dans le cadre de nos campagnes. Vous pouvez ainsi contacter nos agents plus rapidement et nous pouvons évaluer nos performances plus précisément. Nous sommes susceptibles de collecter des données sur votre utilisation de nos sites en fonction du numéro de téléphone fourni. Politique de confidentialité de Call Tracking
      Wunderkind
      Nous faisons appel à Wunderkind pour afficher des publicités numériques sur les sites pris en charge par Wunderkind. Les publicités sont basées à la fois sur les données de Wunderkind et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Wunderkind a collectées sur vous. Les données que nous fournissons à Wunderkind nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Wunderkind
      ADC Media
      Nous faisons appel à ADC Media pour afficher des publicités numériques sur les sites pris en charge par ADC Media. Les publicités sont basées à la fois sur les données de ADC Media et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que ADC Media a collectées sur vous. Les données que nous fournissons à ADC Media nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de ADC Media
      AgrantSEM
      Nous faisons appel à AgrantSEM pour afficher des publicités numériques sur les sites pris en charge par AgrantSEM. Les publicités sont basées à la fois sur les données de AgrantSEM et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que AgrantSEM a collectées sur vous. Les données que nous fournissons à AgrantSEM nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de AgrantSEM
      Bidtellect
      Nous faisons appel à Bidtellect pour afficher des publicités numériques sur les sites pris en charge par Bidtellect. Les publicités sont basées à la fois sur les données de Bidtellect et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Bidtellect a collectées sur vous. Les données que nous fournissons à Bidtellect nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Bidtellect
      Bing
      Nous faisons appel à Bing pour afficher des publicités numériques sur les sites pris en charge par Bing. Les publicités sont basées à la fois sur les données de Bing et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Bing a collectées sur vous. Les données que nous fournissons à Bing nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Bing
      G2Crowd
      Nous faisons appel à G2Crowd pour afficher des publicités numériques sur les sites pris en charge par G2Crowd. Les publicités sont basées à la fois sur les données de G2Crowd et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que G2Crowd a collectées sur vous. Les données que nous fournissons à G2Crowd nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de G2Crowd
      NMPI Display
      Nous faisons appel à NMPI Display pour afficher des publicités numériques sur les sites pris en charge par NMPI Display. Les publicités sont basées à la fois sur les données de NMPI Display et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que NMPI Display a collectées sur vous. Les données que nous fournissons à NMPI Display nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de NMPI Display
      VK
      Nous faisons appel à VK pour afficher des publicités numériques sur les sites pris en charge par VK. Les publicités sont basées à la fois sur les données de VK et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que VK a collectées sur vous. Les données que nous fournissons à VK nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de VK
      Adobe Target
      Nous faisons appel à Adobe Target afin de tester les nouvelles fonctionnalités de nos sites et de personnaliser votre expérience. Pour ce faire, nous collectons des données comportementales lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP, d'ID d'appareil, d'ID Autodesk, etc. La version de nos sites peut varier en fonction des tests de fonctionnalités. Le contenu, quant à lui, peut être personnalisé en fonction de vos attributs de visiteur. Politique de confidentialité de Adobe Target
      Google Analytics (Advertising)
      Nous faisons appel à Google Analytics (Advertising) pour afficher des publicités numériques sur les sites pris en charge par Google Analytics (Advertising). Les publicités sont basées à la fois sur les données de Google Analytics (Advertising) et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Google Analytics (Advertising) a collectées sur vous. Les données que nous fournissons à Google Analytics (Advertising) nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Google Analytics (Advertising)
      Trendkite
      Nous faisons appel à Trendkite pour afficher des publicités numériques sur les sites pris en charge par Trendkite. Les publicités sont basées à la fois sur les données de Trendkite et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Trendkite a collectées sur vous. Les données que nous fournissons à Trendkite nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Trendkite
      Hotjar
      Nous faisons appel à Hotjar pour afficher des publicités numériques sur les sites pris en charge par Hotjar. Les publicités sont basées à la fois sur les données de Hotjar et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Hotjar a collectées sur vous. Les données que nous fournissons à Hotjar nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Hotjar
      6 Sense
      Nous faisons appel à 6 Sense pour afficher des publicités numériques sur les sites pris en charge par 6 Sense. Les publicités sont basées à la fois sur les données de 6 Sense et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que 6 Sense a collectées sur vous. Les données que nous fournissons à 6 Sense nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de 6 Sense
      Terminus
      Nous faisons appel à Terminus pour afficher des publicités numériques sur les sites pris en charge par Terminus. Les publicités sont basées à la fois sur les données de Terminus et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que Terminus a collectées sur vous. Les données que nous fournissons à Terminus nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de Terminus
      StackAdapt
      Nous faisons appel à StackAdapt pour afficher des publicités numériques sur les sites pris en charge par StackAdapt. Les publicités sont basées à la fois sur les données de StackAdapt et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que StackAdapt a collectées sur vous. Les données que nous fournissons à StackAdapt nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de StackAdapt
      The Trade Desk
      Nous faisons appel à The Trade Desk pour afficher des publicités numériques sur les sites pris en charge par The Trade Desk. Les publicités sont basées à la fois sur les données de The Trade Desk et sur les données comportementales que nous collectons lorsque vous naviguez sur nos sites. Il peut s'agir de pages visitées, de versions d'évaluation activées, de vidéos lues, d'achats, d'adresses IP ou d'ID d'appareil. Ces informations sont susceptibles d'être fusionnées envers des données que The Trade Desk a collectées sur vous. Les données que nous fournissons à The Trade Desk nous servent à personnaliser les publicités numériques afin de les rendre plus pertinentes. Politique de confidentialité de The Trade Desk
      RollWorks
      We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

      Voulez-vous améliorer votre expérience en ligne?

      Nous souhaitons vous offrir une expérience optimale. Si vous choisissez Oui pour les catégories présentées dans l'écran précédent, nous collecterons vos données et les utiliserons afin de personnaliser votre expérience et d'améliorer nos applications. Vous pouvez modifier vos paramètres à tout moment en accédant à notre Déclaration de confidentialité.

      Votre expérience. Votre choix.

      Nous respectons votre confidentialité. Les données que nous collectons nous aident à comprendre votre utilisation de nos produits, à identifier les informations susceptibles de vous intéresser, mais aussi à améliorer et à valoriser votre engagement envers Autodesk.

      Nous autorisez-vous à collecter et à utiliser vos données afin de personnaliser votre expérience ?

      Découvrez tous les avantages d'une expérience personnalisée. Vous pouvez gérer vos paramètres confidentialité pour ce site. Pour en savoir plus sur les options disponibles, consultez notre Déclaration de confidentialité.