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Monitoring Railway Infrastructure Sites Through BIM and GIS

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说明

Due to their nature, rail infrastructure projects greatly benefit from the adoption of workflows based on intelligent models and point clouds to allow off-site analyses without the need of the physical presence on the field. FSTechnology, a division of the Italian Railways, set up this workflow based on an integration of Autodesk software—including Autodesk Construction Cloud, Revit software, and Civil 3D software—with Esri ArcGIS GeoBIM. We combined CAD, building information modeling (BIM), point clouds, and orthophotos with geographic information system (GIS) and game engine technologies and added the construction program in a browser-based 4D solution with issue tracking. This is not only intended to monitor the progress of the physical works being executed, but also to achieve better control during the maintenance phase of the railways. All these combined and advanced technologies help us to monitor the most-critical infrastructures like viaducts and bridges, and factors of environmental interest and relevance, supported by artificial intelligence.

主要学习内容

  • Learn about combining CAD, BIM, and point clouds with GIS and game engine tech in a browser-based 4D solution with issues tracking.
  • Learn about integrating different platforms to achieve better control during the maintenance phase of the railway sites.
  • Learn about automating processes to reduce human error, time, and costs.
  • Learn about monitoring the most critical infrastructure and factors of environmental interest and relevance supported by AI.

讲师

  • STEFANO LIBIANCHI 的头像
    STEFANO LIBIANCHI
    Stefano Libianchi is a BIM Expert in FSTechnology a company belonging to the Italian State Railways Group Ferrovie dello Stato Italiano. He participates in the researching of new technologies and innovating workflows with BIM and GIS. He worked in the department of strategy, Innovation and System in Italferr. He worked as Freelance BIM Technical Consultant with Autodesk from 2015 to 2018. During this years Stefano acquired experience in BIM management and delivery methods working as BIM Coordinator in the Red Line North Underground's project in Doha. Before the Doha project he worked as Architect in different projects.
  • CATELLO CASCONE
    Catello Cascone is a GIS Specialist in FSTechnology a company belonging to the Italian railways Group Ferrovie dello Stato Italiano. He partecipates in different project using ESRI suite and innovating workflows with BIM and GIS. He worked as GIS specialist with Esri Italy from 2018 to 2022.
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Transcript

STEFANO LIBIANCHI: Hi, everyone. It's a pleasure to present this class with my colleague Catello Cascone. I'm Stefano Libianchi, beam expert in FSTechnology. And in this class, we are going to explain how our workflow can improve the monitoring of railway infrastructure site through BIM and GIS.

Here is the agenda for the presentation. Just a few words about us, then we start to describe the workflow and see the use case, after show the outputs and the conclusions. And, now, a brief introduction of our company and our team. FSTechnology is the high tech company of the Ferrovie dello Stato Italiane group.

It was created at the beginning of 2019. And its goal is to strengthen and support digital innovation among the company of the group. The BIM and GIM Competence Center is a team within FSTechnology. Considering the core processes of the group, we mainly support linear infrastructure projects. And, therefore, we support Italferr, which is the engineering company of the Ferrovie dello Stato Italiano group, during the design and the construction stage from conceptual design to handover.

We also support Rete Ferroviara Italiana, the company owner of the entire railway network. And here in this slide, we can see our team. The main objective of our team is to research and implement new technologies to improve the processes and the workflow for the management of the entire life cycle of infrastructure projects.

Our first class was presented by Marcella Faraone and me in 2018. And since then, our group started to investigate how to better integrate BIM NGIS with other platforms and implement a solution for remote site monitoring. This year, in addition to this class, we are going to present a second one, how to avoid wasting water and energy with the help of BIM NGIS.

Before describing the workflow, I would like to explain the reasons why it was designed. Ferrovie dello Stato Italiane group is the leading energy consumer in Italy with a slice of around 6% of national demand. And, therefore, an investment of 1.6 billion euro will be allocated to plants installation to self-produce energy, amounting to 40% of the overall consumption of the group to be achieved by 2027.

After this date, we will continue with the reduction. The FS group believes that an organization long term success is built on a strategy that prioritizes the protection of natural balances. The FS group's greatest contribution to the creation of an environmentally-sustainable development model is that it offers increasing more efficient and sustainable transport services that maximize the benefits of collective mobility.

The workflow aligns to the objective of FS group, incorporate the protection of the environment into its strategies and priorities by promoting and implementing a more rational use of resources, the use of renewable energy sources, and the prevention of reduction of environmental risks with the aim of gradually reducing the group carbon footprint. To be able to do this, we developed different workflows that respond to specific needs but originate from the same data, which, as we see, are centrally stored on Autodesk Construction Cloud platform.

It is important to highlight the added value and relevance of standardizing and automating of processes with the help of the leading edge technologies. This is the focus of our work, set up a workflow with a continuous fine tuning depending on the outcomes achieved from the tests. So we set up this workflow based on an integration of Autodesk software like Autodesk Construction Cloud, Revit, Navisworks, and Civil 3D with Esri, ArcGIS, and GeoBIM to actively support the monitoring of the environmental impacts.

It all starts with a survey. The data is saved on Autodesk Construction Cloud and [INAUDIBLE] we would notice the central role of the [INAUDIBLE] environment is CC. From the CC, the data is read to open the linear design with Civil 3D and the design of functional element for Revit but also to create collaboration with Esri, ArcGIS. The data prepared on Esri, ArcGIS is used to create useful checklists in workflow for both maintenance and construction works on site.

Also, I like the central role of the external database in which we stored all the valuable information coming from the model and the data retrieved in the field with the checklist. The data from the checklist, therefore, use it to complete the modeling with the information taken from the sites. And in the case of water design, we create an automaton with Dynamo and Civil 3D that adds information to specific assets, for example, on the pipes.

This part of the workflow was presented last year in Autodesk University. And we prepared an automatic procedure to assess, estimate the physical progress of the works inside the construction site using the survey deliverables and an ad hoc simplified model that represent the progress of the work using Navisworks. This reaches the data with further information that we will need in the future. It is also overlaid, can be viewed and analyzed through ArcGIS Pro webmap or inside GeoBIM.

And on the field with the issue workflow in SEC, show the nullity for safety purposes or use it with augmented reality and virtual reality in the field. The use of artificial intelligence can complete the data of the dashboards as well as IoT with TANDEM.

We focused our energies on the possibility to reduce time on construction site management activities. We will explain where we started and what we have achieved so far. In July in 1996, the European Commission adopted a resolution to implement the Trans-European Transport Network.

The intent of this multi-phased project is to provide coordinated improvements to primary roads, railways, inland waterways, airports, and traffic management systems through the Europe. When complete the Scandinavia Mediterranean corridor of this project will stretch from Helsinki, Filandia, to Valletta, Malta, and the Napoli-Bari high-speed railway project is part of this corridor and start in 2015.

Now, let's explain the workflow in more detail. The starting point of our workflow is the survey but from drone and ground. This short video shows the main construction site area of the works on [INAUDIBLE] Frasso Telesino Railway. We regularly surveyed the site roughly every two months to monitor the construction works, including two viaducts, [INAUDIBLE] system, and tunnel.

And all project file are shared and stood on Autodesk Construction Cloud within folder structure that reflects the work breakdown structure of the project. At the top level, there is the project phase, for example, design phase, construction phase, and main disciplines, civil works, technologies, environment. The main overview, WBS elements, viaducts, tunnels, retaining walls at a lower energy level. We also find the surveys organized by survey date. And at an even lower level, we have the output listed by type or format. And now Catello will continue with the explain of the workflow.

CATELLO CASCONE: Once all the project file are connected, we can reach the scene with all the available base data taken from the different source. This is an example of the data.

The data related to the diagnostic investigation are stored on a group owner portal named Sigmap. Sigmap is a site made up by a DB and a GIS application.

In this specific case, the GIS is a web map that displays the input data provided by the DB part. By accessing the Sigmap, we can have three types of user, owner, same player, who enters the result of the monitoring activities performed on site or organization from the validated environmental monitoring work. By accessing the Sigmap through the username and password, we only have access to specific section according to the user type.

Let's have a look in detail. By looking in, for example, to sigma co-monitoring, with my user, I can only see the project I have access to. And by selecting Cancello Frasso, I can see the atmospheric components granted by the permission of setting.

If I choose groundwater, I can see the master data sheets over the sites being monitored or enter new ones. Each master file provided the general site's data and associated measures, which are under a validated flow between the owner and the supplier. In addition of this information, documents and images useful for monitoring the sites can be stored.

Accessing the GIS selection is [? standard. ?] Once in the project I am interested, I will have this type of visualization. Data subject to environmental monitoring, such as roads sites, area, and the road access are referenced on a base map. Zoom in in the site interest.

This site offers design, the interest possibility of insert external data, such as the data made available by ArcGIS or to be able to verify the design against environmental constraints or personal data in KML or shape format. To be able to compare them with this publisher, it's possible to change the cartographic background by selecting the satellite view to view the accuracy of the placement of the monitoring points in the countrysides.

If there are comments to share, we developed a [INAUDIBLE] with the widget to allows the user to comment on the map using a markup tool and text boxes. Once the comments has been added, it can be downloaded locally in the JSON format and sent to the supplier or to a colleague who will be able to reupload and view the comments back in the browser based application using the same widget.

The environmental and archaeological constraints, sensor data come from the Eva portal. In this portal we can see all the archaeological discoveries near the railway project. For example, here we have the area with the high potential archaeological risk in red.

We have a database containing all the information classified by type of archaeological finds. [INAUDIBLE] designs must take into account the classification of a potential archaeological risk in the area of interest. Now we are showing an example of a natural asset, preservation validated with the environmental inspection during a construction. We analyzed the [INAUDIBLE] of the environmental system to verify whether the natural asset were preserved and ensure to project of our landscape heritage.

Using the ArcGIS Pro, we can georeference the asset. Let's see how once the vegetation present in the area of interest has been referenced and classified, we obtain a map of the vegetation near the construction site. On the left, we have the 2D map with the classified point elements, while on the right the 3D scene. In the 3D scene, you can see how the data has been given a realistic symbol, which allows the territorial reality to be digitally reproduced.

From the BIM model, the starting point is the BIM Cloud Connection Connector that combines the data suite and the Esri suite. We have the possibility to upload on the map the most up data version of the BIM model of interest available on Construction Cloud directly into ArcGIS Pro. Once the model is placed on the map, we can navigate it. Select it to turn on and off the layers.

This allow us to see the model as a whole or look at specific elements in more details. We can then explore the spatial context by adding layers to the map. We change the base map, selecting the most suitable among those available in the catalog. In this case, we decided to use the satellite map. Once again, we add the layers to the scene to visualize the model within the spatial context with the build and the natural environment.

We added to the scene a reconstruction of a building, the curve of the construction site and the area of construction site, the tracks and the location. From DTM, we have developed a workflow which allows us to have a very high definition of accuracy. Starting from the same point cloud, we classified it by adding material information to tell concrete from steel, timber, as well as ground from the vegetation.

The first workflow we created is used to calculate, cut, and fill earthworks volumes. And first step of this workflow is about the necessary data of the processing that we will that we will then use in Civil 3D for an automatic calculation of cut and fill volumes. To have a usable result and limit processing times, we had to decimate the input data by using the tool that reduce the density of the point cloud, preserving the geometry as well as possible.

Therefore, in Civil 3D, we import the dams generated from Python scripts loading and the reference surveys generated from the most recent survey. Next, we load the surface of the same area and survey that the previous time-- specifically, the surface to be compared must be named the same plus a suffix indicating the survey, T1 or T2, for example.

Running the Dynamo script, it's detected the dams and in Civil 3D files lists all the surfaces, sorting and pairing of them by name. The script created the volumetric surface from the period dam surface. The data extraction process catches the name of the surface to compose the name of the process volumetric surface so that I will get the same name as the control once and get both the name in the survey comparing a suffix [ITALIAN].

We, therefore, use the solution for semi-automatic volume calculation. We have the possibility to using ArcGIS Pro to get the output for Civil 3D through the dam processing script from the point cloud and the ship pilot to calculate excavation and filling. This help us to make our digital workspace as realistic as possible, allowing us to create a dimension where we can carry out different types of analysis.

Another type of information that we use for our analysis are the building in the area of interest. We use our CT engine software from the Azure suite. We have the possibility to select the quality of our final product and identify the area of interest.

Here, for example, we are selecting Las Vegas. We can identify what to acquire. Here, we select buildings and roads. The result is a base map of the area with the selected data in 3D format. Then we can use a texture to make the buildings look more realistic. Data can be routed or moved. We select those relevant to us, and we can export them to then load them into the GeoBIM web platform, which brings together [INAUDIBLE] works.

The cadastral data are another set of information that we used. From the internal database, we can view, identify, and acquire the plot of land owned by the Ferrovia Group. Then we can use the national database to acquire the cadastral limits of the data plots. The result is an overlay of cadastral information that allows us to have a total picture of the area of interest, identifying which lands can be immediately incorporated with the construction site and which cannot.

We reach our BIM model with more information. Here, for example, we added the information from the construction program. Using the joint tool identifying the right case, we added the time information of start and end of construction on the specific section of the model. Let's see additional dates on the piers then on the bridge deck or on the pier cap.

We can then use the time feature of ArcGIS Pro to view the model according to the datas defined on the time schedule. We see that, in fact, the portion of the model not yet building is not displayed in the scene. Reactivate the navigation of the underground model. We can see by portion of the model, that this is covered by the ground. In particular, here we see the support of fields and planes.

By activating the time slider, we can see the different stages of construction on the BIM model. We have first the visualization of fields then of the planes. Analyzing at the scene with the ground, then we can see the effect of the time filter for the entire work. We can also compare the point cloud acquired on the site with the BIM model to analyze the progress of the construction site in relation to the time schedule.

We then move to the publication of our content. We decided to create the application with the GeoBIM and the shared data for analysis. We published the model containing the time schedule using the following workflow. BIM filed to the geodatabase, make building layer, and, finally, create building scene layer content that allow us to view the model on the Esri online platform.

Once we have acquired the data of interest for the area under examination, we can import them all into a single scene and proceeded with our analysis. We use GeoBIM where we see a 3D scene with the dwellings, ground beam model of the viaduct, and the classified vegetation also referenced. We can also activate it on the ground navigation to see the viaduct in its entirety.

We have identified the viaduct construction site area in orange and the area near the tracks in white. The point cloud has been uploaded. We have added some markers to our scene that lead back to diagnostic investigation portal. We can use them for monitoring the surface and the water example of data got from a pitometer.

This information on the presence of historical aqueduct was acquired from the Eva portal. By integrating the information retrieved from this portal, we can monitor and therefore better preserve the archaeological asset, such as ancient Roman roads and/or aqueducts close to the tracks. With the land register data, we can identify the best area to plan the installation of photovoltaic plants close to the track. With the land register data added, we can also use the shadows tool to perform shading the analysis, identify the most efficient location and orientation of the photovoltaic panels.

Here we see the use of the tool with the time slot as a variable and the shadows in red. By using all this data together in a 3D scene, we can make analysis and obtain results that help us to our choice. Here, however, the map contained in the GeoBIM web application-- browsing the map and zooming in on our construction site, we can observe the functionality of the time slider.

With a simple preview, we can see the work appearing according to the information we got from the construction program. We then use the layer list to show how high the portion of the model or show the entire model, just as we did earlier with the desktop application. We also have a dynamic legend that show us what is displayed on the map.

With a click, we switch from a 2D visualization to a 3D one. We can then navigate to the scene and see in transparency even the portion of the model placed below the ground level. GeoBIM offer for new tools, the ability to navigate the scene at a different time, the ability to choose the view whether we prefer, the calculation of the shadows, and the calculation on the viewing accounts.

Thanks to publication as a building layer, we can use the 3D Explorer tool to see the BIM model and the information it contains, just like the desktop tool. Among other applications that can be used at the 3D scene, we have the issue tool. Here, for example, we see in white the client's area of the tracks, which indicates the safety distance to be respected during the passage of trains. It's overlapping with the construction site boundaries in orange.

Using this tool, we can fill out a form with the user full information, name of issue, status, type, causes, and description.

Once sent, we can see it in the documents in the application and review the summary table. We can view in a BIM 360 the created issues. We are seeing in a start and target data to the resolve the issue and the user who has to manage it. Finally, we publish it. As you can see in the list of activities, there is the list of activities issues with the uploaded information.

Using GeoBIM we also have the possibility to select or to select the information visible in the scene. Let's select, for example, the layer of activity construction site. We can see at the same time the feature and the [INAUDIBLE] containing the design of the construction site. We then reach the application with the point cloud representing the physical progress of the work. We can then overlay the BIM model and the point cloud inside the build and the natural environment.

STEFANO LIBIANCHI: Thanks to Catello, we have seen some of the possible analysis using ArcGIS and GeoBIM. Now let's see the other results that we can obtain with the other workflows. The first output that we quickly show, we got by combining the project data and the artificial intelligence analysis, the orthophoto taken on site.

In this video, we can see the elements identified for a given survey, for example, plants, tracks, structural peels, and that by choosing an element, in this case, tank. The dashboard updates to show all the AI images where this object was recognized using the algorithm.

With the use of Unity, a cross-platform game engine, and ArcGIS SDK for Unity, we managed to integrate GIS data and BIM models. Resulting is a solution very simple to navigate and enjoyable by all known BIM experts. And what you see in this video is a simulation of some potentially dangerous situation while moving inside a building and in the construction site. Another output that we are going to describe is augmented reality. And as we can see in the video, it is possible to exchange information remotely or open the documentation needed to carry out the checks of various kinds.

One step forward we are taking is approaching the digital twin. We are studying how to use TANDEM and the potential. We are currently testing it to integrate the information coming from an IoT sensor and field service information to have an overall view of the data. In the future, we hope to be able to forecast and anticipate problems before they arise.

Here we are looking at how we can put together the data collected through 3D scene of ArcGIS Enterprise. We are able to have a territorial context enriched with data such as a building, roads, vegetation, and navigate the scene even on the ground to compare the differences with our model with the context. Now, the output is this dashboards built with an Esri application of ArcGIS enterprise.

In this video, we are looking at an example that shows the construction data of some sites. The dashboard is made up of various interactive parts that allow the user to query data for different purposes. In the lower section, also, there are graphs that allow the user to see the consumption trend of the sites.

In conclusion, let's go back to the strategies seen before and show how we can intervene with our workflow. Naturally, to solve the protection of environment and water reduction, we use artificial intelligence and TANDEM to have an overall view of the information.

While we use GeoBIM, as [INAUDIBLE] does-- for example, to position the photovoltaic panels in the best areas and the augmented reality and virtual reality to reach dangerous area-- moreover, we can say that with our workflow using an integration oriented approach, it's possible to achieve many benefits, work in common environment, integrate platform, use integrated methodology to have fewer errors, and use Digital Twin and utility network tool. Thank you. And I hope you enjoy the presentation and our work. Thank you for the watching.

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我们通过 Wistia 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Wistia 隐私政策
Tealium
我们通过 Tealium 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Tealium 隐私政策
Upsellit
我们通过 Upsellit 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Upsellit 隐私政策
CJ Affiliates
我们通过 CJ Affiliates 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. CJ Affiliates 隐私政策
Commission Factory
我们通过 Commission Factory 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Commission Factory 隐私政策
Google Analytics (Strictly Necessary)
我们通过 Google Analytics (Strictly Necessary) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Strictly Necessary) 隐私政策
Typepad Stats
我们通过 Typepad Stats 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Typepad Stats 隐私政策
Geo Targetly
我们使用 Geo Targetly 将网站访问者引导至最合适的网页并/或根据他们的位置提供量身定制的内容。 Geo Targetly 使用网站访问者的 IP 地址确定访问者设备的大致位置。 这有助于确保访问者以其(最有可能的)本地语言浏览内容。Geo Targetly 隐私政策
SpeedCurve
我们使用 SpeedCurve 来监控和衡量您的网站体验的性能,具体因素为网页加载时间以及后续元素(如图像、脚本和文本)的响应能力。SpeedCurve 隐私政策
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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改善您的体验 – 使我们能够为您展示与您相关的内容

Google Optimize
我们通过 Google Optimize 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Google Optimize 隐私政策
ClickTale
我们通过 ClickTale 更好地了解您可能会在站点的哪些方面遇到困难。我们通过会话记录来帮助了解您与站点的交互方式,包括页面上的各种元素。将隐藏可能会识别个人身份的信息,而不会收集此信息。. ClickTale 隐私政策
OneSignal
我们通过 OneSignal 在 OneSignal 提供支持的站点上投放数字广告。根据 OneSignal 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 OneSignal 收集的与您相关的数据相整合。我们利用发送给 OneSignal 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. OneSignal 隐私政策
Optimizely
我们通过 Optimizely 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Optimizely 隐私政策
Amplitude
我们通过 Amplitude 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Amplitude 隐私政策
Snowplow
我们通过 Snowplow 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Snowplow 隐私政策
UserVoice
我们通过 UserVoice 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. UserVoice 隐私政策
Clearbit
Clearbit 允许实时数据扩充,为客户提供个性化且相关的体验。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。Clearbit 隐私政策
YouTube
YouTube 是一个视频共享平台,允许用户在我们的网站上查看和共享嵌入视频。YouTube 提供关于视频性能的观看指标。 YouTube 隐私政策

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定制您的广告 – 允许我们为您提供针对性的广告

Adobe Analytics
我们通过 Adobe Analytics 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Adobe Analytics 隐私政策
Google Analytics (Web Analytics)
我们通过 Google Analytics (Web Analytics) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Web Analytics) 隐私政策
AdWords
我们通过 AdWords 在 AdWords 提供支持的站点上投放数字广告。根据 AdWords 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AdWords 收集的与您相关的数据相整合。我们利用发送给 AdWords 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AdWords 隐私政策
Marketo
我们通过 Marketo 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。我们可能会将此数据与从其他信息源收集的数据相整合,以根据高级分析处理方法向您提供改进的销售体验或客户服务体验以及更相关的内容。. Marketo 隐私政策
Doubleclick
我们通过 Doubleclick 在 Doubleclick 提供支持的站点上投放数字广告。根据 Doubleclick 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Doubleclick 收集的与您相关的数据相整合。我们利用发送给 Doubleclick 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Doubleclick 隐私政策
HubSpot
我们通过 HubSpot 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。. HubSpot 隐私政策
Twitter
我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
Facebook
我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
LinkedIn
我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
Yahoo! Japan
我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
Naver
我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
Quantcast
我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
Call Tracking
我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
Wunderkind
我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
ADC Media
我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
AgrantSEM
我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
Bidtellect
我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
Bing
我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
G2Crowd
我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
NMPI Display
我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
VK
我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
Adobe Target
我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
Google Analytics (Advertising)
我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
Trendkite
我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
Hotjar
我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
6 Sense
我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
Terminus
我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
StackAdapt
我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
The Trade Desk
我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
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

是否确定要简化联机体验?

我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

个性化您的体验,选择由您来做。

我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。