Improve Your Business Performance with Digital Twin and GIS

A physical environment or asset is represented in the digital world as a digital twin. However, today, a digital twin does not only mean a three-dimensional visualization, but it is also an operation and decision support infrastructure that accelerates decision-making processes. If this structure is used together with GIS (Geographic Information Systems), institutions can both analyze data based on location and make their assets more trackable, measurable, and manageable.

Using up-to-date data is especially important in infrastructure, industrial facilities, large-scale field operations, and city management. Because in many organizations, decisions are still made using outdated field data. Instead of transferring data coming from the field to a digital environment, with the digital twin approach, 2D GIS layers, 3D models, reports, and analysis dashboards can be viewed in the same environment. Thus, faster and more accurate decisions can be made in processes such as maintenance, investment, planning, and field management.

Aerial view of city with digital twin models

Why is data so important in digital twin projects?

The value of a digital twin is determined not only by the quality of the model but also by the up-to-dateness and accuracy of the data provided by the model. In this area, information taken from sources such as panoramic images, sensor data, and corporate databases can be analyzed in real-time or near real-time using LiDAR. Institutions can ensure that their assets are tracked not only as "marked points on a map" but also with their field equivalents and details.

At this point, GIS improves the spatial intelligence of the digital twin. The GIS infrastructure has the ability to query the location of assets, which region they serve, their proximity to risk areas, their maintenance history, and their performance. It is the digital twin that makes this spatial data more understandable and functional in a 3D environment.

Digital wireframes over street assets like bus stops and trees

Objexa: AI-supported inventory strategy for digital twin

One of the most time-consuming issues in digital twin and GIS is creating an up-to-date inventory of field assets and keeping it constantly up-to-date. Therefore, artificial intelligence-based object recognition systems are now required to accelerate inventory production.

Objexa aims to analyze field assets more quickly through object recognition and classification using image data. Therefore, AI-supported automation can make inventory processes better than manual controls.

ObjexaLens provides a free trial for object recognition from photos.

Our ObjexaLens product, which we developed for this purpose, provides a test environment where institutions and users can test the system's object recognition capabilities for free. ObjexaLens has the ability to find objects in photos by analyzing photos uploaded via web-based, mobile, or API. This allows organizations to do a quick preliminary evaluation (POC) for their own use cases and test the integration potential.

For example, a user can see identified objects by uploading a photo taken in the field to their mobile device.

Person taking picture of a street scene with object recognition bounding boxes

Corporately, API integration can automate this process and make it compatible with existing systems. This method especially accelerates requirements such as field control, reporting, and inventory management.

To examine and try ObjexaLens for free: Objexa

Which sectors does it appeal to?

GIS, digital twin, and artificial intelligence-based object recognition provide direct benefits to many sectors:

  • Smart cities and municipalities: asset management, maintenance planning, field control
  • Transportation: Field observations and updates, inventory analysis
  • Industry and facility management: Online management of campus or facility assets
  • Disaster and risk management: seeing and evaluating important assets

Data is transformed into action by the digital twin.

Thanks to digital twin technologies that combine data coming from the field on a single platform, companies can make faster, more measurable, and more accurate decisions. Artificial intelligence-based object recognition solutions increase the spatial analysis capability of GIS while accelerating inventory processes. ObjexaLens helps institutions start this change quickly by offering an environment within the Objexa ecosystem where you can test object recognition capabilities from photos for free.

If you want to create a roadmap based on GIS and object recognition, create a digital twin for your institution, or evaluate ObjexaLens according to your use case, you can contact us.

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