Use cases
DIDYMOS-XR has 5 use cases for demonstrating the digital twin (DT) capture and creation methods in extended reality (XR) applications. In the context of the project these are referred to as 1) Digital twin creation, 2) Tourism, 3) City maintenance/inventory, 4) City planning, and 5) Industry. The XR applications are unique to each use case with a mix of virtual and augmented reality (VR and AR) being used as well as a mix of wearable, mobile, and desktop devices.
01
Digital Twin creation
The digital twin is created based on capture from cars equipped with cameras/drones and various sensors already available in the city. These sensors include traffic light sensors, weather sensors, daylight sensors, air quality sensors, and some cameras. Data from sensors available in the city enable the reconstruction of an accurate and up-to-date digital twin. This will be the set of data that is accessible to all the other XR applications.
GOAL:
- Creating the virtual environment (digital twin) from the sensors
- Checking the quality of the updates received from the sensors: the model can be imported to simulation software such as Carla in order to test the process of updating the digital twin.
- Finetuning the updating of the DT: geometry updates (capture update), mesh update (capture remains the same), sensor data updates (live updates to be fed into the XR applications)
Of all the use cases this is the most technical and the user will be strictly the backend developer of the DT.
02
Tourism
The use case exploits Virtual and Augmented Reality to offer different experiences to the user according to their location. The users of this application are tourists or tourism planners/guides.
VR will be used for remote experiences. The aim of the remote experience is to immerse the user in the life of the city. The user can explore the virtual city, checking when places are more crowded, when there is the most of the traffic, when is better to get public transportation, when it is better to go to out due to weather or pollution condition. The tourist can also check information about opening time of shops/museums and restaurants.
AR will be used for the on-site experience. With AR, the user will see augmented information on top of the real world. There will be two distinct experiences in Vilanova, Spain and Etteln, Germany.
03
City maintenance
In this use case, sensor updates are used to make prompt decisions to safeguard the welfare of the city. The users are city planners as well as residents of the city, though not all possible uses are equally valuable to both users.
Examples:
- Plant management: detecting plants that can be invasive or water intensive. Smart sensors in the city are able to automatically detect this information and will notify the city when action needs to be taken.
- Vandalism: sensible sites, detection of graffiti, detection of damage to public furniture
- Rubbish: rubbish to be collected – this is done using a sensor with the staff of the city receiving a notification when a bin is full for smarter collection
- Parking slot detection: out of all these examples, this is most relevant to residents who will be able to use the application for finding a parking place
04
City planning
In this use case the user can apply changes to the digital twin in order to run simulations of different scenarios in the city. The Twin will be imported into existing simulator software such as Carla or Omniverse. The user for this application would be a city planner.
Examples:
- changes to the configuration of city lights/traffic lights can be used to simulate different traffic scenarios
- Simulate how the increasing number of autonomous vehicles can affect parking and traffic light’s position and duration.
- Changing the configuration of the buildings (creating new ones, deleting old ones) to see how this affects the quality of the city (how traffic changes, how places can become more or less crowded).
05
Industry
This digital twin will be used to generate up-to-date maps needed by autonomous mobile robots to navigate manufacturing environments. The use case seeks to improve the capabilities of current digital twin capture techniques by adding a human in the loop. The user of this AR application is the worker acting as the human-in-the-loop. In this case, the user is provided with an AR mobile/wearable application with two main functionalities:
- Correct errors in the 3D scanning of the factory environment
The worker can scan parts of the factory environment and compare them with the digital twin (already created). If misalignments or errors (e.g., obstacles) are found the use can correct them. Also, the user can update the digital twin model by adding parts that were not scanned (e.g, hidden/covered places) - Add POI to the 3D scanning of the factory environment
The worker can scan parts of the factory environment and add Point of Interest (POI) manually. This POIs update the digital twin
