## 3 Results
This module is important for making VT navigation more intuitive, preventing unwanted changes in the direction of observation when moving from one location to another. This also provides users with a compass and the orientation of the image in relation to the geographical north. (5) Lag prevention: The VT works with two panorama layers of 128 tiles--low and high resolution. This is to optimise loading and prevent lagging during navigation. The panorama is rarely, if ever, reconstructed in full. When a user loads a new panorama, their browser initially requests the blurred (lighter) version of the entire panorama, which loads much faster. Only the sharper tiles included in the user's viewing frame are loaded shortly after. This process is completed with the JavaScript library PhotoSphereViewer [71], which takes care of displaying the panorama. It places the tiles in the right position and updates them in real time as the user browses the site. (6) Access security: Images are stored and accessed by the tour server behind an authentication protocol. This allows for control of access at several levels, granting different users varying rights. For example, it permits accredited members of the public to navigate exteriors and public spaces, specialised scientists to access any room, and researchers dealing with confidential data to access real-time information. Upon accessing the tour, a login interface is prompted, and certain areas of the tour may or may not be accessible based on the user's credentials. Step 5: Integration of IoT (see Figure 3--'polygon' positioning). This step involves creating a reference geometry (typically a polygon or boundary representation) superimposed on a visible object within the VT. For example, the silhouette of a temperature sensor. Once defined, the polygon becomes a georeferenced object within the VT, enabling connection with other objects in a database. In the example, when an accredited user clicks on the temperature polygon, a graphic displaying the history of stored temperatures is prompted (see Figure 4). While adding new polygons may be time-consuming, the fact that they are geolocalised objects assures their correct position independent from image versioning. Figure 3: Workflow for VT construction and definition of database-linked elements. highlighted in the viewing zone, while other objects (i.e., the architecture or MEP models) can be added and filtered by the user (data tree on the left-side column and geometries in grey on the viewing zone). Additional properties related to the object (Room 2) are also available (right-side column). Step 7: Scalability. The technical solution is currently implemented in other buildings in the district. For further details and evaluation of this process, please see the next section. Figure 7 shows the VT interface, using the orthophoto tool, to illustrate the current and future intervention spaces for escalating the solution. The spaces highlighted in this article are shown in green. In red are the 26 spaces under implementation (results expected in November 2024). The large yellow dot represents the future Smart Living Lab Building, which is the ultimate implementation target of this research. Figure 5: Example of _‘Room 2’_ in the VT connecting to BIMs. Figure 6: Example of _‘Room 2’_ in the BIMs’ CDE platform [47].