## 9 Major Project Issues and Survey Results
### Procedure for Data Sharing, Delivery, Testing, Archiving, and Asset Recognition
#### 9.2.2 Phase 2: Delivery of Final Documents, Their Review/Testing, and Final Archiving
In fact, during the project, no problems were ever encountered in loading the point cloud with images on Cintoo(r). This was due to the fact that within the Reconstruct software, used to produce the final point cloud model, there is a function dedicated to exporting the model with images in a format compatible with the Cintoo platform. * The procedure used for validating image quality on the Cintoo platform proved to be inapplicable; despite the technology's quality of the platform, the data uploading to the cloud is very time-consuming. Consequently, it was found much more convenient to perform such verifications using the data navigation functions available in the free Reconstruct(r) project viewer, thereby restricting the cloud platform's use to only asset recognition activities. The costs related to uploading the entire Milan project to the cloud would have been prohibitively expensive. For this reason the data of the complexes were loaded into Cintoo only for the period strictly needed to run the asset recognition process. At the end of the operation, the data have been unloaded from Cintoo(r) to make room for the data of a new complex, thus drastically reducing the purchased server space. Ensuring the quality of the images was a very demanding task for the surveyors to guarantee, particularly due to problems of improper lighting of the photographed scene rather than excessive operator movement (Figures 34 and 35). Figure 34: An example of a blurry image. This defect happens when the on-demand 5K resolution image is taken with the capture head in movement. In a few isolated cases, when systematic image acquisitions of low quality were encountered in the survey of a building complex, it was requested by the tester to repeat the image acquisition. The most challenging issue to manage occurred when a survey revealed a discrete number of low quality images--high enough to cause problems for MM technicians in recognizing the assets but not numerous enough to justify a radical intervention, such as a complete resurvey of the entire complex. This issue was resolved empirically by performing photographic integrations where necessary, but it remains an open topic for potential future projects of this kind. More serious than the quality of the images, but easier to be corrected by a software reworking of the data, were the cases in which the survey trajectories were not joined correctly, thus not allowing the navigation of the model and generating overlaps between the three-dimensional models. In some cases, minor misalignments were found, which were nevertheless required to be corrected (Figure 36). Figure 36: An example where an incorrect alignment between trajectories resulted in an appreciable discrepancy between the walls of a building. Figure 35: If improper lighting is applied to the images, the results can be underexposed images. The work has been successfully completed, and all the data are stored in the servers of MM. Data can now be used to recognize and locate assets or to address a wide variety of building management needs.