Visual data management system and method

1. A system configured for data communication, the system comprising:

one or more hardware processors configured by machine-readable instructions to: electronically receive a plurality of machine-readable sensor data of a physical facility having multiple 3D objects;

electronically process the plurality of machine-readable sensor data to output a machine-readable point cloud model including physically-based renders of said 3D objects with surface texturing, the point cloud model configured for augmented virtual navigation by a remote user platform in a virtual navigation space logically linked to the point cloud model;

electronically process the machine-readable point cloud model with a machine-readable convolutional neural network component to generate a machine-readable dynamic configuration database of geotagged-locations of the 3D objects with a set of configuration management suggestion metadata logically annotated to the 3D objects; and

electronically output visual and audio data to the remote user platform, including at least one of the 3D objects associated with at least one of said configuration management suggestion metadata linked to the at least one of the 3D objects in the virtual navigation space.

2. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically process the point cloud model with a neural network to output a set of most probable suggestions for augmented virtual navigation.

3. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically receive the plurality of machine-readable sensor data from multiple remote sensors.

4. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically receive the plurality of machine-readable sensor data from a crowdsourcing network.

5. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically process the configuration database to recognize historical change data over to a predetermined period of time of the 3D objects.

6. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically process the configuration database to recognize historical maintenance data over to a predetermined period of time of the 3D objects.

7. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically receive the plurality of machine-readable sensor data from a group of selected from one of a RFID, barcode, a serial number, a quick response code associated with the 3D objects.

8. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to process the machine-readable point cloud model to provide physically based rendering of the 3D objects.

9. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to process the machine-readable point cloud model wherein multiple remote user platforms are configured for augmented virtual navigation within the point cloud model.

10. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to process the machine-readable point cloud model wherein multiple remote user platforms are configured for simultaneous augmented virtual navigation within the point cloud model.

11. A system configured for data communication, the system comprising:

one or more hardware processors configured by machine-readable instructions to:

electronically receive a plurality of machine-readable sensor data of a physical facility having multiple 3D objects;

electronically process the plurality of machine-readable sensor data to output a machine-readable point cloud model including physically-based renders of said 3D objects with surface texturing, the point cloud model configured for augmented virtual navigation by a remote user in a virtual navigation space logically linked to said point cloud model;

electronically process the point cloud model with a machine-readable convolutional neural network to output a set of probable suggestions for augmented virtual navigation of the point cloud model by the remote user with a set of configuration management suggestion metadata electronically annotated to the 3D objects; and

electronically output visual data to the remote user including at least one of the 3D objects associated with at least one of said configuration management maintenance suggestion metadata linked to the at least one of the 3D objects in the virtual navigation space.

12. The system of claim 11 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically process machine-readable point cloud model to generate a machine-readable configuration database of geotagged-location of the 3D objects.

13. The system of claim 11 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically receive the plurality of machine-readable sensor data from multiple remote sensors.

14. The system of claim 11 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically receive the plurality of machine-readable sensor data from a crowdsourcing network.

15. The system of claim 11 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically process the configuration database to recognize historical change data over to a predetermined period of time of the 3D objects.

16. The system of claim 11 , wherein the one or more hardware processors are further configured by machine-readable instructions to electronically process the configuration database to recognize historical maintenance data over to a predetermined period of time of the 3D objects.

17. The system of claim 11 , wherein the one or more hardware processors are further configured by machine-readable instructions to store a database of a machine-readable history data of the remote user associated with the point cloud model augmented virtual navigation and processing the machine readable history data with the neural network to output the set of probable suggestions.

18. The system of claim 11 , wherein the one or more hardware processors are further configured by machine-readable instructions to process the machine-readable point cloud model to provide physically based rendering of the 3D objects for texturing.

19. A system configured for data communication, the system comprising:

one or more hardware processors configured by machine-readable instructions to:

electronically receive a machine-readable point cloud model generated from a plurality of machine-readable sensor data of a physical facility having multiple 3D objects;

the machine-readable point cloud model including physically-based renders of said 3D objects with surface texturing, the point cloud model being configured for augmented virtual navigation by a remote user platform in a virtual navigation space logically linked to said point cloud model;

electronically process the machine-readable point cloud model with a machine-readable convolutional neural network component to generate a machine-readable dynamic configuration database of geotagged-locations of the 3D objects with a set of configuration management suggestion maintenance metadata electronically annotated to the 3D objects; and

electronically output visual and audio data to the remote user platform including at least one of the 3D objects associated with at least one of said configuration management maintenance suggestion metadata linked to the at least one of the 3D objects in the virtual navigation space.

20. The system of claim 19 , wherein the one or more hardware processors are further configured by machine-readable instructions to process the machine-readable point cloud model wherein multiple remote users can access the point cloud model simultaneously.