Systems and methods for auditing assets

Patent metadata

Field	Value
Publication number	US-12358541-B2
Application number	US-202418608683-A
Country	US
Kind code	B2
Filing date	Mar 18, 2024
Priority date	Oct 16, 2019
Publication date	Jul 15, 2025
Grant date	Jul 15, 2025

Abstract

In one embodiment, a method includes receiving first Light Detection and Ranging (LiDAR) data associated with a railroad environment, extracting an asset from the first LiDAR data associated with the railroad environment, and superimposing the asset into a spatial model. The method also includes receiving a field indication associated with a modification to the railroad environment and modifying the spatial model in response to receiving the field indication associated with the modification to the railroad environment. The method further includes receiving second LiDAR data associated with the railroad environment and comparing the second LiDAR data to the modified spatial model.

First claim

What is claimed is:

1. A method of identifying and auditing railroad assets, comprising:
storing, via a processor, a plurality of railroad data, engines, and models;
collecting, via a data collection engine, sensor data from a sensor disposed on a vehicle to generate a spatial model of a railroad environment;
automatically identifying railroad assets, via a machine learning module;
instantiating the machine learning module to extract railroad assets from the sensor data; and
comparing, via the machine learning module, the identified railroad assets with the plurality of railroad data to audit the presence and location of railroad assets within the environment captured by the sensor.

2. The method of claim 1 , wherein the sensor data includes one or more of LiDAR data, GPS data, a field indication, or an image.

3. The method of claim 1 , wherein the data collection engine is configured to generate the spatial model using LiDAR data, GPS data, one or more field indications, one or more images, one or more LiDAR point clouds.

4. The method of claim 1 , wherein the data collection engine is configured to collect one or more field indications from a user device.

5. The method of claim 1 , where in the data collection engine uses a Geographic Information System (GIS) or LiDAR visualization software to generate the spatial model of a railroad environment.

6. The method of claim 5 , wherein the GIS is configured to analyze spatial locations and organize layers of information into the spatial model using maps, two-dimensional (2D) scenes, or three-dimensional (3D) scenes.

7. The method of claim 1 , wherein the 2D scenes include orthographic imagery generated from LiDAR point cloud data.

8. The method of claim 1 , wherein the data collection engine is configured to superimpose one or more assets into the spatial model.

9. The method of claim 1 , wherein the railroad asset is data extracted from sensor data that represents a physical object.

10. A method of auditing railroad assets, comprising:
storing, via a processor, a plurality of railroad data, engines, and models;
modifying, via a model modification engine, a spatial model of a railroad environment including a railroad asset, captured by a sensor disposed on a vehicle, in response to one or more field indications, wherein the model modification engine is configured to model the spatial model in response to receiving a field indication that the railroad environment has or will be modified; and
comparing, via a comparison engine, spatial model data from one or more spatial models to determine whether an anomaly exists.

11. The method of claim 10 , wherein the field indication indicates that the railroad asset will be or has been moved from a first location to a second location within the railroad environment.

12. The method of claim 10 , wherein the field indication indicates that the railroad asset will be or has been removed from the railroad environment.

13. The method of claim 10 , wherein the field indication indicates that the railroad asset will be or has been added to the railroad environment.

14. The method of claim 10 , wherein the comparison engine is configured to compare data from a first spatial model generated at a time T1 to data within a second spatial model generated at a time T2.

15. The method of claim 14 , wherein time T2 is any time after time T1.

16. The method of claim 10 , wherein the comparison engine is configured to determine that a location of a first railroad asset within a first spatial model is different than a location of the first railroad asset within a second spatial model.

17. The method of claim 10 , wherein the comparison engine is configured to determine that a location of a first railroad asset within a first spatial model is not present within a second spatial model.

18. The method of claim 10 , wherein the comparison engine is configured to verify, based on the comparison of two or more spatial models, that the information within the compared two or more spatial models is the same.

19. The method of claim 10 , wherein the comparison engine determines that a location of an asset within first spatial model is different than a location of the asset within second spatial model.

20. The method of claim 19 , further comprising wherein the comparison engine determines that the asset within the first spatial model is not present within the second spatial model.

Assignees

• Bnsf Railway Co

Inventors

• Davis Philip Gerald
• Springer Ross Aaron
• Wagner Devin Scott
• Ford Jacob Scott

Classifications

• G06Q50/40

  Business processes related to the transportation industry (shipping G06Q10/083) · CPC title

• G01S17/89

  for mapping or imaging · CPC title

• G01S7/4808

  Evaluating distance, position or velocity data · CPC title

• B61L25/06 Primary

  Indicating or recording the setting of track apparatus, e.g. of points, of signals · CPC title

• B61L23/042 Primary

  Track changes detection · CPC title