Systems and methods for auditing assets

Patent metadata

Field	Value
Publication number	US-11932290-B2
Application number	US-202217816580-A
Country	US
Kind code	B2
Filing date	Aug 1, 2022
Priority date	Oct 16, 2019
Publication date	Mar 19, 2024
Grant date	Mar 19, 2024

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 system for identifying and auditing railroad assets, comprising:
a memory having a database storing a plurality of railroad data, engines, and models; and
a processor operably coupled to the memory and capable of executing machine-readable instructions to perform program steps, the program steps including:
a data collection engine configured to collect sensor data from a sensor disposed on a vehicle to generate a spatial model of a railroad environment;
a machine learning module configured to automatically identify railroad assets,
wherein the data collection engine instantiates the machine learning module to extract railroad assets from the sensor data, and
wherein the machine learning module is configured to compare the identified railroad assets to the database to audit the presence and location of railroad assets within the environment captured by the sensor.

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

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

5. The system of claim 4 , 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.

6. The system 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.

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

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

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

10. A system for auditing railroad assets, comprising:
a memory having a database storing a plurality of railroad data, engines, and models; and
a processor operably coupled to the memory and capable of executing machine-readable instructions to perform program steps, the program steps including:
a model modification engine configured to modify 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
a comparison engine configured to compare spatial model data from one or more spatial models to determine whether an anomaly exists.

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

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

14. The system of claim 10 , wherein the comparison engine is configured to compare data from a first spatial model generated at a time T 1 to data within a second spatial model generated at a time T 2 .

15. The system of claim 14 , wherein time T 2 is any time after time T 1 .

16. The system 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 system 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 system 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.

Assignees

• Bnsf Railway Co

Inventors

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

Classifications

• B61L23/042 Primary

  Track changes detection · CPC title

• B61L23/041

  Obstacle detection · CPC title

• B61L25/06 Primary

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

• G06N20/00

  Machine learning · CPC title

• B61K9/08 Primary

  Measuring installations for surveying permanent way · CPC title