System, server and data capture device for roadside asset tracking and maintenance monitoring

• US 10,346,691 B2
• Filed: 01/15/2016
• Issued: 07/09/2019
• Est. Priority Date: 01/16/2015
• Status: Active Grant

• Current Assignee: Norman Boyle
• Original Assignee: Norman Boyle
• Inventors: Boyle, Norman
• Primary Examiner(s): Saini, Amandeep
• Application Number:
  US15/543,318
• Publication Number:
  US 20180247137A1
• Time in Patent Office: 1,271 Days
• Field of Search: 382103
• CPC Class Codes: A01D 2101/00 Lawn-mowers
• CPC Class Codes: A01D 34/863 and for mowing around obstacles, e.g. posts, trees, fences or the like A01D34/866 takes precedence
• CPC Class Codes: A01D 43/00 Mowers combined with apparatus performing additional operations while mowing A01D37/00, A01D39/00, A01D41/00, take precedence
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 10/20 Administration of product repair or maintenance
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/62 Text, e.g. of license plates, overlay texts or captions on TV images
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal

Abstract

There is provided herein an apparatus and method for roadside asset tracking and maintenance monitoring having a mobile unit with data capture devices for capturing roadside asset imagery, global positioning system (GPS) receivers and data interfaces for communicating with an asset management server. As such, the apparatus may take roadside imagery for automated asset identification which may include utilising an asset type image recognition technique for automating the identification of the roadside assets.

Claims

1. A method for roadside asset tracking and maintenance monitoring, the method comprising:

periodically deploying a vehicle alongside a roadside section, the vehicle comprising a data capture device comprising;

an asset data capture device comprising forward and rearward facing cameras configured for capturing forward and rearward facing roadside asset image data from the perspective of the vehicle;

a global positioning system (GPS) receiver; and

a data interface for communicating with an asset management server, the server comprising an asset tracking register database;

receiving the roadside asset image data representing images taken of a plurality of roadside assets;

receiving location data from the GPS receiver representing the respective locations the roadside assets;

utilising an asset type image recognition technique for automating the identification of the roadside assets;

generating a map representation, representing the roadside section and the locations of the identified roadside assets along the roadside section, for displaying before and after maintenance comparison imagery utilising the image data received from the forward and rearward facing cameras;

comparing roadside asset data of the asset tracking register database to;

record newly identified roadside assets and their respective locations in the asset tracking register database; and

identify missing roadside assets.

2. The method as claimed in claim 1, wherein the asset type image recognition technique comprises an image recognition stage comprising edge shape detection.

3. The method as claimed in claim 2, wherein the edge shape detection comprises rotation invariance processing to allow for edge shape detection of skew roadsign assets.

4. The method as claimed in claim 3, wherein edge shape detection comprises comparison to reference shapes in a shape reference database.

5. The method as claimed in claim 1, wherein the image recognition comprises an image recognition stage comprising colour detection.

6. The method as claimed in claim 5, wherein the colour detection comprises colour juxtapose detection.

7. The method as claimed in claim 6, wherein colour detection comprises comparison to reference colours in a colour reference database.

8. The method as claimed in claim 1, wherein the image recognition comprises an image recognition stage comprising symbol detection.

9. The method as claimed in claim 8, wherein symbol detection comprises comparison to reference symbols in a symbol reference database.

10. The method as claimed in claim 8, wherein symbol detection comprises alphanumeric symbol detection.

11. The method as claimed in claim 8, wherein symbol detection comprises text recognition.

12. The method as claimed in claim 1, wherein the vehicle further comprises an asset proximity detector for detecting the proximity of roadside assets and wherein the asset data capture device is triggered by the asset proximity detector.

13. The method as claimed in claim 12, wherein the vehicle comprises a grass cutter unit and wherein the proximity detector is configured for detecting when the roadside asset is engaged by the grass cutter unit.

14. The method as claimed in claim 1, wherein the vehicle comprises a grass cutter unit and wherein the grass cutter unit is controllable to be moveable with respect to the vehicle and wherein the forward facing camera is configured to follow the movement of the grass cutter unit.

15. The method as claimed in claim 1, wherein the method further comprises image comparison for detecting roadside asset damage or degradation to identify assets requiring maintenance.

16. The method as claimed in claim 15, wherein the image comparison comprises colour comparison.

17. The method as claimed in claim 15, wherein the image comparison comprises shape comparison.

18. The method as claimed in claim 15, wherein the image comparison comprises colour detection.

19. The method as claimed in claim 15, wherein the image comparison comprises symbol comparison.