Handling of predictive models based on asset location

• US 10,510,006 B2
• Filed: 03/09/2016
• Issued: 12/17/2019
• Est. Priority Date: 03/09/2016
• Status: Active Grant

• Current Assignee: Uptake Technologies, Inc.
• Original Assignee: Uptake Technologies, Inc.
• Inventors: McElhinney, Adam, Boueri, John, Stacey, Timothy
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US15/064,878
• Publication Number:
  US 20170262756A1
• Time in Patent Office: 1,378 Days
• CPC Class Codes: G01M 99/008 by doing functionality tests
• CPC Class Codes: G05B 23/021 adopting a different treatment of each operating region or a different mode of the monitored system, e.g. transient modes; different operating configurations of monitored system
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/0082 for monitoring traffic from a ground station radar or analogous systems specially adapted for traffic control G01S13/91
• CPC Class Codes: G08G 9/00 Traffic control systems for craft where the kind of craft is irrelevant or unspecified

Abstract

Disclosed herein is a computer architecture and software that is configured to modify handling of predictive models by an asset-monitoring system based on a location of an asset. In accordance with example embodiments, the asset-monitoring system may maintain data indicative of a location of interest that represents a location in which operating data from assets should be disregarded. The asset-monitoring system may determine whether an asset is within the location of interest. If so, the asset-monitoring system may disregard operating data for the asset when handling a predictive model related to the operation of the asset.

Claims

1. A computing system comprising:

at least one processor;

a non-transitory computer-readable medium; and

program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to;

receive, for each of a plurality of assets, position data;

determine that given position data for a given asset of the plurality of assets matches a location associated with unreliable operating data;

in response to the determination, decide to disregard operating data for the given asset when handling a predictive model related to the operation of the plurality of assets; and

handle the predictive model in accordance with the decision.

2. The computing system of claim 1, further comprising program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to:

receive, for each of the plurality of assets, operating data corresponding to the position data.

3. The computing system of claim 2, wherein the program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to handle the predictive model in accordance with the decision comprise program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to define the predictive model based on a set of received operating data for the plurality of assets that excludes the operating data corresponding to the given position data for the given asset.

4. The computing system of claim 2, wherein the predictive model is previously defined by the computing system, and wherein the program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to handle the predictive model in accordance with the decision comprise program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to modify the predictive model based on a set of received operating data for the plurality of assets that excludes the operating data corresponding to the given position data for the given asset.

5. The computing system of claim 1, wherein the program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to handle the predictive model in accordance with the decision comprise program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to forgo execution of the predictive model for the given asset.

6. The computing system of claim 1, wherein the location associated with unreliable operating data is a first location, and wherein the computing system further comprises program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to:

before the determination, define one or more locations associated with unreliable operating data, wherein the one or more locations comprise the first location.

7. The computing system of claim 6, wherein the program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to define the one or more locations comprise program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to define the one or more locations based at least on historical position data for one or more of the plurality of assets.

8. The computing system of claim 1, wherein the program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to determine that the given position data for the given asset of the plurality of assets matches the location associated with unreliable operating data comprise program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to determine that the given position data corresponds to a position that is within a threshold distance of the location associated with unreliable operating data.

9. The computing system of claim 1, further comprising program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to:

before the determination, cause a computing device to output an indication of an abnormal condition when operating data for the given asset satisfies particular criteria; and

in response to the determination, forgo causing the computing device to output the indication of the abnormal condition when operating data for the given asset satisfies the particular criteria.

10. A non-transitory computer-readable medium having instructions stored thereon that are executable to cause a computing system to:

receive, for each of a plurality of assets, position data;

determine that given position data for a given asset of the plurality of assets matches a location associated with unreliable operating data;

in response to the determination, decide to disregard operating data for the given asset when handling a predictive model related to the operation of the plurality of assets; and

handle the predictive model in accordance with the decision.

11. The non-transitory computer-readable medium of claim 10, further comprising instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to:

receive, for each of the plurality of assets, operating data corresponding to the position data.

12. The non-transitory computer-readable medium of claim 11, wherein the instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to handle the predictive model in accordance with the decision comprise instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to define the predictive model based on a set of received operating data for the plurality of assets that excludes the operating data corresponding to the given position data for the given asset.

13. The non-transitory computer-readable medium of claim 11, wherein the predictive model is previously defined by the computing system, and wherein the instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to handle the predictive model in accordance with the decision comprise instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to modify the predictive model based on a set of received operating data for the plurality of assets that excludes the operating data corresponding to the given position data for the given asset.

14. The non-transitory computer-readable medium of claim 10, wherein the instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to handle the predictive model in accordance with the decision comprise instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to forgo execution of the predictive model for the given asset.

15. The non-transitory computer-readable medium of claim 10, further comprising instructions stored on the non-transitory computer-readable medium that are executable to cause the computing system to:

before the determination, cause a computing device to output an indication of an abnormal condition when operating data for the given asset satisfies particular criteria; and

in response to the determination, forgo causing the computing device to output the indication of the abnormal condition when operating data for the given asset satisfies the particular criteria.

16. A computer-implemented method comprising:

receiving, by a computing system for each of a plurality of assets, position data;

determining, by the computing system, that given position data for a given asset of the plurality of assets matches a location associated with unreliable operating data;

in response to the determination, deciding, by the computing system, to disregard operating data for the given asset when handling a predictive model related to the operation of the plurality of assets; and

handling, by the computing system, the predictive model in accordance with the decision.

17. The computer-implemented method of claim 16, wherein the location associated with unreliable operating data is a first location, and wherein the method further comprises:

before the determination, defining, by the computing system, one or more locations associated with unreliable operating data, wherein the one or more locations comprise the first location.

18. The computer-implemented method of claim 17, wherein defining the one or more locations comprises defining the one or more locations based at least on historical position data for one or more of the plurality of assets.

19. The computer-implemented method of claim 16, wherein determining that the given position data for the given asset of the plurality of assets matches the location associated with unreliable operating data comprises determining that the given position data corresponds to a position that is within a threshold distance of the location associated with unreliable operating data.

20. The computer-implemented method of claim 16, wherein handling the predictive model in accordance with the decision comprises at least one of (a) defining the predictive model using a set of received operating data for the plurality of assets that excludes operating data for the given asset corresponding to the given position data for the given asset, (b) modifying the predictive model using a set of received operating data for the plurality of assets that excludes operating data for the given asset corresponding to the given position data for the given asset, or (c) forgoing execution of the predictive model for the given asset.