Method for analyzing time series activity streams and devices thereof

• US 9,348,943 B2
• Filed: 12/08/2014
• Issued: 05/24/2016
• Est. Priority Date: 11/16/2011
• Status: Active Grant

• Current Assignee: PTC Inc.
• Original Assignee: PTC Inc.
• Inventors: Bullotta, Rick, Schaefer, John
• Primary Examiner(s): Pham, Tuan A
• Application Number:
  US14/563,191
• Publication Number:
  US 20150213152A1
• Time in Patent Office: 533 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2477 Temporal data queries
• CPC Class Codes: G06F 16/27 Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 16/903 Querying for retrieval from the web G06F16/953
• CPC Class Codes: G06F 16/9038 Presentation of query results
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: H04L 43/08 Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters

Abstract

A method, non-transitory computer readable medium, and data manager computing device comprises retrieving a time series data of a monitored asset based on one or more tags in response to a request. Further, a heterogeneous data based on the one or more tags is retrieved. Furthermore, a cause of an anomaly period in retrieved time series data of the monitored asset is determined based on the retrieved heterogeneous data. Finally, the determined cause of the anomaly period in the time series data in the monitored asset is provided.

Claims

1. A method for managing time series data of monitored assets, the method comprising:

connecting, to a network, a system for managing data associated with a plurality of monitored asset devices, the network including the plurality of monitored asset devices, a plurality of client computing devices, and a plurality of third party computing devices;

storing, in a memory associated with the system for managing data, time series activity streams including time series data originating from the plurality of monitored asset devices,

wherein each of the time series data includes at least one of tags, metadata and a time stamp;

retrieving, by a processor of the system for managing data, first time series data associated with a first monitored asset device of the plurality of monitored asset devices;

identifying an anomaly period among the retrieved first time series data of the first monitored asset device, the anomaly period indicating an anomaly in operation of the first monitored asset device,

wherein the anomaly period is identified based on at least one of (i) a comparison of the first time series data to threshold values of the first monitored asset device, (ii) a calculation determining that the first time series data exceeds a predetermined standard deviation, and (iii) an input including an anomaly notification;

retrieving, by the processor, responsive to the identification of the anomaly period, first heterogeneous data associated with the anomalous period, the first heterogeneous data being different than the first time series data,

wherein the heterogeneous data is originated from at least one of (i) the memory associated with the system for managing data, (ii) the plurality of monitored asset devices, (iii) the plurality of client computing devices, and (iv) the plurality of third party computing devices; and

transmitting, by the processor, to one of the client computing devices, at least two of (i) a result set including at least a portion of the first time series data and the first heterogeneous data, (ii) a cause of the anomaly occurring in the anomaly period, determined based at least in part on the first heterogeneous data, and (iii) a corrective step to correct the anomaly,

wherein the corrective step includes instructions identified based on at least one of (i) correlating the cause of the anomaly to a table of corrected steps stored in the memory associated with the system for managing data, (ii) receiving inputs from computing devices of technical experts or manufacturers, and (iii) identifying suggestions in social network databases.

2. The method of claim 1, wherein the first heterogeneous data includes data associated with a time prior to or during the anomalous period.

3. The method of claim 1, wherein the heterogeneous data includes structured and/or unstructured data and includes at least one of (i) heterogeneous contextual data, and (ii) heterogeneous related asset data.

4. The method of claim 3,

wherein the memory stores a hierarchical relationship model defining associations among the plurality of monitored asset devices,

wherein the retrieving the first heterogeneous data includes retrieving heterogeneous related asset data from one or more related monitored assets of the plurality of monitored asset devices, and

wherein the one or more related monitored assets are determined based on hierarchical relationship model of the first monitored asset device.

5. The method of claim 1, wherein the heterogeneous data includes heterogeneous contextual data originating from one or more of data servers and social network databases.

6. The method of claim 1, wherein the retrieval of the first time series data associated with a first monitored asset device is performed in response to receiving a request from one of the plurality of client computing devices,

wherein the request includes at least one keyword, and wherein the first time series data is identified from the time series activity streams based on a query using the at least one keyword included in the request and the tags of the time series data in the time series activity streams.

7. The method of claim 1, wherein each of the plurality of monitored asset devices include corresponding sensors, and wherein the time series activity streams are received periodically or in real time from the sensors of the plurality of monitored asset devices.

8. The method of claim 1, comprising:

receiving, from the sensors of one of the plurality of monitored asset devices, time series data;

tagging, by a processor of the system for managing data, the time series data using keywords and/or metadata; and

storing the received time series data in the memory associated with the system for managing data, the time series data being stored in association with corresponding time stamps.

9. A system for managing time series data of monitored assets, the system comprising:

a processor; and

a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to;

connect, to a network, a system for managing data associated with a plurality of monitored asset devices, the network including the plurality of monitored asset devices, a plurality of client computing devices, and a plurality of third party computing devices;

store, in the memory, time series activity streams including time series data originating from the plurality of monitored asset devices,

wherein each of the time series data includes at least one of tags, metadata and a time stamp;

retrieve first time series data associated with a first monitored asset device of the plurality of monitored asset devices, the first heterogeneous data being different than the first time series data;

determine whether an anomaly period is identified among the retrieved first time series data of the first monitored asset device, the anomaly period indicating an anomaly in operation of the first monitored asset device,

wherein the anomaly period is identified based on at least one of (i) a comparison of the first time series data to threshold values of the first monitored asset device, (ii) a calculation determining that the first time series data exceeds a predetermined standard deviation, and (iii) an input including an anomaly notification; and

if the determination identifies an anomaly period;

retrieve first heterogeneous data associated with the anomalous period,

wherein the heterogeneous data is originated from at least two of (i) the memory associated with the system for managing data, (ii) the plurality of monitored asset devices, (iii) the plurality of client computing devices, and (iv) the plurality of third party computing devices; and

transmit to one of the client computing devices, at least one of (i) a result set including at least a portion of the first time series data and the first heterogeneous data, (ii) a cause of the anomaly occurring in the anomaly period, determined based at least in part on the first heterogeneous data, and (iii) a corrective step to correct the anomaly,

wherein the corrective step to correct the anomaly includes instructions identified based on at least one of (i) correlating the cause of the anomaly to a table of corrected steps stored in the memory associated with the system for managing data, (ii) receiving inputs from computing devices of technical experts or manufacturers, and (iii) identifying suggestions in social network databases.

10. The system of claim 9, wherein the first heterogeneous data includes data associated with a time prior to or during the anomalous period.

11. The system of claim 9, wherein the heterogeneous data includes structured and/or unstructured data and includes at least one of (i) heterogeneous contextual data, and (ii) heterogeneous related asset data.

12. The system of claim 11,

wherein the memory stores a hierarchical relationship model defining associations among the plurality of monitored asset devices,

wherein the retrieving the first heterogeneous data includes retrieving heterogeneous related asset data from one or more related monitored assets of the plurality of monitored asset devices, and

wherein the one or more related monitored assets are determined based on hierarchical relationship model of the first monitored asset device.

13. The system of claim 9, wherein the heterogeneous data includes heterogeneous contextual data originating from one or more of data servers and social network databases.

14. The system of claim 9,

wherein the retrieval of the first time series data associated with a first monitored asset device is performed in response to receiving a request from one of the plurality of client computing devices,

wherein the request includes at least one keyword, and wherein the first time series data is identified from the time series activity streams based on a query using the at least one keyword included in the request and the tags of the time series data in the time series activity streams.

15. The system of claim 9, wherein each of the plurality of monitored asset devices include corresponding sensors, and wherein the time series activity stream are received periodically or in real time from the sensors of the plurality of monitored asset devices.

16. The system of claim 9, wherein the instructions, when executed by the processor, cause the processor to:

receive, from the sensors of one of the plurality of monitored asset devices, time series data;

tag the time series data using keywords and/or metadata; and

store the received time series data in the memory associated with the system for managing data, the time series data being stored in association with corresponding time stamps.