Edge computing platform

• US 10,379,842 B2
• Filed: 06/20/2018
• Issued: 08/13/2019
• Est. Priority Date: 08/27/2015
• Status: Active Grant

• Current Assignee: Tyco Fire & Security GmbH (Johnson Controls International plc)
• Original Assignee: Foghorn Systems, Inc. (Johnson Controls International plc)
• Inventors: Malladi, Sastry K M, Ravi, Thirumalai Muppur, Reddy, Mohan Komalla, Raghavendra, Kamesh
• Primary Examiner(s): Wu, Daxin
• Application Number:
  US16/013,853
• Publication Number:
  US 20180300124A1
• Time in Patent Office: 419 Days
• Field of Search: None
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06F 8/70 Software maintenance or management
• CPC Class Codes: G06F 9/542 Event management; Broadcasting; Multicasting; Notifications
• CPC Class Codes: H04L 12/2823 Reporting information sensed by appliance or service execution status of appliance services in a home automation network device-related reporting H04L43/065; arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom H04Q9/00
• CPC Class Codes: H04L 12/283 Processing of data at an internetworking point of a home automation network
• CPC Class Codes: H04L 12/40006 Architecture of a communication node current supply arrangements H04L12/10; intermediate storage or scheduling H04L49/90
• CPC Class Codes: H04L 2012/4026 Bus for use in automation systems
• CPC Class Codes: H04L 65/40 Support for services or applications
• 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 67/561 Adding application-functional data or data for application control, e.g. adding metadata

Abstract

A method for enabling intelligence at the edge. Features include: triggering by sensor data in a software layer hosted on either a gateway device or an embedded system. Software layer is connected to a local-area network. A repository of services, applications, and data processing engines is made accessible by the software layer. Matching the sensor data with semantic descriptions of occurrence of specific conditions through an expression language made available by the software layer. Automatic discovery of pattern events by continuously executing expressions. Intelligently composing services and applications across the gateway device and embedded systems across the network managed by the software layer for chaining applications and analytics expressions. Optimizing the layout of the applications and analytics based on resource availability. Monitoring the health of the software layer. Storing of raw sensor data or results of expressions in a local time-series database or cloud storage. Services and components can be containerized to ensure smooth running in any gateway environment.

Claims

1. A method comprising:

receiving a first sensor data stream from a first physical sensor of a local network at an edge computing platform coupled between the first physical sensor and a remote network, wherein the first sensor data stream comprises data about a condition being monitored;

producing on a data bus of the edge computing platform a first stream data corresponding to the first sensor data stream;

processing the first stream data from the data bus in real time at an analytics engine of the edge computing platform without first transferring the first sensor data stream to the remote network, wherein the processing comprises executing one or more analytic expressions of an expression language on the first stream data, identifying the presence of a pattern in the first stream data comprising an indication of the condition, and generating on the data bus intelligence information about the condition; and

executing an application on the edge computing platform, wherein the application determines based on the intelligence information whether to transmit at least a portion of the intelligence information to the remote network for additional processing and whether to take selected action in the local network affecting the condition monitored by the first physical sensor without awaiting the additional processing, wherein the processing at the analytics engine comprises

using the expression language, specifying a first virtual sensor comprising one or more of the analytics expressions, wherein the virtual sensor comprises a first input and a first output, the first input receives the first sensor data stream, the first output outputs a second sensor data stream on the data bus that comprises the first sensor data stream operated on according to a first function, and the intelligence information comprises the second sensor data stream, and

executing the analytics expressions specifying the first virtual sensor to apply the first virtual sensor and generate intelligence information on the data bus of the edge computing platform.

2. The method of claim 1 wherein the edge computing platform is embedded in a network device of the local network.

3. The method of claim 1 wherein the edge computing platform comprises a gateway of the local network.

4. The method of claim 1 comprising:

receiving the first sensor data stream at a data ingestion agent of the edge platform system; and

the data ingestion agent producing ingested first stream data from the first sensor data stream.

5. The method of claim 4 comprising:

receiving the ingested first stream data at a data enrichment component of the edge platform; and

the data enrichment component enriching the ingested first stream data in real time and producing enriched ingested first stream data,

wherein the enriching comprises one or more of decoding, supplementing with metadata, and normalizing the ingested stream data.

6. The method of claim 5 comprising:

receiving the enriched ingested first stream data at the analytics engine,

wherein the enriched ingested first stream data comprises the first stream data processed by the analytics engine.

7. The method of claim 6 wherein the one or more analytic expressions executed by the analytics engine specify one or more functions, each function comprising at least one of a transform, pattern detection, dynamic calibration, signal processing, math expression, data compaction, data analytic, data aggregation, rule application, alert, or service invocation, and the processing the first stream data at the analytics engine comprises applying the one or more functions to the first stream data, and generating the intelligence information.

8. The method of claim 1 wherein the selected action comprises at least one of generating an alert or altering an operation in the local network.

9. The method of claim 1 wherein the edge computing platform is coupled to the local network by a first network connection of a first type and is coupled to the remote network by a second network connection of a second type, the second type is different from the first type, and the second type comprises a lower bandwidth connection.

10. The method of claim 1 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, processing the aggregated data using machine learning.

11. The method of claim 1 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, performing remote monitoring on the aggregated data.

12. The method of claim 1 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, performing operational intelligence using the aggregated data.

13. The method of claim 1 comprising:

aggregating the first sensor data stream and second sensor data stream in real time to obtain aggregated data and transmitting the aggregated data to the remote network for additional processing.

28. The method of claim 1 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, performing predictive maintenance using the aggregated data.

14. A method comprising:

receiving a first sensor data stream from a first physical sensor of a local network at an edge computing platform coupled between the first physical sensor and a remote network, wherein the first sensor data stream comprises data relating to a condition being monitored;

producing on a data bus of the edge computing platform a first stream data corresponding to the first sensor data stream;

processing the first stream data from the data bus in real time at an analytics engine of the edge computing platform without first transferring the first sensor data stream to the remote network, wherein the processing at the analytics engine comprises

using an expression language of the analytics engine, specifying a first virtual sensor comprising one or more of the analytics expressions, wherein the virtual sensor comprises a first input that receives the first sensor data stream from the data bus, a first output that outputs a second sensor data stream on the data bus, and the second sensor data stream comprises stream data resulting from the first sensor data stream being operated on according to a first function,

executing one or more analytic expressions of the expression language to detect a presence of a pattern in the second sensor data stream, wherein an indication of the condition occurs when the presence of a pattern is detected in the second sensor data stream, and

when the indication of the condition occurs, generating on the data bus intelligence information about the condition; and

executing an application on the edge computing platform, wherein the application determines based on the intelligence information about the condition whether to at least one of transmit at least a portion of the intelligence information to the remote network for additional processing or take a predetermined action in the local network to affect the condition being monitored without awaiting the additional processing.

15. The method of claim 14 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, performing predictive maintenance using the aggregated data.

16. The method of claim 14 wherein the edge computing platform is embedded in a network device of the local network.

17. The method of claim 14 wherein the edge computing platform comprises a gateway of the local network.

18. The method of claim 14 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, processing the aggregated data using machine learning.

19. The method of claim 14 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, performing remote monitoring on the aggregated data.

20. The method of claim 14 comprising:

transmitting intelligence information comprising aggregated data based on the first sensor data stream and second sensor data stream to the remote network; and

at the remote network, performing operational intelligence using the aggregated data.

21. The method of claim 14 comprising:

aggregating the first sensor data stream and second sensor data stream in real time to obtain aggregated data and transmitting the aggregated data to the remote network for additional processing.

22. The method of claim 14 comprising:

receiving the first sensor data stream at a data ingestion agent of the edge platform system; and

the data ingestion agent producing ingested first stream data from the first sensor data stream.

23. The method of claim 22 comprising:

receiving the ingested first stream data at a data enrichment component of the edge platform; and

the data enrichment component enriching the ingested first stream data in real time and producing enriched ingested first stream data,

wherein the enriching comprises one or more of decoding, supplementing with metadata, and normalizing the ingested stream data.

24. The method of claim 23 comprising:

receiving the enriched ingested first stream data at the analytics engine,

wherein the enriched ingested first stream data comprises the first stream data processed by the analytics engine.

25. The method of claim 24 wherein the one or more analytic expressions executed by the analytics engine specify one or more functions, each function comprising at least one of a transform, pattern detection, dynamic calibration, signal processing, math expression, data compaction, data analytic, data aggregation, rule application, alert, or service invocation, and the processing the first stream data at the analytics engine comprises applying the one or more functions to the first stream data, and generating the intelligence information.

26. The method of claim 14 wherein the predetermined action comprises at least one of generating an alert or altering an operation in the local network.

27. The method of claim 14 wherein the edge computing platform is coupled to the local network by a first network connection of a first type and is coupled to the remote network by a second network connection of a second type, the second type is different from the first type, and the second type comprises a lower bandwidth connection.