Data consolidation mechanisms for internet of things integration platform

• US 9,372,922 B2
• Filed: 08/01/2013
• Issued: 06/21/2016
• Est. Priority Date: 07/11/2013
• Status: Active Grant

• Current Assignee: Neura Inc (Otonomo Technologies Ltd.)
• Original Assignee: Neura Inc (Otonomo Technologies Ltd.)
• Inventors: Shaashua, Triinu Magi, Shaashua, Ori
• Primary Examiner(s): Hu, Jensen
• Application Number:
  US13/957,259
• Publication Number:
  US 20150019553A1
• Time in Patent Office: 1,055 Days
• Field of Search: 707/737
• US Class Current: 1/1
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: H04L 43/10 Active monitoring, e.g. heartbeat, ping or trace-route
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• 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: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]

Abstract

A method of consolidating Internet of Things (IoT) devices connected via an IoT network is disclosed. The method includes extracting a first data record from a data source connected to the IoT integration platform; analyzing the first data record to generate a derivative record relevant to a user context; aggregating the first data record and the derivative record to a contextually grouped data cluster; and presenting the derivative record on an integration interface along with other data records in the data cluster.

Claims

1. A method of consolidating Internet of Things (IoT) devices connected via an IoT integration platform, comprising:

extracting a first data record collected by a data source associated with an IoT device and connected to the IoT integration platform, wherein the IoT integration platform is implemented in a computing cloud and connected to multiple data sources from different vertical IoT solutions;

analyzing the first data record to generate a derivative record relevant to a user context setting specific to a perspective of a user, wherein the data source is not owned solely by the user;

aggregating the first data record and the derivative record to a contextually grouped data cluster relevant to the user context setting, wherein the contextually grouped data cluster includes records from the multiple data sources that are associated with multiple users;

presenting the derivative record on an integration interface along with other data records in the contextually grouped data cluster; and

profiling behavior of the user under the user context setting based on the contextually grouped data cluster.

2. The method of claim 1, wherein said analyzing the first data record includes generating a user-centric semantic label for the first data record.

3. The method of claim 1, wherein said analyzing the first data record includes generating a contextual description of the user context setting for the first data record.

4. The method of claim 3, further comprising correlating the first data record with a second data record based on a shared characteristic, wherein the first data record and the second data record are from different sources using different data interfaces and wherein the shared characteristic includes a shared timestamp, a shared data measurement dimension, a shared data source location, a shared semantic label, a shared owner profile, a shared social relation context, or any combination thereof;

and presenting the first data record with the second data record in connection to the contextual description.

5. The method of claim 3, wherein the contextual description is in a natural language of a user of the integration interface.

6. The method of claim 1, wherein the contextually grouped data cluster is a data cluster of device activities relevant to the user within a time period.

7. The method of claim 6, wherein presenting the derivative record includes presenting a life line diagram displaying data records in the contextually grouped data cluster within the time period to a device of the user.

8. The method of claim 1, further comprising normalizing the first data record;

and presenting the normalized first data record with the derivative record.

9. The method of claim 1, wherein the data source is a network-enabled IoT device.

10. The method of claim 1, wherein the data source is a first user account of an external website that the IoT integration platform is coupled to, where the first user account is associated with a second user account operating the integration interface.

11. A method of consolidating Internet of Things (IoT) devices connected via an IoT integration platform, comprising:

extracting a first data record collected by a data source connected to the IoT integration platform, wherein the IoT integration platform is connected to multiple data sources from different vertical IoT solutions;

analyzing the first data record to generate a derivative record relevant to a user context setting specific to a perspective of a user and to generate a semantic label for an IoT device;

aggregating the first data record and the derivative record to a contextually grouped data cluster relevant to the user context setting, wherein the contextually grouped data cluster includes records from the multiple data sources that are associated with multiple users; and

presenting the derivative record on an integration interface along with other data records in the contextually grouped data cluster;

extracting a second data record from the IoT device connected to the IoT integration platform;

analyzing the second data record to generate a context description of the second data record; and

presenting the context description on the integration interface along with the semantic label of the IoT device.

12. The method of claim 11, wherein analyzing the first data record includes determining a user entry specifying the semantic label for the IoT device.

13. The method of claim 11, wherein analyzing the first data record includes copying the semantic label for the IoT device from another IoT device when the IoT device is determined to be correlated with the another IoT device.

14. The method of claim 13, wherein the IoT device and the another IoT device is determined to be correlated when activation time is substantially similar between the IoT device and the another IoT device.

15. The method of claim 13, wherein the IoT device and the another IoT device is determined to be correlated when geo-locations of the IoT device and the another IoT device is within a predetermined distance for a predetermined duration.

16. The method of claim 11, wherein determining the semantic label is based on the semantic label being associated with limited usage of the IoT device within a time of day or time of week.

17. The method of claim 11, wherein analyzing the second data record includes generating the context description based on a device behavior pattern of the IoT device from the second data record.

18. The method of claim 11, wherein determining the semantic label is based a social connection known to the IoT integration platform between a first user accessing the integration interface and a second user registered to the IoT device.

19. The method of claim 11, wherein analyzing the second data record includes generating the context description based on a geo-location of the IoT device from the second data record.

20. The method of claim 19, wherein the geo-location is determined based on router signal strength to the IoT device.

21. The method of claim 11, wherein analyzing the second data record includes generating the context description based on absolute timing of the second data record.

22. The method of claim 11, wherein analyzing the second data record includes generating the context description based on relative timing of the second data record from a third data record.

23. An integration platform system connected to Internet of Things (IoT) devices, comprising:

a data correlation module configured to extract a first data record collected by a data source connected to the integration platform system, wherein the integration platform system is connected to multiple data sources from different vertical IoT solutions;

a data analysis module, coupled to the data correlation module, configured to analyze the first data record to generate a derivative record relevant to a user context setting specific to a perspective of a user;

wherein the data correlation module is further configured to aggregate the first data record and the derivative record to a contextually grouped data cluster relevant to the user context setting and wherein the data analysis module is configured to profile behavior of the user under the user context setting based on the contextually grouped data cluster, wherein the contextually grouped data cluster includes records from multiple data sources that are associated with multiple users; and

a consolidation interface generation module, coupled to the data correlation module and the data analysis module, configured to present the derivative record on an integration interface along with other data records in the contextually grouped data cluster.