received by the International Bureau on 30 January 2017 (30.01.2017)

We claim:

1. A computer automated system comprising:

a processing unit;

a memory element coupled to the processing unit;

a means for communicating over a network;

wherein the computer automated system is configured to, in real-time:

aggregate data from a plurality of data sources, wherein the said plurality of data sources comprise a single or plurality of proxy devices, legacy protocols, devices, applications, machines, sensors, things across locations and user types, or device clouds among devices and applications;

normalize data from the said plurality of data sources;

analyze the aggregated, normalized data based on a correlated event or events, a correlated condition or conditions, and a correlated trend or trends across the plurality of data sources;

based on the analyzed data, combine the aggregated and normalized data, and display the combined data in a display compatible format.

2. The computer automated system of claim 1 wherein the system is further configured to:

abstract a plurality of classes of the said data sources.

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3. The computer automated system of claim 2 wherein to abstract the plurality of classes of data sources comprises abstracting a plurality of classes of devices such as medical CT scanners, medical MRIs, printers, and UPS systems.

4. The computer automated system of claim 1 wherein in normalizing said data from the plurality of data sources, the computer system is further caused to:

via a plurality of extensible connectors, extract at least one of log file data, SNMP data and HTTP data from each of a plurality of connected devices.

5. The computer automated system of claim 4 wherein the system is further configured to: map data-model parameters to variables in device models via a previously created plurality of templates; and

wherein the said plurality of extensible connectors are further caused to extract the data model parameters mapped to the said variables in the said device models.

6. The computer automated system of claim 1 wherein the system is configured to:

store each device parameter as a name value pair in a no-schema database.

7. The computer automated system of claim 1 wherein the system configured to:

canonical-ize all normalized and aggregated data, which comprises simplifying the data by adding meta data and derived data to device data via a set of workflows.

8. The computer automated system of claim 1 wherein the system is configured to: display device data in a plurality of different forms wherein the said plurality of different forms comprises at least one of a graph, a chart, and a table.

9. The computer automated system of claim 8 wherein the said graph, chart and table are configured to show data relevant to each data source class.

10. The computer automated system of claim 1 wherein the analysis based on the correlated event or events, the correlated condition or conditions, and the correlated trend or trends across the plurality of data sources, comprises analysis via a single or plurality of Device Internet of Things (IOT) stacks and gateways; and wherein based on the said analysis, the system is configured to implement a single or plurality of decisions, in real-time, in a return path or closed loop, on a single or plurality of machines, sensors, devices or applications.

1 1 . The computer automated system of claim 1 further comprising a mobile device.

12. In a computer automated system comprising a processing unit coupled to a memory element and having instructions encoded thereon, a method comprising, in real-time:

aggregating data from a plurality of data sources, wherein the said plurality of data sources comprise a single or plurality of proxy devices, legacy protocols, devices, applications, machines, sensors, things across locations and user types, or device clouds among devices and applications;

normalizing said data from the plurality of data sources;

analyzing the aggregated, normalized data based on a correlated event or events, a correlated condition or conditions, and a correlated trend or trends across the plurality of data sources;

based on the analyzed data, combining the aggregated and normalized data, and displaying the combined data in a display compatible format.

13. The method of claim 12 further comprising:

abstracting a plurality of classes of the said data sources.

14. The method of claim 13 wherein the said abstracting the plurality of classes of the said data sources comprises abstracting a plurality of classes of devices such as medical CT scanners, medical MRIs, printers, and UPS systems.

15. The method of claim 12 wherein the said normalizing further comprises:

extracting at least one of a log file data, an SNMP data and HTTP data from each of a plurality of connected data sources.

16. The method of claim 1 5 further comprising:

mapping data-model parameters to variables in data source models via a plurality of pre- created templates; and

extracting the data model parameters mapped to the said variables in the said data source models via the said plurality of extensible connectors.

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17. The method of claim 12 further comprising:

storing each device parameter as a name value pair in a no-schema database.

1 8. The method of claim 12 further comprising:

canonical-izing all normalized and aggregated data, which comprises simplifying the data by adding meta data and derived data to device data via a set of workflows.

19. The method of claim 12 further comprising:

displaying device data in a plurality of forms wherein the said plurality of forms comprises at least one of a graph, a chart, and a table.

20. The method of claim 19 wherein the said graph, chart and table are configured to show data relevant to each data source class.

21. The method of claim 12 wherein the analyzing based on the correlated event or events, the correlated condition or conditions, and the correlated trend or trends across the plurality of data sources, compris^es:

analyzing via a single or plurality of Device Internet of Things (lOT) stacks and gateways; and

based on the said analyzing, implementing a single or plurality of decisions, in realtime, in a return path or closed loop, on a single or plurality of machines, sensors, devices or applications.

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22. In a computer automated system comprising a processing unit coupled to a memory element and having instructions encoded thereon, a method comprising, in real-time:

aggregating data from a plurality of data sources, wherein the said plurality of data sources comprise a single or plurality of proxy devices, legacy protocols, devices, applications, machines, sensors, things across locations and user types, or device clouds among devices and applications;

normalizing said data from the plurality of data sources, wherein the normalizing comprises:

generating an abstract data model for a single or plurality of data source classes;

extracting data model parameters via the generated abstract data model; polling the extracted data model parameters for each data source type; adding metadata and derived data to the extracted data model parameter; analyzing the aggregated and normalized data based on a correlated event or events, a correlated condition or conditions, and a correlated trend or trends across the plurality of data sources; and

based on the said analyzing:

implementing a single or plurality of decisions, in real-time, in a return path or closed loop, on a single or plurality of machines, sensors, devices or applications; and

combining the aggregated and normalized data, and displaying the combined data in a display compatible format.

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23. A mobile wireless communication device comprising:

a processing unit;

a memory element coupled to the processing unit;

encoded instructions that configure the mobile device to, in real-time:

aggregate data from a plurality of data sources, wherein the said plurality of data sources comprise a single or plurality of proxy devices, legacy protocols, devices, applications, machines, sensors, things across locations and user types, or device clouds among devices and applications;

normalize data from the said plurality of data sources;

analyze the aggregated, normalized data based on a correlated event or events, a correlated condition or conditions, and a correlated trend or trends across the plurality of data sources;

based on the analyzed data, combine the aggregated and normalized data, and display the combined data in a display compatible format.

24. The mobile wireless communication device of claim 23 wherein the device is further configured to:

based on the analyzed data, trigger a single or plurality of decisions or actions, in real-time, in a return path or closed loop, on a single or plurality of machines, sensors, devices or applications.

25. A computer automated system comprising:

a processing unit;

41 a memory element coupled to the processing unit;

a means for communicating over a network;

wherein the computer automated system is configured to, in real-time:

aggregate data from a plurality of data sources, wherein the said plurality of data sources comprise a single or plurality of proxy devices, legacy protocols, devices, applications, machines, sensors, things across locations and user types, or device clouds among devices and applications;

normalize data from the said plurality of data sources which normalizing comprises extracting data from each of a plurality of connected devices;

analyze the aggregated, normalized data based on a correlated event or events, a correlated condition or conditions, and a correlated trend or trends across the plurality of data sources;

based on the analyzed data, combine the aggregated and normalized data, and display the combined data in a display compatible format;

wherein the computer automated system is further configured to: map data-model parameters to variables in device models via a previously created plurality of templates; and

extract the data model parameters mapped to the said variables in the said device models.

26. In a computer automated system comprising a processing unit coupled to a memory element and having instructions encoded thereon, a method comprising, in real-time:

aggregating data from a plurality of data sources, wherein the said plurality of data sources comprise a single or plurality of proxy devices, legacy protocols, devices, applications,

42 machines, sensors, things across locations and user types, or device clouds among devices and applications;

normalizing said data from the plurality of data sources which normalizing comprises extracting data from each of a plurality of connected devices; ;

analyzing the aggregated, normalized data based on a correlated event or events, a correlated condition or conditions, and a correlated trend or trends across the plurality of data sources;

based on the analyzed data, combining the aggregated and normalized data, and displaying the combined data in a display compatible format;

mapping data-model parameters to variables in device models via a previously created plurality of templates; and

extracting the data model parameters mapped to the said variables in the said device models.

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