A device for performing autonomous analytics comprises one or more adaptors, device hierarchy data, and an analytic executive. The adaptors are configured to adapt data streams from one or more heterogeneous data sources into a tagged dataset. The device hierarchy data comprises an identification of one or more hierarchical relationships between the device and one or more additional devices. The analytic executive is configured to identify a plurality of relevant devices based on the device hierarchy data and collect device data from each of the plurality of relevant devices. The analytic executive is further configured to generate a collection of analytic models using the collected device data, score one or more new data items included in the tagged dataset using the collection of analytic models, yielding scored results, and use one or more business rules to trigger an action based on the scored results.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A device for performing autonomous analytics, the device comprising: one or more adaptors configured to adapt data streams from one or more heterogeneous data sources into a tagged dataset; device hierarchy data comprising an identification of one or more hierarchical relationships between the device and one or more additional devices; an analytic executive configured to: identifying a plurality of relevant devices based on the device hierarchy data, collecting device data from each of the plurality of relevant devices, generating a collection of analytic models using the collected device data, scoring one or more new data items included in the tagged dataset using the collection of analytic models, yielding scored results, and using one or more business rules to trigger an action based on the scored results. 2. The device of claim 1, further comprising: a display component configured to present a visualization of the scored results on a display. 3. The device of claim 2, wherein the visualization comprises one or more virtual objects representative of the scored results overlaid on an image depicting one or more physical objects. 4. The device of claim 1, wherein the plurality of relevant devices comprises a plurality of child devices hierarchically connected to the device via an ISA relationship. 5. The device of claim 4, wherein the analytic executive is further configured to: distribute one or more analytic models from the collection of analytic models to the plurality of child devices. 6. The device of claim 1, wherein the plurality of relevant devices comprises a plurality of devices hierarchically connected to the device via a TYPEOF relationship. 7. The device of claim 6, wherein the analytic executive is further configured to: use the collected device data to identify relevant features in the tagged dataset during generation of the collection of analytic models. 8. The device of claim 1, wherein the plurality of relevant devices comprises a plurality of devices hierarchically connected to the device via a CONTAINS relationship. 9. The device of claim 8, wherein the analytic executive is further configured to: identify one or more relevant data sources based on the device data collected from each of the plurality of relevant devices; connect to each of the one or more relevant data sources, wherein the one or more heterogeneous data sources comprise the one or more relevant data sources. 10. The device of claim 1, wherein the analytic executive is further configured to: identifying one or more processing resources available on the one or more additional devices based on the device hierarchy data; using the one or more processing resources to generate the collection of analytic models. 11. A computer-implemented method for performing autonomous analytics, the method comprising: adapting, by a device, a plurality of data streams from one or more heterogeneous data sources into a tagged dataset; identifying, by the device, a plurality of relevant devices having a hierarchical relationship to the device; collecting, by the device, device data from each of the plurality of relevant devices, generating, by the device, a collection of analytic models using the collected device data, scoring, by the device, one or more new data items included in the tagged dataset using the collection of analytic models, yielding scored results, and using one or more business rules to trigger an action based on the scored results. 12. The method of claim 11, further comprising: presenting a visualization of the scored results on a display. 13. The method of claim 12, wherein the visualization comprises one or more virtual objects representative of the scored results overlaid on an image depicting one or more physical objects. 14. The method of claim 11, wherein the plurality of relevant devices comprises a plurality of child devices hierarchically connected to the device via an ISA relationship. 15. The method of claim 14, further comprising: distributing one or more analytic models from the collection of analytic models to the plurality of child devices. 16. The method of claim 11, wherein the plurality of relevant devices comprises a plurality of devices hierarchically connected to the device via a TYPEOF relationship. 17. The method of claim 16, further comprising: using the collected device data to identify relevant features in the tagged dataset during generation of the collection of analytic models. 18. The method of claim 11, wherein the plurality of relevant devices comprise a plurality of devices hierarchically connected to the device via a CONTAINS relationship. 19. The method of claim 18, further comprising: identifying one or more relevant data sources based on the device data collected from each of the plurality of relevant devices; connecting to each of the one or more relevant data sources, wherein the one or more heterogeneous data sources comprise the one or more relevant data sources. 20. A computing device for performing autonomous analytics, the computing device comprising: a non-volatile computer readable medium configured to store a plurality of virtual devices, each virtual device comprising: an analytic executive configured to train and score a distinct collection of analytic models based on hierarchical relationships existing between the plurality of virtual devices; and one or more processors configured to independently execute the analytic executive associated with each respective virtual device.