Systems and methods for smart spaces

1. A system for providing a smart space, comprising:

a hub configured to receive data from at least one smart object in the smart space; and

an artificial intelligence server in communication with the hub configured to:

generate clusters of the data received from each of the at least one smart objects, each cluster comprising data received from one of the at least one smart objects during one of a plurality of time periods, wherein a plurality of clusters are generated for each of the at least one smart objects, each of the plurality of clusters for each of the at least one smart objects comprising data received during a different time period;

perform processing comprising using the clusters to detect an anomaly in the at least one smart object, the processing comprising evaluating a plurality of the clusters to identify a consistency between the clusters and/or evaluating at least one of the clusters to identify a difference between the at least one cluster and at least one other cluster, wherein detecting the anomaly comprises identifying at least one event in the data that is not within a threshold distance from any of the clusters; and

based on the processing, generate a command and send the command to the at least one smart object, thereby causing a change in an operation of the at least one smart object.

2. The system of claim 1 , wherein the at least one smart object comprises a door/window sensor, a smart plug, a sensor unit, a smart socket, a skipper, a presence tag, a smart wall unit, a thermostat, a plug, a dimmer, a television, a home theater component, an appliance, a lock, a machine, or a device, or a combination thereof.

3. The system of claim 1 , wherein the processing further comprises using the clusters to identify the at least one smart object, classify the at least one smart object, determine a function of the at least one smart object, determine a behavior of the at least one smart object, determine a user behavior, determine a user mood, determine an energy consumption pattern, or create an automated action, or a combination thereof.

4. The system of claim 3 , wherein creating the automated action comprises generating an alert.

5. The system of claim 3 , wherein the command comprises the automated action.

6. The system of claim 1 , wherein generating clusters comprises:

obtaining the data over a period of time;

identifying temporal relationships between events in the data; and

forming the clusters at times indicative of the temporal relationships.

7. The system of claim 1 , wherein classifying the smart object comprises analyzing the clusters to identify a pattern indicative of an object type.

8. The system of claim 1 , wherein classifying the smart object comprises:

analyzing the clusters to identify pattern indicative of a plurality of object types, thereby identifying a plurality of smart objects; and

associating the plurality of smart objects with one another into a composite object.

9. The system of claim 1 , wherein determining the user behavior comprises analyzing the clusters to identify a pattern indicative of a repeated user action.

10. The system of claim 1 , wherein determining the energy consumption pattern comprises identifying events in the data corresponding to energy use and compiling energy use data for a period of time.

11. The system of claim 10 , wherein determining the energy consumption pattern further comprises:

obtaining weather information; and

correlating the weather information with the energy use.

12. The system of claim 1 , wherein the artificial intelligence server is further configured to perform processing comprising associating the at least one smart object into a smart space network.

13. The system of claim 1 , wherein the processing to identify the smart object comprises performing a discovery process via one or more communications protocols.

14. The system of claim 1 , wherein an outcome of the processing is reported to a mobile device, a personal computer, a television, or a combination thereof.

15. The system of claim 1 , wherein the hub is further configured to control output displayed on a television.

16. The system of claim 1 , wherein the artificial intelligence server is further configured to install software on the hub.

17. The system of claim 1 , wherein:

the hub is in communication with a display and a controller, and

the hub is further configured to provide a user interface for control of the smart space via the display and receive a user command via the controller.

18. The system of claim 17 , wherein the display is a television.

19. The system of claim 1 , wherein generating the command is further based on at least one event planned by at least one intelligent agent.

20. The system of claim 19 , wherein:

the at least one intelligent agent comprises a drag and drop user interface configured to receive user input, and

generating the command is further based on the user input.

21. The system of claim 19 , wherein:

the at least one intelligent agent comprises an artificial intelligence and/or machine learning component, and

generating the command is further based on code automatically generated by the artificial intelligence and/or machine learning component.

22. A method for providing a smart space, comprising:

receiving, at a hub, data from at least one smart object in the smart space;

generating, with an artificial intelligence server in communication with the hub, clusters of the data received from each of the at least one smart objects, each cluster comprising data received from one of the at least one smart objects during one of a plurality of time periods, wherein a plurality of clusters are generated for each of the at least one smart objects, each of the plurality of clusters for each of the at least one smart objects comprising data received during a different time period;

performing processing, with the server, comprising using a cluster to detect an anomaly in the at least one smart object by performing processing including identifying at least one event in the data that is not within a threshold distance from any of the clusters; and

based on the processing, generating a command and sending the command to the at least one smart object, thereby causing a change in an operation of the at least one smart object.

23. The method of claim 22 , wherein the at least one smart object comprises a door/window sensor, a smart plug, a sensor unit, a smart socket, a skipper, a presence tag, a smart wall unit, a thermostat, a plug, a dimmer, a television, a home theater component, an appliance, a lock, a machine, or a device, or a combination thereof.

24. The method of claim 22 , wherein the processing further comprises using the clusters to identify the at least one smart object, classify the at least one smart object, determine a function of the at least one smart object, determine a behavior of the at least one smart object, determine a user behavior, determine a user mood, determine an energy consumption pattern, or create an automated action, or a combination thereof.

25. The method of claim 24 , wherein the command comprises the automated action.

26. The method of claim 24 , wherein creating the automated action comprises generating an alert.

27. The method of claim 22 , wherein generating clusters comprises:

obtaining the data over a period of time;

identifying temporal relationships between events in the data; and

forming the clusters at times indicative of the temporal relationships.

28. The method of claim 22 , wherein classifying the smart object comprises analyzing the clusters to identify a pattern indicative of an object type.

29. The method of claim 22 , wherein classifying the smart object comprises:

analyzing the clusters to identify pattern indicative of a plurality of object types, thereby identifying a plurality of smart objects; and

associating the plurality of smart objects with one another into a composite object.

30. The method of claim 22 , wherein determining the user behavior comprises analyzing the clusters to identify a pattern indicative of a repeated user action.

31. The method of claim 22 , wherein determining the energy consumption pattern comprises identifying events in the data corresponding to energy use and compiling energy use data for a period of time.

32. The method of claim 31 , wherein determining the energy consumption pattern further comprises:

obtaining weather information; and

correlating the weather information with the energy use.

33. The method of claim 22 , further comprising performing processing, with the artificial intelligence server, comprising associating the at least one smart object into a smart space network.

34. The method of claim 22 , wherein the processing to identify the smart object comprises performing a discovery process via one or more communications protocols.

35. The method of claim 22 , wherein an outcome of the processing is reported to a mobile device, a personal computer, a television, or a combination thereof.

36. The method of claim 22 , further comprising controlling, with the hub, output displayed on a television.

37. The method of claim 22 , further comprising installing, with the artificial intelligence server, software on the hub.

38. The method of claim 22 , wherein the hub is in communication with a display and a controller, the method further comprising:

providing, with the hub, a user interface for control of the smart space via the display; and

receiving, with the hub, a user command via the controller.

39. The method of claim 38 , wherein the display is a television.

40. The method of claim 22 , wherein generating the command is further based on at least one event planned by at least one intelligent agent.

41. The method of claim 40 , wherein:

the at least one intelligent agent comprises a drag and drop user interface configured to receive user input, and

generating the command is further based on the user input.

42. The method of claim 40 , wherein:

the at least one intelligent agent comprises an artificial intelligence and/or machine learning component, and

generating the command is further based on code automatically generated by the artificial intelligence and/or machine learning component.