Method and system of interaction within both real and virtual worlds

• US 8,412,662 B2
• Filed: 06/04/2009
• Issued: 04/02/2013
• Est. Priority Date: 06/04/2009
• Status: Expired due to Fees

• Current Assignee: Google Technology Holdings LLC (Alphabet Inc.)
• Original Assignee: Motorola Mobility LLC (Lenovo Group Ltd.)
• Inventors: Ramic, Haris, Tirpak, Thomas M.
• Primary Examiner(s): Chaki, Kakali
• Assistant Examiner(s): Seck, Ababacar
• Application Number:
  US12/478,140
• Publication Number:
  US 20100312739A1
• Time in Patent Office: 1,398 Days
• Field of Search: 706/12, 706/47
• US Class Current: 706/47
• CPC Class Codes: G06N 3/006 based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]

Abstract

A method and system for controlling the activities of real and virtual entities by monitoring and analyzing a real entity'"'"'s activities and providing responses to affect virtual and real behavior patterns, according to pre-established rules. A Real-time Monitoring and Virtualization (RMV) utility collects information about the real entity'"'"'s behavior utilizing monitors. The RMV utility creates a model of the behavior of the real entity. The RMV utility utilizes the created model and maps one or more first characteristics of the behavior of the real entity to one or more second characteristics of a behavior of a virtual entity. From the monitored and mapped characteristics, the RMV utility identifies desired behavior patterns (i.e., responses) for the virtual entity, according to pre-established rules. The RMV utility triggers actions of the real entity corresponding to the responses selected for the desired behavior patterns of the virtual entity.

Claims

1. In a data processing system, a method comprising:

a receiver receiving information about a first behavior pattern comprising actions/activities of a first entity that exists in a real world;

a processor creating a model of the first behavior pattern based on actions/activities of the first entity via execution of an event sequence analysis and adaptation engine;

mapping, by using the model created, one or more first characteristics of the first behavior pattern of the first entity in the real world to one or more second characteristics of a second behavior pattern of a second entity that exists in a virtual world, according to a pre-defined set of rules, relations and conditions;

identifying potential behavior patterns for the second entity by using the mapped first and second characteristics;

selecting a current behavior pattern from among the potential behavior patterns of the second entity based on the mapped first and second characteristics; and

triggering an optimized response by the second entity based on the current behavior pattern selected.

2. The method of claim 1, wherein said collecting further comprises:

recording information about characteristics of the first entity and a corresponding environment of the first entity via one or more monitoring devices;

wherein said one or more monitoring devices are placed at one or more of;

(a) a location at which said monitoring device is attached to the first entity; and

(b) a fixed location within the surrounding environment of the first entity;

wherein said one or more monitoring devices identifies (a) an occurrence of one or more of a pre-specified set of events by using pre-defined thresholds; and

(b) an existence of one or more of a pre-specified set of conditions by using pre-defined event rules; and

wherein said one or more monitoring devices forwards information about the identified events and conditions to an event sequence analysis and adaptation engine in order to determine an appropriate response by the second entity.

3. The method of claim 1, wherein said selecting further comprises:

determining one or more of;

(a) a local response, according to a pre-specified set of local action rules and identified conditions; and

(b) a global response, according to a pre-specified set of global action rules and identified events and conditions; and

wherein said local response provides interaction directly with the first entity;

wherein said global response provides interaction directly with the surrounding environment.

4. The method of claim 1, wherein said creating further comprises:

creating behavior models that represent a pre-determined level of statistical correlation between set of events and conditions by using causal analysis techniques; and

developing said behavior models by using machine learning or incremental learning techniques;

wherein said behavior models predict probable future behavior patterns.

5. The method of claim 1, wherein said mapping further comprises:

identifying a first set of characteristics of the first entity that triggers a response by a second entity;

selecting the second entity to provide a response, according to one or more of;

(a) a set of priority rules; and

(b) characteristics of the second entity;

choosing characteristics of the second entity that the second entity utilizes in order to provide a response to the first entity; and

determining the mechanisms that are utilized to enable the second entity to provide the response, according to the characteristics chosen.

6. The method of claim 1, further comprising:

developing a virtual entity representation of the real entity based on the behavior models; and

creating said second entity that exists in the virtual world from one or more behavior models for a corresponding physical entity in the real world.

7. The method of claim 1, further comprising:

providing a graphical user interface (GUI) having one or more of;

(a) an event history list; and

(b) conditions corresponding to an event history and a pre-specified set of event rules; and

displaying preset, pre-defined labels for events and conditions recorded in a historical database, wherein said labels provide a representative scoring scale.

8. A data processing system comprising:

a memory;

one or more processors coupled to the memory;

a utility which executes on the one or more processors to provide the functions of;

collecting information about a first behavior pattern comprising actions/activities of a first entity that exists in the real world;

creating a model of the first behavior pattern based on the actions/activities of the first entity;

mapping, by using the model created, one or more first characteristics of the first behavior pattern of the first entity in the real world to one or more second characteristics of a second behavior pattern of a second entity that exists in a virtual world, according to a pre-defined set of rules, relations and conditions;

identifying potential behavior patterns for the second entity by using the mapped first and second characteristics;

selecting a current behavior pattern from among the potential behavior patterns of the second entity based on the mapped first and second characteristics; and

triggering an optimized response by the second entity based on the current behavior pattern selected.

9. The data processing system of claim 8, wherein said functions for collecting further comprises functions for:

recording information about characteristics of the first entity and a corresponding environment of the first entity via a monitoring device;

wherein said monitoring device is placed at one or more of;

(a) a location at which said monitoring device is attached to the first entity; and

(b) a fixed location within the surrounding environment of the first entity;

wherein said monitoring device identifies (a) an occurrence of one or more of a pre-specified set of events by using a pre-defined set of thresholds; and

(b) an existence of one or more of a pre-specified set of conditions by using a pre-defined set of event rules; and

wherein said monitoring device sends information about the identified events and conditions to an event sequence analysis and adaptation engine in order to determine an appropriate response by the second entity.

10. The data processing system of claim 8, wherein said functions for selecting further comprises functions for:

determining one or more of;

(a) a local response, according to a pre-specified set of local action rules and identified conditions; and

(b) a global response, according to a pre-specified set of global action rules and identified events and conditions; and

wherein said local response provides interaction directly with the first entity;

wherein said global response provides interaction directly with the surrounding environment.

11. The data processing system of claim 8, wherein said functions for creating further comprises functions for:

creating behavior models that represent a pre-determined level of statistical correlation between set of events and conditions by using causal analysis techniques; and

developing said behavior models by using one or more of machine learning and incremental learning techniques;

wherein said behavior models predict probable future behavior patterns.

12. The data processing system of claim 8, wherein said functions for mapping further comprises functions for:

identifying a first set of characteristics of the first entity that triggers a response by a second entity;

selecting the second entity to provide a response, according to one or more of;

(a) a set of priority rules; and

(b) characteristics of the second entity;

choosing a characteristics of the second entity that the second entity utilizes in order to provide a response to the first entity; and

determining the mechanisms that are utilized to enable the second entity to provide the response, according to the characteristics chosen.

13. The data processing system of claim 8, said utility further comprising functions for:

developing a virtual entity representation of the real entity based on the behavior models; and

creating said second entity that exists in the virtual world from a previously created set of behavior models for a corresponding physical entity in the real world.

14. The data processing system of claim 8, further comprising:

a display providing a graphical user interface (GUI) having one or more of;

(a) an event history list; and

(b) conditions corresponding to an event history and a pre-specified set of event rules; and

wherein said utility further comprising functions for enabling a display within the GUI of preset, pre-defined labels for events and conditions recorded in a historical database, wherein said labels provide a representative scoring scale.

15. In a data processing system having a processor, a method performed by the processor execution of one more utilities, the method comprising:

collecting information about a first behavior pattern comprising actions/activities of a first entity that exists in the real world;

creating one or more behavior models of the first behavior pattern based on the actions/activities of the first entity;

developing a virtual entity representation of the real entity based on the behavior models;

creating said virtual entity as a second entity that exists in a virtual world, wherein said virtual entity is created from the one or more behavior models;

mapping, by using the model created, one or more first characteristics of the first behavior pattern of the first entity in the real world to one or more second characteristics of a second behavior pattern of the second entity that exists in the virtual world, according to a pre-defined set of rules, relations and conditions;

identifying potential behavior patterns for the second entity by using the mapped first and second characteristics;

selecting a current behavior pattern from among the potential behavior patterns of the second entity based on the mapped first and second characteristics; and

triggering an optimized response by the second entity based on the current behavior pattern selected.

16. The method of claim 15, wherein said collecting further comprises:

recording information about characteristics of the first entity and a corresponding environment of the first entity via one or more monitoring devices;

wherein said one or more monitoring devices are placed at one or more of;

(a) a location at which said monitoring device is attached to the first entity; and

(b) a fixed location within the surrounding environment of the first entity;

wherein said one or more monitoring devices identifies (a) an occurrence of one or more of a pre-specified set of events by using pre-defined thresholds; and

(b) an existence of one or more of a pre-specified set of conditions by using pre-defined event rules; and

wherein said one or more monitoring devices forwards information about the identified events and conditions to an event sequence analysis and adaptation engine in order to determine an appropriate response by the second entity.

17. The method of claim 15, wherein said selecting further comprises:

determining one or more of;

(a) a local response, according to a pre-specified set of local action rules and identified conditions; and

(b) a global response, according to a pre-specified set of global action rules and identified events and conditions; and

wherein said local response provides interaction directly with the first entity;

wherein said global response provides interaction directly with the surrounding environment.

18. The method of claim 15, wherein said creating further comprises:

creating behavior models that represent a pre-determined level of statistical correlation between set of events and conditions by using causal analysis techniques; and

developing said behavior models by using machine learning or incremental learning techniques;

wherein said behavior models predict probable future behavior patterns.

19. The method of claim 15, wherein said mapping further comprises:

identifying a first set of characteristics of the first entity that triggers a response by a second entity;

selecting the second entity to provide a response, according to one or more of;

(a) a set of priority rules; and

(b) characteristics of the second entity;

choosing characteristics of the second entity that the second entity utilizes in order to provide a response to the first entity; and

determining the mechanisms that are utilized to enable the second entity to provide the response, according to the characteristics chosen.