Methods, systems, and computer program products for extensible, profile-and context-based information correlation, routing and distribution

• US 20060265397A1
• Filed: 02/22/2006
• Published: 11/23/2006
• Est. Priority Date: 03/06/2001
• Status: Abandoned Application

• Current Assignee: Knowledge Factor Incorporated
• Original Assignee: Knowledge Factor Incorporated
• Inventors: Vandivier, Laura C., Pace, Jason K., Pet, Willem J. A., Bryan, Edward L., Bennett, David T., Welton, Robert L., Bell, Donald J., Zobel, Richard W. Jr.
• Application Number:
  US11/359,888
• Publication Number:
  US 20060265397A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 2219/2612 Data acquisition interface
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• 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: H04L 67/30 Profiles

Abstract

Methods, systems, and computer program products for extensible, profile- and context-based information correlation, routing, and distribution are disclosed. According to one system, source plug-ins receive output from a plurality of different sensors. A content manager merges data from individual sensors together with metadata that is representative of a context and aggregates the sensor data and the context metadata into knowledge items. A scenario engine achieves sensor fusion by comparing the sensor data and its context metadata against a defined set of policies and/or rules and provides for performance of an action when a rule or policy is satisfied.

Claims

1. A system for merging data from a plurality of different sensors and for achieving sensor fusion based on a rule or policy being satisfied, the system comprising:

(a) a plurality of source plug-ins for receiving data from a plurality of different sensors;

(b) a content manager for merging the data from the sensors together with metadata that is representative of a context and for aggregating the information and the metadata into knowledge items; and

(c) a scenario engine for achieving sensor fusion by comparing the sensor data and the metadata against a predefined set of policies or rules and for providing an action when a rule or policy is satisfied.

2. The system of claim 1 comprising a delivery engine for transmitting the knowledge items over a plurality of different communication channels in response to a rule or policy being satisfied.

3. The system of claim 2 wherein the delivery engine is adapted to transmit the knowledge items to humans, knowledge switches, and computer systems using stored profile information.

4. The system of claim 2 wherein the delivery engine is adapted to automatically transmit the knowledge items to a predetermined individual using dynamic profile information for identifying the individual.

5. The system of claim 2 where in the delivery engine is adapted to transmit the knowledge items to the recipients over secure transmission channels.

6. The system of claim 2 where in the delivery engine is adapted to transmit the knowledge items to the appropriate individuals in a nonlinear manner.

7. The system of claim 2 wherein the delivery engine is adapted to provide authenticated and confirmed transmission of the knowledge items to the recipients.

8. The system of claim 2 wherein the delivery engine is adapted to, in response to failing to deliver the knowledge items to a first recipient, to deliver the knowledge items to a fallback recipient.

9. The system of claim 2 wherein the delivery engine is adapted to deliver the knowledge items to a subset of a group of recipients based on a rule or policy definition.

10. The system of claim 1 wherein the scenario engine is adapted to interface with external mathematical and logic libraries to locate the rules and policies.

11. The system of claim 1 comprising a plurality of knowledge switches including components (a)-(c) for communicating with each other in a hierarchical or peer-to-peer manner.

12. The system of claim 1 wherein the content manager and the scenario engine are extensible in real-time via plug-in software.

13. The system of claim 1 wherein the source plug-ins are adapted to interface with sensors selected from the group consisting of mechanical sensors, electronic sensors, and electro-mechanical sensors.

14. The system of claim 1 wherein the content manager is adapted to merge the sensor data with metadata including at least one of the items selected from the group consisting of geographic location information of a sensor, time and date information, history, rule or policy that was triggered, associated sensor readings at the time of receipt, and system identification information.

15. The system of claim 1 wherein the scenario engine is adapted to compare the sensor data with one or more additional types of sensor data to determine whether one of the policies or rules is satisfied.

16. The system of claim 1 wherein the scenario engine is adapted to compare the sensor data with static values to determine whether one or more of the rules or policies is satisfied.

17. The system of claim 1 wherein the scenario engine is adapted to compare the sensor data with metadata to determine whether one or more of the policies or rules is satisfied.

18. The system of claim 1 wherein the scenario engine is adapted to compare the metadata with other metadata to determine whether one or more of the policies or rules is satisfied.

19. The system of claim 1 wherein the scenario engine is adapted to compare the metadata with one or more static values to determine whether one or more of the polices or rules is satisfied.

20. The system of claim 1 wherein the scenario engine includes a functional library including functions usable to manipulate or calculate return values based on the sensor data or the metadata.

21. The system of claim 1 wherein the scenario engine is adapted to, in response to a rule or policy being satisfied, write a value in a memory location.

22. The system of claim 1 wherein the scenario engine is adapted to, in response to one of the rules or policies being satisfied, initiate execution of an external software application.

23. The system of claim 1 wherein, in response to one of the rules or polices being satisfied, the scenario engine is adapted to initiate transmission of information.

24. The system of claim 1 wherein the scenario engine is adapted to, in response to one or more of the rule or policies being satisfied, initiate a query for internal or external data.

25. The system of claim 1 wherein the scenario engine is adapted to transmit a control sequence to an external system in response to one or more of the rules or policies being satisfied.

26. The system of claim 1 comprising first and second knowledge switches, each including elements (a)-(c) wherein the first knowledge switch is deployed on a mobile platform and the second knowledge switch is deployed on a stationary platform.

27. The system of claim 26 wherein the first and second knowledge switches each have an associated area of awareness and wherein the first and second knowledge switches are adapted to communicate with each other in response to intersection of their respective areas of awareness.

28. A method for merging data from a plurality of different sensors with context metadata and for achieving sensor fusion, the method comprising:

(a) receiving data at a plurality of source plug-ins from a plurality of different sensors;

(b) merging the data from the sensors together with metadata that is representative of a context;

(c) aggregating and storing the data and the metadata as knowledge items; and

(d) achieving sensor fusion by applying scenarios to the knowledge items and providing for performance of an action when a rule or policy defined by the scenarios is satisfied.

29. A computer program product comprising computer-executable instructions embodied in a computer-readable medium for performing steps comprising:

(a) receiving data at a plurality of source plug-ins from a plurality of different sensors;

(b) merging the data from the sensors together with metadata that is representative of a context;

(c) aggregating and storing the data and the metadata as knowledge items; and

(d) achieving sensor fusion by applying scenarios to the knowledge items and providing for performance of an action when a rule or policy defined by the scenarios is satisfied.