Computer-implemented systems and methods of analyzing data in an ad-hoc network for predictive decision-making

• US 10,091,276 B2
• Filed: 05/16/2014
• Issued: 10/02/2018
• Est. Priority Date: 09/27/2013
• Status: Active Grant

• Current Assignee: TransVoyant Inc.
• Original Assignee: TransVoyant Inc.
• Inventors: Bloomquist, Kirk Elliot, Groseclose, Dennis William
• Primary Examiner(s): Taylor, Nicholas
• Assistant Examiner(s): Roy, Sanjoy
• Application Number:
  US14/279,526
• Publication Number:
  US 20160337441A1
• Time in Patent Office: 1,600 Days
• CPC Class Codes: G06N 5/025 Extracting rules from data
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G08B 31/00 Predictive alarm systems characterised by extrapolation or other computation using updated historic data
• CPC Class Codes: H04L 67/5651 Reducing the amount or size of exchanged application data
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

A computer-implemented system and method of predictive decision-making in an ad hoc network. The computer-implemented method includes receiving a set of rules into the ad hoc network and identifying a data set for each rule. The computer-implemented method also includes selecting a first and second node from the ad hoc network to process a first and second rule as a function of the identified data set according to an optimizing algorithm. The computer-implemented method also selects a third node to receive the processed results from the first and second nodes. An indication is provided of the processed results by the third node.

Claims

1. A computer-implemented method for predictive decision-making, comprising:

receiving a set of rules into an ad-hoc network having distributed nodes, wherein each distributed node is capable of processing data as a function of one or more rules in the set of rules;

for each rule of the received set of rules, identifying a respective potential candidate data set including spatial, temporal, or contextual data elements that are a respective potential candidate for the respective rule;

selecting a first node from the distributed nodes as a function of the respective identified potential candidate data set for a first rule of the received set of rules, wherein the first node is configured to identify candidate spatial, temporal, or contextual data elements, and disregard non-candidate data elements, received by the selected first node for the first rule;

selecting a second node from the distributed nodes as a function of the respective identified potential candidate data set for a second rule of the received set of rules, wherein the second node is configured to identify candidate spatial, temporal, or contextual data elements, and disregard non-candidate data elements, received by the selected second node for the second rule;

selecting a third node from the distributed nodes, wherein the third node is configured to receive respective identified candidate spatial, temporal, or contextual data elements for each of the first and second rules from the selected first and second nodes and to spatially, temporally, or contextually index the received candidate data elements in memory as a function of the received set of rules;

receiving, at the selected third node, identified candidate spatial, temporal, or contextual data elements for each of the first and second rules from the selected first and second nodes;

spatially, temporally, or contextually indexing, at the selected third node, the received candidate spatial, temporal, or contextual data elements in memory as a function of the received set of rules; and

changing a display at the selected third node based on the indexed candidate data elements.

2. The method of claim 1, wherein the selected first node is different from the selected second node and the selected third node is the same as the selected first node or the selected second node.

3. The method of claim 1, wherein the step of selecting the first node includes identifying a source of potential candidate spatial, temporal, or contextual data elements in the respective identified potential candidate data set for the first rule.

4. The method of claim 3, wherein the step of identifying a source of potential candidate spatial, temporal, or contextual data elements includes identifying one or more of a dynamic potential candidate data source, a location of the potential candidate data elements, or an origin of the potential candidate data elements.

5. The method of claim 1, wherein at least one of the steps of selecting the first node, selecting the second node, or selecting the third note further comprises using an optimizing algorithm to minimize the amount of data elements transferred between distributed nodes of the ad hoc network.

6. The method of claim 1, wherein at least one of the steps of selecting the first node, selecting the second node, or selecting the third note further comprises using an optimizing algorithm to minimize the processing required by the distributed nodes to process data elements as a function of the first and second rules of the received set of rules.

7. The method of claim 1, wherein the first rule and the second rule are subrules of a third rule of the received set of rules;

wherein the method further comprises;

the selected third node identifying an event as satisfying the third rule using the spatially, temporally, or contextually indexed candidate data elements;

wherein the step of changing the display comprises displaying an indication that the third rule is satisfied.

8. The method of claim 1, wherein the step of changing the display at the selected third node comprises one or more of the following steps:

displaying the indexed candidate data elements;

providing an alert from the selected third node; and

displaying a recommended action sequence at the third node based on the indexed candidate data elements.

18. The method of claim 1, wherein the selected third node comprises at least one spatial, temporal, or contextual in memory distributed data structure for a third rule of the received set of rules and wherein the step of spatially, temporally, or contextually indexing comprises placing the received candidate data elements in the corresponding one of the at least one spatial, temporal, or contextual in memory distributed data structure as a function of the third rule.

19. The method of claim 1, wherein at least one of the selected first or second nodes comprises at least one spatial, temporal, or contextual in memory distributed data structure for the corresponding first or second rule, and wherein the step of receiving identified candidate data elements further comprises receiving identified candidate spatial, temporal, or contextual data elements from the corresponding at least one spatial, temporal, or contextual in memory distributed data structure of the at least one of the selected first or second nodes.

20. The method of claim 1, further comprising transmitting a notification message from the selected third node based on the indexed candidate data elements.

9. A system for predictive decision-making, comprising:

a set of rules;

a plurality of distributed nodes forming an ad hoc network, each of the plurality of nodes being capable of processing data as a function of one or more rules in the set of rules and of receiving data from a data source;

wherein the plurality of distributed nodes further comprises;

a first distributed node configured to identify candidate spatial, temporal, or contextual data elements, and disregard non-candidate data elements, received by the first node for a first rule;

a second distributed node configured to identify candidate spatial, temporal, or contextual data elements, and disregard non-candidate data elements, received by the first node for a second rule; and

a third distributed node comprising at least one spatial, temporal, or contextual in memory distributed data structure for a third rule of the set of rules, the third distributed node configured to respectively receive identified candidate spatial, temporal, or contextual data elements for each of the first and second rules from the first and second nodes, and is further configured to place the received spatial, temporal, or contextual candidate data elements in the corresponding one of the at least one spatial, temporal, or contextual in memory distributed data structure as a function of the third rule of the set of rules;

a rules manager configured to, for each rule of the set of rules, identify a respective potential candidate data set including spatial, temporal, or contextual data elements that are a respective potential candidate for the respective rule, to select the first and second nodes as a function of the respective identified potential candidate data set for the first and second rules, and to select the third node as a function of the set of rules.

10. The system of claim 9, wherein the first node is different from the second node and the third node is the same as the first or second node.

11. The system of claim 9, wherein the rules manager is in a distributed node of the plurality of distributed nodes.

12. The system of claim 9, wherein the rules manager is distributed between two or more distributed nodes of the plurality of distributed nodes.

13. The system of claim 9, wherein the first rule and the second rule are subrules of a third rule of the set of rules, wherein the third distributed node is further configured to identify an event as satisfying the third rule using the candidate spatial, temporal, or contextual data elements placed in the corresponding one of the at least one spatial, temporal, or contextual in memory distributed data structure for the third rule.

14. The system of claim 9, wherein the third distributed node further comprises at least one of a display, or an interface to provide an alert or notification message to another distributed node based on the indexed candidate spatial, temporal, or contextual data elements for the third rule.

15. The system of claim 9, wherein the rules manager is configured to distribute respective rules of the set of rules to selected nodes of the plurality of distributed nodes using an optimizing algorithm.

16. A computer-implemented method for predictive decision-making, comprising:

receiving a set of rules into an ad-hoc network having a plurality of distributed nodes, where each distributed node is capable of processing data as a function of one or more rules in the received set of rules;

for each rule of the received set of rules, identifying a respective potential candidate data set including spatial, temporal, or contextual data elements that are a respective potential candidate for the respective rule;

using an optimizing algorithm to select two or more distributed nodes from the plurality of distributed nodes as a function of a respective identified potential candidate data set for a respective rule of the received set of rules, wherein each selected distributed node is configured to identify respective candidate spatial, temporal, or contextual data elements, and to disregard non-candidate data elements, received by the respective distributed node for the respective rule and to select a third distributed node from the plurality of distributed nodes to receive respective identified candidate spatial, temporal, or contextual data elements for each of the respective rules from the selected two or more distributed nodes and to index the received candidate spatial, temporal, or contextual data elements in memory as a function of the received set of rules;

receiving the respective identified candidate spatial, temporal, or contextual data elements from each of the two or more distributed nodes at the third distributed node;

indexing the received candidate spatial, temporal, or contextual data elements in memory at the third distributed node as a function of the received set of rules; and

the third distributed node creating a relationship in memory between two or more of the indexed candidate spatial, temporal or contextual data elements.

17. The method of claim 16, wherein the third distributed node is a different distributed node from each of the two or more distributed nodes and wherein the method further comprises the third distributed node providing a rule suggestion based on the relationship created in memory by the third distributed node.