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US 10,949,778 B2Granted
Computer-implemented systems and methods of analyzing data in an ad-hoc network for predictive decision-making
AssigneeTransvoyant, Inc.
InventorsKirk Elliot Bloomquist, Dennis William Groseclose
Life of this patent
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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.
Claims20
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 spatial, temporal, or contextual data elements 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, and contextual data elements that are a respective potential candidate for the respective rule;
- selecting at least two nodes from the distributed nodes as a function of the respective identified potential candidate data set for each rule of the received set of rules;
- identifying, using at least one of the selected nodes, candidate spatial, temporal, and contextual data elements received by the respective selected node for at least one rule of the received set of rules;
- spatially, temporally, or contextually indexing, using at least one of the selected nodes, the respective identified candidate data elements for the at least one rule in memory as a function of the received set of rules;
- and
- changing a display of at least one of the plurality of distributed nodes based on the indexed candidate data elements.
4 more elements
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 spatial, temporal, or contextual data elements as a function of one or more rules in 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, and contextual data elements that are a respective potential candidate for the respective rule, and further configured to select at least two distributed nodes of the plurality of distributed nodes as a function of the respective identified potential candidate data set for each rule of the set of rules;
- wherein at least one of the selected distributed nodes is configured to identify candidate spatial, temporal, and contextual data elements received by the at least one selected node for at least one rule of the set of rules;
- and
- wherein at least one of the selected distributed nodes comprises spatial, temporal, and contextual in memory distributed data structures and is configured to place respective identified spatial, temporal, or contextual candidate data elements in the corresponding one of the spatial, temporal, and contextual in memory distributed data structures as a function of the at least one rule of the set of rules.
3 more elements
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, wherein each distributed node is capable of processing spatial, temporal, or contextual data elements 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, and contextual data elements that are a respective potential candidate for the respective rule;
- selecting at least two distributed nodes from the plurality of distributed nodes as a function of a respective identified potential candidate data set for each rule of the received set of rules;
- identifying, using at least one of the selected nodes, candidate spatial, temporal, and contextual data elements received by the respective selected node for at least one rule of the received set of rules;
- spatially, temporally, or contextually indexing, using at least one of the selected nodes, the respective identified candidate data elements for the at least one rule in memory as a function of the received set of rules;
- and
- creating a relationship between at least two of the indexed candidate spatial, temporal or contextual data elements in a memory of at least one node of the plurality of distributed nodes.
4 more elements
Dependencies are inferred from the claim text.