US-12619852-B2 - Method and system for simulating, predicting, interpreting, comparing, or visualizing complex data

Abstract

A method may include receiving a data stream of complex data and receiving a type of a simulated organic life model and a type of a simulated environment. The method may include selecting a scenario for a simulation, parsing each variable in the data stream to a variable of the simulated organic life model or a variable of the simulated environment, and processing a simulation of the simulated organic life model in the simulated environment. The method may include altering one or more variables of the simulated organic life model based on one or more variables of the simulated environment, producing output data sets containing a continuum of data ranging from the data stream to predicted endpoint values for each data stream variable, and changing the simulated organic life model based on the altered one or more variables of the simulated organic life model.

Inventors

• Alexander J. Stokes

Assignees

• OHUKU LLC

Dates

Publication Date

20260505

Application Date

20180127

Claims (18)

1. 1 . A method of handling data, the method comprising: receiving a data stream of data comprising a plurality of variables, wherein the plurality of variables includes a first variable describing a characteristic of a company and a second variable describing a characteristic of an environment of the company; assigning each variable of the plurality of variables in the data stream to a respective variable of a simulated organic life model or a simulated environment, such that the first variable is assigned to a variable representing a physical parameter of a simulated organic life model and the second variable is assigned to a variable of the simulated environment, wherein the simulated organic life model represents the company as an organism modeled by the simulated organic life model, the organism being a plant, tree, fern, coral, fish, anemone, or animal; processing a simulation of the simulated organic life model in the simulated environment based on the assigned first variable and second variable, wherein the simulation simulates a biological process of the organism persisting, growing, adapting, sustaining damage, flourishing, or dying in the simulated environment based on a simulated effect of the variable of the simulated environment on the organism, and the simulation generates a visual representation of the organism such that a visual appearance of the organism represents a state of the company; altering one or more variables of the simulated organic life model based on one or more variables of the simulated environment; producing output data sets containing data from the data stream to predicted endpoint values for each data stream variable; and changing the simulated organic life model based on the altered one or more variables of the simulated organic life model; wherein the changing of the simulated organic life model changes the visual appearance of the organism in the simulation.
2. 2 . The method of claim 1 , wherein the simulated organic life model includes intrinsic variables configured as one or more outputs indicating physical parameters or physical characteristics.
3. 3 . The method of claim 1 , wherein the simulated environment simulates a mountain, a farm, plains, a celestial environment, a forest, a river, a desert, an atmospheric environment, or an aquatic environment.
4. 4 . The method of claim 3 , wherein the simulated environment includes extrinsic variables configured as one or more inputs or environmental parameters to affect changes in the simulated organic life model.
5. 5 . The method of claim 1 , wherein the data corresponds to economic markets, security systems, employment systems, national systems, weapons systems, or health management systems.
6. 6 . The method of claim 1 , wherein altering the one or more variables of the simulated organic life model includes, in response to the processing the simulation of the simulated organic life model in the simulated environment based on the one or more variables, affecting an ability of the organic life model to persist, grow, adapt, sustain damage, flourish, or die.
7. 7 . The method of claim 6 , further comprising determining a possible outcome in reality, and wherein altering the organic life model's ability to persist, grow, adapt, sustain damage, flourish, or die corresponds to the possible outcome.
8. 8 . The method of claim 7 , in response to determining the possible outcome in reality, performing outside of the simulation an affirmative act, a passive act, or an act of omission, each of which corresponds to at least one variable of the data stream parsed into one or both of the simulated organic life model and the simulated environment.
9. 9 . The method of claim 1 , further comprising receiving user interaction with the simulated environment.
10. 10 . The method of claim 9 , wherein receiving the user interaction with the simulated environment includes receiving, from a haptic device, user interaction input through the haptic device.
11. 11 . The method of claim 9 , wherein receiving the user interaction with the simulated environment includes receiving, from a virtual reality system, user interaction input through the virtual reality system.
12. 12 . A method of discovering variable to variable parsing strategies between a data stream of data and a simulated organic life model and its simulated environment, the method comprising: receiving a data stream of data comprising a plurality of variables, wherein the plurality of variables includes a first variable describing a characteristic of a company and a second variable describing a characteristic of an environment of the company; iteratively, for each combination of variables of the data stream and variables of the simulated organic life model and the simulated environment: assigning each variable of the plurality of variables of the data stream to a respective variable of a simulated organic life model or a simulated environment, such that the first variable is assigned to a variable representing a physical parameter of the simulated organic life model and the second variable is assigned to a variable of the simulated environment, wherein the simulated organic life model represents the company as an organism modeled by the simulated organic life model, the organism being a plant, tree, fern, coral, fish, anemone, or animal; processing a simulation of the simulated organic life model in the simulated environment based on the assigned first variable and second variable, wherein the simulation simulates a biological process of the organism persisting, growing, adapting, sustaining damage, flourishing, or dying in the simulated environment based on a simulated effect of the variable of the simulated environment on the organism, and the simulation generates a visual representation of the organism such that a visual appearance of the organism represents a state of the company; and recording a result of processing the simulation and a listing of each variable of the data stream and a corresponding variable of the simulated organic life model or a corresponding variable of the simulated environment; sorting results from the processed simulations by rank order; selecting a listing of each variable of the data stream and the corresponding variable of the simulated organic life model or the corresponding variable of the simulated environment based on the sorting; and using the listing with a different data stream of data for a chosen preferred simulation outcome; wherein changing the simulated organic life model changes the visual appearance of the biological organism in the simulation.
13. 13 . The method of claim 12 , wherein the simulated organic life model includes intrinsic variables configured as one or more outputs indicating physical parameters or physical characteristics.
14. 14 . The method of claim 12 , wherein the simulated environment simulates a mountain, a farm, plains, a celestial environment, a forest, a river, a desert, an atmospheric environment, or an aquatic environment.
15. 15 . The method of claim 14 , wherein the simulated environment includes extrinsic variables configured as one or more inputs or environmental parameters to affect changes in the simulated organic life model.
16. 16 . The method of claim 12 , wherein the data corresponds to economic markets, security systems, employment systems, national systems, weapons systems, or health management systems.
17. 17 . The method of claim 12 , wherein sorting by rank order includes sorting the results from the processed simulations according to a delta in growth, health, or outcome.
18. 18 . The method of claim 17 , further comprising displaying the results in a graphical format.

Description

FIELD The application relates generally to a method and system for simulating, predicting, interpreting, comparing, or visualizing complex data BACKGROUND Analysis, monitoring, and prediction of complex data can involve the collection and display of large amounts of disparate information from a multitude of sources. This numerical or categorical data is usually viewed as numerous text, graphs, or numerical summaries, by individuals who process, identify data patterns, and then predict future outcomes, based on the type of data and their personal experience in analysis of this data type. Such processes and methodologies may be complex and may require a degree of expertise beyond that of many individuals. The subject matter claimed herein is not limited to embodiments that solve any disadvantages or that operate only in environments such as those described above. Rather, this background is only provided to illustrate one example technology area where some embodiments described herein may be practiced. SUMMARY Embodiments of the present disclosure may include a method of simulating, predicting, comparing, and/or conveying complex data. The method may include receiving a data stream of complex data and receiving a type of a simulated organic life model and a type of a simulated environment. The method may further include selecting a scenario for a simulation and parsing each variable in the data stream to a variable of the simulated organic life model or a variable of the simulated environment. Additionally, the method may include processing a simulation of the simulated organic life model in the simulated environment based on the parsed variables. Also, the method may include altering one or more variables of the simulated organic life model based on one or more variables of the simulated environment. Additionally, the method may include producing output data sets containing a continuum of data ranging from the data stream to predicted endpoint values for each data stream variable. Also, the method may include changing the simulated organic life model based on the altered one or more variables of the simulated organic life model. BRIEF DESCRIPTION OF THE FIGURES These and other features, aspects, and advantages of the present disclosure are better understood when the following Detailed Description is read with reference to the accompanying drawings. FIG. 1 is a depiction of an example system to simulate and display complex data; FIG. 2 is a depiction of an example simulation process; FIG. 3 is a depiction of an example simulation process using real-time data; FIG. 4a is a schematic of the example simulation; FIG. 4b is a depiction of the processing of the example simulation; FIG. 5a is a depiction of one example embodiment of a graphical image of the simulation process; FIG. 5b is a depiction of one example embodiment of a graphical image of the simulation process for multiple simulated organic life models in an example current state; FIG. 5c is a depiction of one example embodiment of a graphical image of the simulation process for multiple simulated organic life models in an example simulation-processed state in an example negative extrinsic environment; FIG. 5d is a depiction of one example embodiment of a graphical image of the simulation process for multiple simulated organic life models in an example simulation-processed state in an example positive extrinsic environment; FIG. 5e is a depiction of an example table indicating example results of FIGS. 5b-5d as compared to FIG. 5a. FIG. 6a is a depiction of one example embodiment of a user interacting with a simulated organic life model; FIG. 6b is a depiction of one example embodiment of a user interacting with a simulated organic life model; FIG. 6c is a depiction of one example embodiment of a user interacting with a simulated organic life model; FIG. 7a is a depiction of one example embodiment of a user interacting with a simulated environment; FIG. 7b is a depiction of one example embodiment of a user interacting with a simulated environment; FIG. 7c is a depiction of one example embodiment of a user interacting with a simulated environment; FIG. 8a is a depiction of an example embodiment of an interactive virtual reality system; FIG. 8b is a depiction of example embodiments of user interaction, gestures, and movement sensing; FIG. 8c is a depiction of an example method of receiving user interaction and generating haptic feedback; FIG. 9 is a depiction of an example embodiment of an iterative variable parsing engine; and FIG. 10 is a depiction of an overview of an example simulation process. DESCRIPTION OF EMBODIMENTS Through a computer system that simulates and displays complex data as organic life models, users can monitor and compare non-text visual simulations providing a mechanism to predict data sets and compare outcomes without needing to see a text or numerical display. The computing system can be any sort of user client device or can be a serv