IP Library › Granted Patent US 12,744,820
Granted Patent B2
US 12,744,820 · App. 18/813,475 · Granted Sep 22, 2026

Time-series geospatial data system for world simulation

Inventors: Jason Crabtree (Vienna, VA); Andrew Sellers (Monument, CO)
Assignee: QOMPLX LLC
H04L63/20G06F16/2477G06F16/951H04L63/1425H04L63/1441
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Quick Facts
Patent No.
US 12,744,820
App. No.
18/813,475
Filed
Aug 23, 2024
Granted
Sep 22, 2026
Kind
B2
Art Unit
2497
USPC
726/22
Abstract

A system and method for providing time-series geospatial data and a world-scale simulation platform used to generate simulated-world environments by rendering data-dense geographical regions corresponding to heterogenous sourced data and formats for highly scalable parallel simulations, and comprised of a multi-dimensional time-series database used for enabling query support across multiple simulations via individual simulation and entity swimlanes for cyber, physical and cyber-physical entities and regions.

Claims (67)

1 . A computing system for data-dense geographical regions using heterogenous source data and formats for enabling highly scalable parallel world simulations, comprising:

a computer system comprising a memory and a processor;

a plurality of instructions that, when operating on the processor, cause the computer system to:

retrieve a plurality of geospatial data for a geographic region, wherein the geospatial data includes both real-world geospatial data and simulated geospatial data;

assign a unique identifier for each of one or more portions of the geospatial data, wherein each unique identifier is associated with a particular digital world of a plurality of digital worlds;

store the geospatial data and the associated unique identifiers in a multidimensional time-series database, wherein the multidimensional time-series database is structured based on the plurality of digital worlds;

assign the geospatial data to distinct processing units based on the unique identifiers associated with the geospatial data to execute a plurality of simulations, wherein one or more of the plurality of simulations are each associated with a different digital world;

execute the plurality of simulations for each processing unit using the geospatial data from the multidimensional time-series database;

render results from the plurality of simulations to a user interface; and

perform queries across the results from the plurality of simulations.

2 . The system of claim 1 , wherein the location identifier comprises keywords identifying a specific location.

3 . The system of claim 1 , wherein the geospatial data includes vector data.

4 . The system of claim 1 , wherein the geospatial data includes raster tiles.

5 . The system of claim 1 , wherein at least some of the geospatial data represents time-progressive analyses.

6 . The system of claim 1 , wherein the location identifiers link to additional datasets.

7 . The system of claim 1 , wherein the geospatial data includes sensor data.

8 . The system of claim 1 , further comprising filters for refining data.

9 . The system of claim 8 , wherein the filters apply to time-series data.

10 . A computer-implemented method for data-dense geographical regions using heterogenous source data and formats for enabling highly scalable parallel world simulations, the computer-implemented method comprising:

retrieving a plurality of geospatial data for a geographic region, wherein the geospatial data includes both real-world geospatial data and simulated geospatial data;

assigning a unique identifier for each of one or more portions of the geospatial data, wherein each unique identifier is associated with a particular digital world of a plurality of digital worlds;

storing the geospatial data and the associated unique identifiers in a multidimensional time-series database, wherein the multidimensional time-series database is structured based on the plurality of digital worlds;

assigning the geospatial data to distinct processing units based on the unique identifiers associated with the geospatial data to execute a plurality of simulations, wherein one or more of the plurality of simulations are each associated with a different digital world;

executing the plurality of simulations for each processing unit using the geospatial data from the multidimensional time-series database;

rendering results from the plurality of simulations to a user interface; and

performing queries across the results from the plurality of simulations.

11 . The computer-implemented method of claim 10 , wherein the location identifier comprises keywords identifying a specific location.

12 . The computer-implemented method of claim 10 , wherein the geospatial data includes vector data.

13 . The computer-implemented method of claim 10 , wherein the geospatial data includes raster data.

14 . The computer-implemented method of claim 10 , wherein at least some of the geospatial data represents time-progressive analyses.

15 . The computer-implemented method of claim 10 , wherein location identifiers link to additional datasets.

16 . The computer-implemented method of claim 10 , wherein the geospatial data includes sensor data.

17 . The computer-implemented method of claim 10 , further comprising applying filters to refine data.

18 . The computer-implemented method of claim 17 , wherein the filters apply to time-series data.

19 . A system for data-dense geographical regions using heterogenous source data and formats for enabling highly scalable parallel world simulations, comprising:

a computing system comprising a processor and a memory, configured to:

retrieve a plurality of geospatial data for a geographic region, wherein the geospatial data includes both real-world geospatial data and simulated geospatial data;

assign a unique identifier for each of one or more portions of the geospatial data, wherein each unique identifier is associated with a particular digital world of a plurality of digital worlds;

store the geospatial data and the associated unique identifiers in a multidimensional time-series database, wherein the multidimensional time-series database is structured based on the plurality of digital worlds;

assign the geospatial data to distinct processing units based on the unique identifiers associated with the geospatial data to execute a plurality of simulations, wherein one or more of the plurality of simulations are each associated with a different digital world;

execute the plurality of simulations for each processing unit using the geospatial data from the multidimensional time-series database;

render results from the plurality of simulations to a user interface; and

perform queries across the results from the plurality of simulations.

20 . The system of claim 19 , wherein the location identifier comprises keywords identifying a specific location.

21 . The system of claim 19 , wherein the geospatial data includes vector data.

22 . The system of claim 19 , wherein the geospatial data includes raster data.

23 . The system of claim 19 , wherein at least some of the geospatial data represents time-progressive analyses.

24 . The system of claim 19 , wherein location identifiers link to additional datasets.

25 . The system of claim 19 , wherein the geospatial data includes sensor data.

26 . The system of claim 19 , further comprises applying filters to refine data.

27 . The system of claim 26 , wherein the filters apply to time-series data.

28 . Non-transitory, computer-readable storage media having computer-executable instructions embodied thereon that, when executed by one or more processors of a computing system for enabling highly scalable parallel world simulations, cause the computing system to:

retrieve a plurality of geospatial data for a geographic region, wherein the geospatial data includes both real-world geospatial data and simulated geospatial data;

assign a unique identifier for each of one or more portions of the geospatial data, wherein each unique identifier is associated with a particular digital world of a plurality of digital worlds;

store the geospatial data and the associated unique identifiers in a multidimensional time-series database, wherein the multidimensional time-series database is structured based on the plurality of digital worlds;

assign the geospatial data to distinct processing units based on the unique identifiers associated with the geospatial data to execute a plurality of simulations, wherein one or more of the plurality of simulations are each associated with a different digital world;

execute the plurality of simulations for each processing unit using the geospatial data from the multidimensional time-series database;

render results from the plurality of simulations to a user interface; and

perform queries across the results from the plurality of simulations.

29 . The non-transitory, computer-readable storage media of claim 28 , wherein the location identifier comprises keywords identifying a specific location.

30 . The non-transitory, computer-readable storage media of claim 28 , wherein the geospatial data includes vector data.

31 . The non-transitory, computer-readable storage media of claim 28 , wherein the geospatial data includes raster data.

32 . The non-transitory, computer-readable storage media of claim 28 , wherein at least some of the geospatial data represents time-progressive analyses.

33 . The non-transitory, computer-readable storage media of claim 28 , wherein location identifiers link to additional datasets.

34 . The non-transitory, computer-readable storage media of claim 28 , wherein the geospatial data includes sensor data.

35 . The non-transitory, computer-readable storage media of claim 28 , further comprises applying filters to refine data.

36 . The non-transitory, computer-readable storage media of claim 35 , wherein the filters apply to time-series data.

Assignments (3)
CHANGE OF NAME Recorded Sep 28, 2024
From: QPX LLC
To: QOMPLX LLC
Reel/Frame 069070/0283 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 18, 2024
From: QOMPLX, INC.
To: QPX LLC
Reel/Frame 068989/0509 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 15, 2024
From: CRABTREE, JASON; SELLERS, ANDREW
To: QOMPLX, INC.
Reel/Frame 068590/0967 →
Continuity (48)
Continuation 18497243 · Oct 30, 2023
Continuation 17106997 · Nov 30, 2020
Continuation In Part 15931534 · May 13, 2020
Continuation In Part 16777270 · Jan 30, 2020
Continuation In Part 16720383 · Dec 19, 2019
Continuation 15823363 · Nov 27, 2017
Continuation In Part 15725274 · Oct 4, 2017
Continuation In Part 15655113 · Jul 20, 2017
Continuation In Part 15616427 · Jun 7, 2017
Continuation In Part 14925974 · Oct 28, 2015
Continuation In Part 15237625 · Aug 15, 2016
Continuation In Part 15206195 · Jul 8, 2016
Continuation In Part 15186453 · Jun 18, 2016
Continuation 15166158 · May 26, 2016
Continuation In Part 15141752 · Apr 28, 2016
Continuation In Part 15091563 · Apr 5, 2016
Continuation In Part 14986536 · Dec 31, 2015
Continuation In Part 14925974 · Oct 28, 2015
Continuation In Part 15683765 · Aug 22, 2017
Continuation In Part 15409510 · Jan 18, 2017
Continuation In Part 15379899 · Dec 15, 2016
Continuation In Part 15376657 · Dec 13, 2016
Continuation In Part 15237625 · Aug 15, 2016
Continuation In Part 16718906 · Dec 18, 2019
Continuation 15879182 · Jan 24, 2018
Continuation In Part 15850037 · Dec 21, 2017
Continuation In Part 15673368 · Aug 9, 2017
Continuation In Part 15376657 · Dec 13, 2016
Continuation In Part 15489716 · Apr 17, 2017
Continuation In Part 15409510 · Jan 18, 2017
Continuation In Part 15905041 · Feb 26, 2018
Continuation In Part 15237625 · Aug 15, 2016
Continuation In Part 16191054 · Nov 14, 2018
Continuation In Part 15655113 · Jul 20, 2017
Continuation In Part 16654309 · Oct 16, 2019
Continuation In Part 15847443 · Dec 19, 2017
Continuation In Part 15790457 · Oct 23, 2017
Continuation In Part 15790327 · Oct 23, 2017
Continuation In Part 15616427 · Jun 7, 2017
Continuation In Part 15141752 · Apr 28, 2016
Continuation In Part 15616427 · Jun 7, 2017
Continuation In Part 15489716 · Apr 17, 2017
Continuation In Part 16660727 · Oct 22, 2019
Continuation 15229476 · Aug 5, 2016
Continuation In Part 15206195 · Jul 8, 2016
Provisional Application 62568298 · Oct 4, 2017
Provisional Application 62568291 · Oct 4, 2017
Related Publication 20240414209A1 · Dec 12, 2024
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