# US 10,372,721 B2 · Spatio-temporal data processing systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,372,721 B2 - Document ID: US10372721B2 - Status: Granted - Kind: B2 - Application number: 15/642,277 - Filed: 2017-07-05 - Published: 2017-10-19 - Granted: 2019-08-06 - Earliest claimed: 2012-12-04 - Assignees: Intertrust Technologies Corporation - Applicants: Intertrust Technologies Corporation - Inventors: Andre Karpistsenko; Rainer Sternfeld; Kalle Kagi; Oleg Murk; Rando Valt; Roberto Antonio Ferreira De Almeida - Web page: https://patentgrep.com/patent/US10372721B2 ## CPC - G06F 16/25: Integrating or interfacing systems involving database management systems - G06Q 10/06: Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling - G06Q 10/08: Logistics, e.g. warehousing, loading or distribution; Inventory or stock management - G06Q 50/02: Agriculture; Fishing; Forestry; Mining - H04L 67/2885: Hierarchically arranged intermediate devices, e.g. for hierarchical caching - G01V 99/00: Subject matter not provided for in other groups of this subclass - G01V 2210/70: Other details related to processing - G06Q 10/0637: Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals - 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 - H04N 21/23109: {by placing content in organized collections, e.g. EPG data repository (details of retrieval of video data and associated meta data in video databases G06F16/739)} - H04N 21/84: Generation or processing of descriptive data, e.g. content descriptors {(systems specially adapted for using meta-information in broadcast systems H04H60/73)} - H04N 21/8456: {by decomposing the content in the time domain, e.g. in time segments} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract This disclosure relates to systems and methods for collecting, integrating, processing, distributing, and analyzing spatial and/or spatio-temporal information associated with a variety of data sources and/or locations. In some embodiments, systems and methods described herein allow for collection and integration of information included in one or more spatial and/or spatio-temporal data streams and/or other related information that may be utilized in connection with one or more analytical processes. In certain embodiments, the disclosed embodiments may allow a user to, among other things, interact with spatio-temporal information associated with a variety of diverse data sources, generate visualizations using such data, and/or perform desired analytical queries based on the data. ## Claims ### Claim 1 A method of processing spatio-temporal data performed by a system comprising a processor and a non-transitory computer-readable storage medium storing instructions that, when executed, cause the system to perform the method, the method comprising: receiving a plurality of data streams associated with a plurality of diverse distributed data sources, the plurality of data streams comprising data having a spatial component and a temporal component; transforming the data associated with the plurality of data streams into corresponding first data entries in a first grid data structure, the first grid data structure including a plurality of spatial dimensions and at least one temporal dimension; receiving, by a service engine executing on the system, a user request from a user system relating to a subset of the data associated with the plurality of data streams; identifying a subset of the first data entries in the first grid data structure based on the received request; generating, using the service engine, a response to the user request based on the identified subset of first data entries in the first grid data structure; and transmitting the response to the user system. ### Claim 2 (depends on 1) The method of claim 1, wherein the first grid data structure includes at least three spatial dimensions. ### Claim 3 (depends on 1) The method of claim 1, wherein the method further comprises: extracting metadata included in the plurality of data streams and associating the metadata with one or more corresponding first data entries in the first grid data structure. ### Claim 4 (depends on 3) The method of claim 3, wherein identifying the subset of the first data entries in the first data grid structure is further based, at least in part, on the metadata. ### Claim 5 (depends on 3) The method of claim 3, wherein the metadata comprises aggregated information associated with the plurality of data streams. ### Claim 6 (depends on 1) The method of claim 1, wherein the data included in the plurality of data streams comprises measured data information. ### Claim 7 (depends on 1) The method of claim 1, wherein data included in the plurality of data streams comprises modeled data information. ### Claim 8 (depends on 1) The method of claim 1, wherein the response comprises a visualization generated based on the subset of the first data entries in the first grid data structure. ### Claim 9 (depends on 1) The method of claim 1, wherein the response comprises a computation result from a predictive model based on the subset of the first data entries in the first grid data structure. ### Claim 10 (depends on 1) The method of claim 1, wherein the response comprises at least one metric based on the subset of the first data entries in the first grid data structure. ### Claim 11 (depends on 1) The method of claim 1, wherein the method further comprises identifying a portion of the first data entries comprising outlier data based on data associated with the portion of the first data entries exceeding a threshold relative to data associated with other first data entries within a defined temporal and spatial range relative to the portion. ### Claim 12 (depends on 10) The method of claim 10, wherein the method further comprises generating the user response based on first data entries other than the identified portion of the first data entries. ### Claim 13 (depends on 1) The method of claim 1, wherein the first data entries are associated with a first spatial resolution and the method further comprises: transforming the first data entries into second data entries in a second grid data structure, the second data entries being associated with a second spatial resolution that is different than the first spatial resolution. ### Claim 14 A non-transitory computer-readable storage medium storing instructions that, when executed by a processor of a computer system, cause the computer system to perform a method comprising: receiving a plurality of data streams associated with a plurality of diverse distributed data sources, the plurality of data streams comprising data having a spatial component and a temporal component; transforming the data associated with the plurality of data streams into corresponding first data entries in a first grid data structure, the first grid data structure including a plurality of spatial dimensions and at least one temporal dimension; receiving, by a service engine executing on the system, a user request from a user system relating to a subset of the data associated with the plurality of data streams; identifying a subset of the first data entries in the first grid data structure based on the received request; generating, using the service engine, a response to the user request based on the identified subset of first data entries in the first grid data structure; and transmitting the response to the user system. ### Claim 15 (depends on 14) The non-transitory computer-readable storage medium of claim 14, wherein identifying the subset of the first data entries in the first data grid structure is further based, at least in part, on metadata related to the plurality of data streams associated with the first grid data structure. ### Claim 16 (depends on 14) The non-transitory computer-readable storage medium of claim 14, wherein the data included in the plurality of data streams comprises measured data information. ### Claim 17 (depends on 14) The non-transitory computer-readable storage medium of claim 14, wherein data included in the plurality of data streams comprises modeled data information. ### Claim 18 (depends on 14) The non-transitory computer-readable storage medium of claim 14, wherein the response comprises a visualization generated based on the subset of the first data entries in the first grid data structure. ### Claim 19 (depends on 14) The non-transitory computer-readable storage medium of claim 14, wherein the response comprises a computation result from a predictive model based on the subset of the first data entries in the first grid data structure. ### Claim 20 (depends on 14) The non-transitory computer-readable storage medium of claim 14, wherein the response comprises at least one metric based on the subset of the first data entries in the first grid data structure.