# US 10,768,924 B2 · Automated usage driven engineering > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,768,924 B2 - Document ID: US10768924B2 - Status: Granted - Kind: B2 - Application number: 16/719,534 - Filed: 2019-12-18 - Published: 2020-04-23 - Granted: 2020-09-08 - Earliest claimed: 2017-10-03 - Assignees: Accenture Global Solutions Limited - Applicants: Accenture Global Solutions Limited - Inventors: Matthew Thomas Short; Sunny Webb; Eric Philippe Henri Schaeffer; Robert Krueger; Teodoro Lio; Scott Anthony Ellsworth - Web page: https://patentgrep.com/patent/US10768924B2 ## CPC - G06F 8/65: Updates (security arrangements therefor G06F21/57) - G06Q 10/00: Administration; Management - 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 - 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) ## Abstract Implementations directed to providing a computer-implemented method for automating vehicle feature updates, the method being executed by one or more processors and comprising receiving telematics data identifying an actual usage of a vehicle; performing a gap analysis between the actual usage of the vehicle and an expected usage of the vehicle; determining a feature update based on the gap analysis; providing the feature update to a product engineering module when the feature cannot be implemented by a software update; and providing the feature update to an onboard computer system when the feature can be implemented by a software update. ## Claims ### Claim 1 A computer-implemented method for automating vehicle feature updates, the method being executed by one or more processors and comprising: receiving telematics data identifying an actual usage of a first vehicle; automatically performing a gap analysis, using a gap analysis component, to determine a difference between the actual usage of the first vehicle and an expected usage of the first vehicle based at least in part on the telematics data; determining, using a configuration adjustment component, a plurality of feature updates that are implementable as software updates based at least in part on the difference between the actual usage of the first vehicle and the expected usage of the first vehicle; determining a selected feature update from the plurality of feature updates to provide to an onboard computer system of an active vehicle; and updating a selected feature on the onboard computer system of the active vehicle using the selected feature update when the selected feature update can be implemented by a software update. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the selected feature update is a modification to a software component of the vehicle. ### Claim 3 (depends on 2) The computer-implemented method of claim 2, wherein the software component is a display feature shown on an adaptable display in the vehicle. ### Claim 4 (depends on 1) The computer-implemented method of claim 1 further comprising: assigning a weight value to each of the plurality of feature updates based at least in part on a machine learning algorithm, and wherein determining the selected feature is determined at least in part based on the assigned weight value of a feature update meeting a threshold. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein the telematics data is collected by a plurality of onboard sensors associated with the vehicle. ### Claim 6 (depends on 5) The computer-implemented method of claim 5, wherein the telematics data includes internal vehicle and external vehicle information collected by the onboard sensors. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein the selected feature update is a corrective action. ### Claim 8 A system, comprising: one or more processors; and a computer-readable storage device coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for automating vehicle feature updates, the operations comprising: receiving telematics data identifying an actual usage of a first vehicle; automatically performing a gap analysis, using a gap analysis component, to determine a difference between the actual usage of the first vehicle and an expected usage of the first vehicle based at least in part on the telematics data; determining, using a configuration adjustment component, a plurality of feature updates that are implementable as software updates based at least in part on the difference between the actual usage of the first vehicle and the expected usage of the first vehicle; determining a selected feature update from the plurality of feature updates to provide to an onboard computer system of an active vehicle; and updating a selected feature on the onboard computer system of the active vehicle using the selected feature update when the selected feature update can be implemented by a software update. ### Claim 9 (depends on 8) The system of claim 8, wherein the selected feature update is a modification to a software component of the vehicle. ### Claim 10 (depends on 9) The system of claim 9, wherein the software component is a display feature shown on an adaptable display in the vehicle. ### Claim 11 (depends on 8) The system of claim 8, wherein the operations further comprise: assigning a weight value to each of the plurality of feature updates based at least in part on a machine learning algorithm, and wherein determining the selected feature is determined at least in part based on the assigned weight value of a feature update meeting a threshold. ### Claim 12 (depends on 8) The system of claim 8, wherein the telematics data is collected by a plurality of onboard sensors associated with the vehicle. ### Claim 13 (depends on 12) The system of claim 12, wherein the telematics data includes internal vehicle and external vehicle information collected by the onboard sensors. ### Claim 14 (depends on 8) The system of claim 8, wherein the selected feature update is a corrective action. ### Claim 15 A method comprising: receiving telematics data identifying an actual usage of a first vehicle; automatically performing a gap analysis, using a gap analysis component, to determine a difference between the actual usage of the first vehicle and an expected usage of the first vehicle based at least in part on the telematics data; determining, using a configuration adjustment component, a feature update that is implementable as software updates based at least in part on the difference between the actual usage of the first vehicle and the expected usage of the first vehicle; and updating a feature on an onboard computer system of an active vehicle using the feature update when the feature update can be implemented by a software update. ### Claim 16 (depends on 15) The method of claim 15, wherein the feature update is a modification to a software component of the vehicle. ### Claim 17 (depends on 16) The method of claim 16, wherein the software component is a display feature shown on an adaptable display in the vehicle. ### Claim 18 (depends on 15) The method of claim 15, wherein the telematics data is collected by a plurality of onboard sensors associated with the vehicle. ### Claim 19 (depends on 18) The method of claim 18, wherein the telematics data includes internal vehicle and external vehicle information collected by the onboard sensors. ### Claim 20 (depends on 15) The method of claim 15, wherein the feature update is a corrective action.