# US 12,002,068 B2 · Data processing system with machine learning engine to provide output generation functions > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,002,068 B2 - Document ID: US12002068B2 - Status: Granted - Kind: B2 - Application number: 16/582,611 - Filed: 2019-09-25 - Published: 2020-04-02 - Granted: 2024-06-04 - Earliest claimed: 2018-09-28 - Assignees: Allstate Insurance Company - Applicants: Allstate Insurance Company - Inventors: Sunil Chintakindi; Timothy W. Gibson; Howard Hayes; Regina Madigan; Soton Ayodele Rosanwo; Juan Ortiz-Zabala - Web page: https://patentgrep.com/patent/US12002068B2 ## CPC - G06Q 30/0239: {Online discounts or incentives} - A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet} - A61B 5/02: Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow - A61B 5/024: Measuring pulse rate or heart rate - A61B 5/1112: {Global tracking of patients, e.g. by using GPS} - A61B 5/163: {by tracking eye movement, gaze, or pupil change} - A61B 5/18: for vehicle drivers {or machine operators} - A61B 5/6898: {Portable consumer electronic devices, e.g. music players, telephones, tablet computers} - A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor} - G06F 16/337: {Profile generation, learning or modification} - G06F 21/31: User authentication - G06F 21/32: using biometric data, e.g. fingerprints, iris scans or voiceprints - G06N 20/00: Machine learning - G06Q 30/0222: {During e-commerce, i.e. online transactions} - G06Q 30/0236: {Incentive or reward received by requiring registration or ID from user} - G06Q 30/0269: {based on user profile or attribute} - G06Q 30/0611: {Request for offers or quotes} - G06Q 40/08: Insurance - G16H 10/60: for patient-specific data, e.g. for electronic patient records - H04W 4/029: Location-based management or tracking services - H04W 4/40: for vehicles, e.g. vehicle-to-pedestrians [V2P] - A61B 2560/0242: adapted to measure environmental factors, e.g. temperature, pollution - A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches - A61B 2562/0247: Pressure sensors - G06Q 30/0255: {based on user history} - G06Q 30/0261: {based on user location} - G16H 20/00: ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance - G16H 50/30: for calculating health indices; for individual health risk assessment - H04W 4/021: Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences - H04W 4/38: for collecting sensor information - 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 - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract Methods, computer-readable media, systems, and/or apparatuses for providing offer and output generation functions are provided. For instance, a request for an output may be received by a device. In response, user physical trait data, pre-stored data, location data, and the like, may be extracted and received from a plurality of sources. Machine learning may be used to analyze the data to predict one or more factors associated with the user and the output or offer may be generated based on the predicted factors. ## Claims ### Claim 1 A computing platform, comprising: a processing unit comprising a processor; a communication interface; and a memory unit storing computer-executable instructions that, when executed by the processing unit, cause the computing platform to: receive a request to generate a customized output; generate an instruction to capture physical trait data of a user; transmit the instruction to a mobile device of the user; receive, from the mobile device, the captured physical trait data, wherein the physical trait data is captured via one or more sensors of the mobile device; receive, from the mobile device, one or more mobility patterns of the user based on one or more patterns of driving location; receive, from one or more sensors of a vehicle associated with the user, vehicle performance data corresponding to maneuvers performed by the vehicle while being driven by the user; apply machine learning to the received captured physical trait data, the one or more mobility patterns of the user, and the received vehicle performance data to determine a pattern of decision making behavior made by the user while interacting with the vehicle at specific locations; determine a risk profile based on the pattern of decision making behavior; generate the customized output to include a set of options that correspond to the risk profile of the user; generate a user interface including the customized output; and transmit the user interface to the mobile device for display on a display of the mobile device. ### Claim 2 (depends on 1) The computing platform of claim 1, wherein the captured physical trait data is captured by one or more biometric sensors. ### Claim 3 (depends on 1) The computing platform of claim 1, wherein the instruction to capture physical trait data of the user includes a request for the user to perform an activity with the mobile device. ### Claim 4 (depends on 1) The computing platform of claim 1, wherein the set of options of the customized output includes one or more offers. ### Claim 5 (depends on 1) The computing platform of claim 1, further including instructions that, when executed, cause the computing platform to: authenticate the user, including: transmitting a request for the user to capture an image of a photographic identification; receiving a captured image of the photographic identification, wherein the captured image is geo-tagged with a location; transmitting a request for the user to self-capture an image; receiving the self-captured image, wherein the self-captured image is also geo-tagged with a location; and comparing the image of the photographic identification to the self-captured image using facial recognition to determine whether the user is authenticated. ### Claim 6 (depends on 1) The computing platform of claim 1, wherein the one or more patterns of driving location is based on at least location data including a plurality of location entries corresponding to movement of the user with the mobile device, and further comprising validating the physical trait data based on the location data. ### Claim 7 (depends on 1) The computing platform of claim 1, wherein additional user data to generate the risk profile includes at least one of: medical data of the user, prescription data of the user, sensor data, and device usage data associated with the user of the mobile device. ### Claim 8 A computing device, comprising: a processing unit comprising a processor; a communication interface; and a memory unit storing computer-executable instructions, which when executed by the processing unit, cause the computing device to: execute an application on the computing device, executing the application including: initiating a communication session with a computing platform via the communication interface; displaying, by a display of the computing device, instructions for capturing one or more physical traits of a user; capturing, via one or more sensors in the computing device, the one or more physical traits of the user and driving location; transmitting, to the computing platform, the captured one or more physical traits of the user and one or more mobility patterns associated with the user based on one or more patterns of the driving location; receiving, from the computing platform, a user interface including a generated customized output that includes a set of options corresponding to a risk profile based on a pattern of decision making behavior made by the user while interacting with a vehicle at specific locations, wherein the pattern of decision making behavior is determined based on the captured one or more physical traits, the one or more mobility patterns of the user, and vehicle performance data received from one or more sensors of the vehicle associated with the user corresponding to maneuvers performed by the vehicle while being driven by the user; and displaying, by a display of the computing device, the received user interface. ### Claim 9 (depends on 8) The computing device of claim 8, wherein the one or more patterns of driving location is based on at least location data of the user including a plurality of location entries corresponding to movement of the user performed with the computing device, and further comprising validating the one or more physical traits based on the location data. ### Claim 10 (depends on 8) The computing device of claim 8, wherein the one or more physical traits of the user include one or more of: blood pressure, heart rate, and pulse. ### Claim 11 (depends on 8) The computing device of claim 8, wherein the instructions for capturing one or more physical traits of the user include instructions to capture one or more images of the user wherein the one or more images are geo-tagged with a location. ### Claim 12 (depends on 11) The computing device of claim 11, wherein capturing one or more images of the user includes executing the application to control an image capture device of the computing device. ### Claim 13 (depends on 8) The computing device of claim 8, wherein the instructions for capturing one or more physical traits of the user include instructions to perform a predefined activity for a predefined time period with the computing device. ### Claim 14 (depends on 13) The computing device of claim 13, wherein the instructions to perform the predefined activity for the predefined time period further including instructions to capture a heart rate of the user at a start of the predefined time period and at an end of the predefined time period. ### Claim 15 A method, comprising: by a computing device having at least one processor, a communication interface and a memory storing instructions that, when executed by the at least one processor, cause the processor to: execute an application on the computing device, executing the application including: initiating a communication session with a computing platform via the communication interface; displaying, by a display of the computing device, instructions for capturing one or more physical traits of a user; capturing, via one or more sensors in the computing device, the one or more physical traits of the user and driving location; transmitting, to the computing platform, the captured one or more physical traits of the user and one or more mobility patterns associated with the user based on one or more patterns of the driving location; receiving, from the computing platform, a user interface including a generated customized output that includes a set of options corresponding to a risk profile based on a pattern of decision making behavior made by the user while interacting with a vehicle at specific locations, wherein the pattern of decision making behavior is determined based on the captured one or more physical traits, the one or more mobility patterns of the user, and vehicle performance data received from one or more sensors of the vehicle associated with the user corresponding to maneuvers performed by the vehicle while being driven by the user; and displaying, by a display of the computing device, the received user interface. ### Claim 16 (depends on 15) The method of claim 15, wherein the one or more patterns of driving location is based on at least location data of the user including a plurality of location entries corresponding to movement of the user performed with the computing device, and further comprising validating the one or more physical traits based on the location data. ### Claim 17 (depends on 15) The method of claim 15, wherein the one or more physical traits of the user include one or more of: blood pressure, heart rate, and pulse. ### Claim 18 (depends on 15) The method of claim 15, wherein the instructions for capturing one or more physical traits of the user include instructions to capture one or more images of the user wherein the one or more images are geo-tagged with a location. ### Claim 19 (depends on 18) The method of claim 18, wherein capturing one or more images of the user includes executing the application to control an image capture device of the computing device. ### Claim 20 (depends on 15) The method of claim 15, wherein the instructions for capturing one or more physical traits of the user include instructions to perform a predefined activity for a predefined time period with the computing device.