State Farm Mutual Automobile Insurance Company

Craig Benjamin Cope

Mark E Clauss

Douglas Albert Graff

Nathan Wilhelm Baumann

Megan Michal Baumann

Thomas Michael Potter

Curtis Simpson

Dustin Ryan Carter

Atlanta Bonnom

Jennifer Luella Lawyer

Kristopher Keith Gaudin

Justin Davis

Aaron C Williams

Joseph P Harr

Andrew Joseph Zeglin

Ryan Michael Gross

Steve J Balbach

Jeff Riblet

Burton J Floyd

Michael K Cook

Jessica Lynn Shull

Melissa C Miles

Kevin Joseph Alcozar

Emily Kate Schneider

Kara Lynn Heuer

Vicki King

Jeffrey Wilson Stoiber

Matthew Lewis Floyd

Jennifer L Crawford

Edward W Breitweiser

Christopher N Kawakita

Steven Joseph Balbach

Rick Lovings

Daryoush Hakimi

Embodiments of extended reality (XR) methods and systems for handling home-related information are disclosed. In one embodiment, a computer-implemented method may include (1) obtaining one or more XR preferences for a party; (2) presenting, using one or more devices associated with the party instructions constructed to guide the party to move throughout or around a real property, and prompts constructed to direct the party to capture data representing one or more of the real property or belongings; (3) determining, by one or more processors processing the captured data, asset data representing one or more of the real property or the belongings; and/or (4) presenting, in a virtualized environment in accordance with the party's XR preferences via an XR device, one or more visual depictions of the determined asset data such that the party or an insurance representative can at least one of view, modify, or approve the asset data.

Extended reality methods and systems for collecting, managing, and using home-related information

A system and computer-implemented method detect and act upon deactivated vehicle components. The system and method include receiving measurements data associated with driving activity. The measurements data includes an indication that at least one feature of an Advanced Driver Assistance System (ADAS) of a vehicle has been deactivated for a driving activity. The system and method may include receiving historical driving data including a history of at least one driving activity aided by activation of the alert from the ADAS feature. The system and method may compare the measurements data to the historical driving data, determine a likelihood level that the feature of the ADAS would have provided the alert had the feature been activated based upon the comparing, and set, based at least upon the determining, at least a portion of an operator profile associated with an operator of the vehicle with the likelihood level.

Automatically tracking driving activity

A method of driver behavior that includes generating, by a mobile device located inside a vehicle, telematics data associated with operation of the vehicle, and transmitting, from the mobile device to one or more processors via wireless communication, the telematics data in real-time. The method also includes analyzing the telematics data to determine whether a driving score for a driver, determining whether the driving score is greater than a threshold value, determining a discount based upon the driving score being higher than the threshold, and generating a communication based upon the discount. The method further includes transmitting the communication.

Methods of facilitating emergency assistance

A system and method may collect telematics and/or other data, and apply the data to insurance-based applications. From the data, an insurance provider may determine accurate vehicle usage information, including information regarding who is using a vehicle and under what conditions. An insurance provider may likewise determine risk levels or a risk profile for an insured driver (or other drivers), which may be used to adjust automobile or other insurance policies. The insurance provider may also use the data collected to adjust behavior based insurance using incentives, recommendations, or other means. For customers that opt-in to the data collection program offered, the present embodiments present the opportunity to demonstrate a low or moderate risk lifestyle and the chance for insurance-related savings based upon that low or moderate risk.

Methods of providing insurance savings based upon telematics and driving behavior identification

A method of vehicle accident response includes generating, by a mobile device located inside a vehicle, telematics data associated with operation of the vehicle, and transmitting, from the mobile device to one or more processors via wireless communication, the telematics data. The method also includes analyzing the telematics data to determine that an accident involving the vehicle has occurred, analyzing the telematics data to determine a likelihood of injury due to the accident, and generating a communication (i) based upon the telematics data and the likelihood of injury and (ii) in response to determining that the accident has occurred. The method further includes transmitting, to the mobile device, the communication.

In system and methods for pre-generating insurance claims, accident data associated with a vehicle accident involving a driver may be collected. The accident data may be analyzed, and a likely severity of the vehicle accident may be determined based upon the analysis of the accident data. An estimated insurance claim may be generated based upon the determined likely severity of the vehicle accident, and transmitted, via wireless communication, from one or more remote servers to a mobile device associated with the driver to facilitate presenting all, or a portion of, the estimated insurance claim to the driver or the insured. A wireless communication from the driver or insured indicating approval, rejection or modification of the estimated insurance claim may be received. The estimated insurance claim may be handled in accordance with the approval, rejection or modification.

Methods of pre-generating insurance claims

In system and methods for loss mitigation, accident data associated with a vehicle accident involving a driver may be collected. The accident data may be analyzed, and a likely severity of the vehicle accident may be determined based upon the analysis of the accident data. A communication related to emergency assistance or an emergency assistance recommendation may be generated based upon the determined likely severity of the vehicle accident, and transmitted, via wireless communication, from one or more remote servers to a mobile device associated with the driver. A wireless communication from the driver indicating approval or modification of the emergency assistance or emergency assistance recommendation may be received. A third party may be notified, via a communication sent from the remote server(s), of requested emergency assistance as approved or modified by the driver. An estimated insurance claim may also be generated based upon vehicle accident likely severity.

Systems and methods relating to usage of multimodal transportation systems are disclosed. Such systems and methods may identify available local transportation modes for a user, such as vehicle-sharing, ridesharing, rental vehicles, taxicabs, owned vehicles, or public transit options. The available transportation modes may be compared, and recommendations may be presented to the user. Routes may be identified, compared, or recommended to a user, and scheduling or ticket purchasing may be facilitated. With user permission, user transportation data may be collected via a smartphone to identify user transportation patterns and preferences, thereby improving recommendations regarding and assessment of user transportation. Information regarding risks or other relevant factors associated with various transportation modes may be assessed for a user based upon typical characteristics of user transportation choices over a plurality of transportation scenarios, which may be indicated by a user transportation profile.

Systems and methods of monitoring and analyzing multimodal transportation usage

A building analysis ('BA') system for detecting events of a building includes a plurality of sensors positioned within a building, a memory device including an optimal profile of an infrastructure to be monitored, and a building analysis (“BA”) server communicatively coupled to the plurality of sensors. The infrastructure is at least one of (i) a fixture associated with the building and (ii) at least one person located within the building. The BA system includes one or more processors in communication with the memory that are programmed to: (i) receive sensor data related to the infrastructure, (ii) compare the sensor data to the optimal profile to detect an event, (iii) generate an alert message including the event and a recommended action for an owner of the building, (iv) transmit the alert message to a user computing device associated with the owner, and (v) take or direct corrective actions.

Systems and methods for detecting building events and trends

A system and computer-implemented method detect and act upon operator reliance to vehicle alerts. The system and method include receiving user profile data of an operator that includes a baseline of at least one driving activity aided by activation of an alert from a feature of an Advanced Driver Assistance System (ADAS). The system and method may include receiving historical ADAS alert frequency data including a history of at least one driving activity aided by activation of the alert from the ADAS feature. The system and method may compare the user profile data with the historical ADAS alert frequency data, determine a reliance level based upon the comparing, and set at least a portion of an operator profile associated with the operator with the reliance level. As a result, a risk averse driver, and/or proper responsiveness to vehicle alerts may be rewarded with insurance-cost savings, such as increased discounts.

Evaluating operator reliance on vehicle alerts

A building analysis ('BA') system for detecting events of a building includes a plurality of sensors positioned within a building, a memory device including an optimal profile of an infrastructure, and a building analysis ('BA') server communicatively coupled to the plurality of sensors. The infrastructure is at least one of (i) a fixture associated with the building and (ii) at least one person located within the building. The BA system includes one or more processors in communication with the memory that are programmed to: (i) receive sensor data related to the infrastructure, (ii) compare the sensor data to the optimal profile to detect an event, (iii) determine a recommended action based upon the detected event, (iv) execute the recommended action to mitigate at least one of damage caused by the detected event to the building and injury caused by the detected event to the at least one person.

A transportation analytics (TA) computing device may be provided. The TA computing device may include at least one processor and/or associated transceiver. The at least one processor and/or associated transceiver may be configured to: (1) receive, from a user mobile device, telematics data including an indicator that the user mobile device is communicatively linked to a transportation device; (2) identify each period that the user mobile device is communicatively linked to a transportation device as a trip using the transportation device; (3) store, the telematics data in a database in association with a trip identifier corresponding to the identified trips and a time stamp; (4) perform a lookup in the database to identify, based upon the timestamps, telematics data corresponding to a time period; and/or (5) calculate, based upon the identified telematics data, a premium amount for insuring the user during the trips taken during the time period.

Transportation analytics systems and methods using a mobility device embedded within a vehicle

A transportation analytics (TA) computing device may be provided. The TA computing device may include at least one processor in communication with at least one memory device. The at least one processor may be configured to: (1) receive, from a user mobile device corresponding to a user, telematics data corresponding to a trip taken using a transportation platform; (2) store, for each trip, the telematics data in a database in association with a trip identifier and a timestamp; (3) perform a lookup in the database to identify, based upon the timestamps, telematics data corresponding to a time period; (4) calculate, in response to identifying the telematics data, based upon the identified telematics data, a premium amount; and/or (5) transfer, in response to calculating the premium amount, the premium amount from a transportation platform account associated with the transportation platform to an insurer account associated with an insurer.

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Bloomington, IL, United States of America

Craig Benjamin Cope