State Farm Mutual Automobile Insurance Company

Sharon Gibson

Joshua M Mast

Taryn M Madey

Phillip Michael Wilkowski

Daniel Wilson

Jason Goldfarb

Nicholas Carmelo Marotta

David Frank

Nathan Lee Tofte

Rosemarie Geier Grant

Douglas L Dewey

Chad Junior Turner

Dustin Helland

Arsh Singh

Systems and methods are described for evaluating and analyzing home data to generate a home score. The method may include: (1) retrieving home data for a property; (2) determining, based upon the home data for the property, one or more home score factors, wherein the determining may include: (i) analyzing, using a trained machine learning data evaluation model, the home data for the property to determine home characteristic data for the property, (ii) analyzing, using the trained machine learning data evaluation model, the home data for the property to determine a likelihood of loss associated with the property, and (iii) determining, based upon the home characteristic data for the property and the likelihood of loss associated with the property; and (3) generating, based upon the one or more home score factors, a home score for the property.

Systems and methods for generating a home score for a user

Systems and methods are described for evaluating and analyzing home data to generate a home score. The method may include: (1) retrieving at least one of home data for a property or user data for a user; (2) determining, using a trained machine learning evaluation model, one or more home score factors based upon at least one of the home data or the user data; (3) receiving, from the user, a home modification indication; (4) modifying, based upon the home modification indication, at least one of the one or more home score factors to create one or more modified home score factors; and (5) generating, based upon the one or more modified home score factors, a home score for the property.

Systems and methods for generating a home score and modifications for a user

Systems and methods are described for evaluating and analyzing home data to generate a home score. The method may include: (1) retrieving home data for a first property; (2) determining, using a trained machine learning evaluation model, one or more home score factors based upon at least the home data; (3) generating, based upon the one or more home score factors, a home score for the first property; (4) retrieving past hazard data associated with a second property; and (5) generating based upon at least the past hazard data, a home modification recommendation.

A computer-implemented method for identifying whether tread of a tire of a vehicle is insufficient is presented. Image data corresponding to at least one image of the tire of the vehicle may be captured using an image sensor. The image data may be processed to determine at least one indication of a tread wear of the tire. At least one of the at least one indication of the tread wear may be analyzed based on tread wear data corresponding to the tire, with the tire being of a particular type. The tread wear data corresponding to the tire may be available to one or more processors that perform the analyzing from a provider of tires of the particular type. Based on the analyzing of the at least one of the at least one indication of the tread wear, it may be identified whether the tread of the tire is insufficient.

System and method for using image data to determine tire quality

A siding evaluation apparatus for use in identifying a characteristic of building siding is disclosed, together with methods and systems for identifying a characteristic of building siding using the siding evaluation apparatus. The siding evaluation apparatus includes a protrusion, clip, or other means for removably attaching to building siding by friction or pressure. The siding evaluation apparatus further includes a color chart holder adapted to hold a color chart for reference. The siding evaluation apparatus is attached to the siding and may be adjusted to display the color chart, which may be photographed together with a portion of the siding. Characteristics of the siding may then be determined based upon the captured photograph and a known reference area of the color chart.

Siding evaluation apparatus and method

Methods and systems for identifying an unidentified plumbing supply product are provided. According to certain aspects, an application executing on an electronic device may be configured to capture image data encoding an image of the unidentified plumbing supply product therein. The application may cause the electronic device to transmit the image data to an identification server. The identification server may analyze the image data to determine the unidentified plumbing supply product encoded in the image data matches a known plumbing supply product in a plumbing supply products database. The identification server may then transmit an indication to the electronic device that the unidentified plumbing supply product was successfully identified. The identification of the unidentified plumbing supply product may be used to process and/or subrogate an insurance claim.

Systems and methods for identifying unidentified plumbing supply products

In a computer-implemented method of roofing material identification, image data corresponding to one or more images of roofing materials may be received. The image data may be processed to determine pertinent characteristics of the roofing materials. The determined characteristics and a characteristics database storing data indicative of associations between a plurality of roofing material products and characteristics of the plurality of roofing material products, may be used to identify a roofing material product associated with the pertinent characteristics. An indication of the identified roofing material product may be provided (e.g., to facilitate claim processing).

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Carlock, IL, United States of America

Sharon Gibson