Systems and Methods for Generating a Home Score for a User

    公开(公告)号:US20230342867A1

    公开(公告)日:2023-10-26

    申请号:US17816379

    申请日:2022-07-29

    CPC classification number: G06Q50/16

    Abstract: 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 identifying unidentified plumbing supply products

    公开(公告)号:US10412169B1

    公开(公告)日:2019-09-10

    申请号:US15852268

    申请日:2017-12-22

    Abstract: 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.

    Method for field identification of roofing materials
    14.
    发明授权
    Method for field identification of roofing materials 有权
    屋顶材料现场识别方法

    公开(公告)号:US09582832B1

    公开(公告)日:2017-02-28

    申请号:US14841810

    申请日:2015-09-01

    CPC classification number: G06Q40/08

    Abstract: 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).

    Abstract translation: 在屋顶材料识别的计算机实现方法中,可以接收对应于屋顶材料的一个或多个图像的图像数据。 可以处理图像数据以确定屋顶材料的相关特性。 所确定的特征和特征数据库可以存储指示多个屋顶材料产品和多个屋顶材料产品的特性之间的关联的数据,以识别与相关特征相关的屋顶材料产品。 可以提供识别的屋顶材料产品的指示(例如,以便于索赔处理)。

    Systems and Methods for Generating a Home Score and Modifications for a User

    公开(公告)号:US20240273637A1

    公开(公告)日:2024-08-15

    申请号:US18643603

    申请日:2024-04-23

    CPC classification number: G06Q40/08

    Abstract: Systems and methods are described for evaluating and gamifying maintenance for a property by a user. The method may include: (1) retrieving home data for a first property; (2) determining, using a first 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) determining, using a second trained machine learning evaluation model, that one or more additional properties are similar to the first property; (5) retrieving past hazard data associated with a second property of the one or more additional properties; and (6) generating, based upon at least the past hazard data and at least one of the one or more home score factors, a learning module for the first property.

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