Systems and Methods for Generating a Home Score for a User Using a Home Score Component Model

    公开(公告)号:US20230342869A1

    公开(公告)日:2023-10-26

    申请号:US17973099

    申请日:2022-10-25

    IPC分类号: G06Q50/16

    CPC分类号: G06Q50/16

    摘要: Systems and methods are described for analyzing home data to generate a home score. The method may include: retrieving home data for a first property; determining that the first property shares home characteristics with a second property; retrieving past hazard data associated with the second property; determining, based upon at least the home data and the past hazard data, one or more first home score factors, wherein the determining includes: analyzing, using a trained machine learning data evaluation model, the home data to determine home characteristic data for the first property, determining second home score factors for the second property based at least upon the past hazard data, and determining, based upon the home characteristic data and the second home score factors, the one or more first home score factors; and generating, based upon the one or more first home score factors, a home score for the first property.

    SENIOR LIVING ENGAGEMENT AND CARE SUPPORT PLATFORMS WITH CHATBOT AND LIST INTEGRATION

    公开(公告)号:US20220245593A1

    公开(公告)日:2022-08-04

    申请号:US17587928

    申请日:2022-01-28

    IPC分类号: G06Q10/10 G16H40/67

    摘要: Provided herein is an engagement and care support platform (“ECSP”) computer system including at least one processor in communication with at least one memory device for facilitating senior user engagement. The processor is programmed to: (i) register a user through an application, (ii) register a caregiver associated with the user through the application, (iii) generate a senior profile based upon user personal and scheduling data, (iv) build a daily interactive user interface that reflects the senior profile, (v) display the daily interactive user interface at a first client device associated with the user, (vi) cause the first client device to initiate a daily interaction prompt to the user, (vii) determine whether any user interaction was received in response to the daily interaction prompt, and (viii) transmit a daily update message to a second client device associated with the caregiver, including an indication of whether any user interaction was received.

    Systems and Methods for Generating a Home Score for a User

    公开(公告)号:US20230342868A1

    公开(公告)日:2023-10-26

    申请号:US17972261

    申请日:2022-10-24

    IPC分类号: G06Q50/16

    CPC分类号: G06Q50/16

    摘要: 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

    公开(公告)号:US20230342867A1

    公开(公告)日:2023-10-26

    申请号:US17816379

    申请日:2022-07-29

    IPC分类号: G06Q50/16

    CPC分类号: G06Q50/16

    摘要: 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.