Systems and methods for identifying ancillary home costs

    公开(公告)号:US11972499B2

    公开(公告)日:2024-04-30

    申请号:US18309387

    申请日:2023-04-28

    CPC classification number: G06Q50/16 G06F3/048 G06Q30/0283 G06Q40/03 G06Q40/08

    Abstract: A home cost analysis server is configured to train an image processing program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the machine-learned image processing program, which outputs a feature of the prospective home, access a second database storing historical ancillary costs, and perform a lookup in the second database to retrieve comparable historical ancillary costs associated homes having a comparable feature to the outputted feature. The server is further configured to analyze the metadata associated with the prospective home, the outputted feature, and the comparable historical ancillary costs to determine ancillary home costs associated with the prospective home, and display the ancillary home costs and an overall monthly cost for the prospective home.

    USING STANDBY GENERATOR CONFIGURATION DATA TO DETERMINE DATA ASSOCIATED WITH TERMS OF RESIDENTIAL INSURANCE COVERAGE

    公开(公告)号:US20210326990A1

    公开(公告)日:2021-10-21

    申请号:US15339527

    申请日:2016-10-31

    Abstract: A computer-implemented method of providing insurance discounts to risk averse home owners having standby generators. The method may include, with customer permission or affirmative consent, (1) receiving, at an insurance provider remote server, data that is indicative of whether a standby generator is associated with a home; (2) receiving, at the insurance provider remote server, data indicative of an amount of the home to which the standby generator is configured to supply power; and (3) determining data associated with the terms of the residential insurance coverage for the home based upon the data indicative of whether the standby generator is associated with the home and/or the data indicative of the amount of the home to which the standby generator is configured to supply power. The standby generator data may be generated or collected by a smart home controller, and transmitted to the insurance provider via wireless communication, for instance.

    Using standby generator data to determine data associated with terms of residential insurance coverage

    公开(公告)号:US10991050B1

    公开(公告)日:2021-04-27

    申请号:US15339450

    申请日:2016-10-31

    Abstract: A computer-implemented method of providing insurance discounts to risk averse home owners having standby generators. The method may include, with customer permission or affirmative consent, (1) receiving, at an insurance provider remote server, data that is indicative of whether a standby generator is associated with a home; (2) receiving, at the insurance provider remote server, data indicative of the current operational condition of the standby generator; and (3) determining, by the insurance provider remote server, data associated with the terms of the residential insurance coverage for the home based upon the data indicative of whether the standby generator is associated with the home and the data indicative of the current operational condition of the standby generator. The standby generator data may be generated or collected by a smart home controller, and transmitted to the insurance provider via wireless communication over one or more radio links or communication channels, for instance.

    SYSTEMS AND METHODS FOR IDENTIFYING ANCILLARY HOME COSTS

    公开(公告)号:US20240265477A1

    公开(公告)日:2024-08-08

    申请号:US18635775

    申请日:2024-04-15

    CPC classification number: G06Q50/16 G06F3/048 G06Q30/0283 G06Q40/03 G06Q40/08

    Abstract: A home cost analysis server is configured to train a machine-learning program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the trained machine-learning program, which outputs a feature of the prospective home, access a second database storing historical additional costs, and perform a lookup in the second database to retrieve comparable historical additional costs associated homes having a comparable feature to the output feature. The server is further configured to analyze the metadata associated with the prospective home, the output feature, and the comparable historical additional costs to determine additional home costs associated with the prospective home, and output the additional home costs and an overall monthly cost for the prospective home.

    SYSTEMS AND METHODS FOR IDENTIFYING ANCILLARY HOME COSTS

    公开(公告)号:US20230298115A1

    公开(公告)日:2023-09-21

    申请号:US18309387

    申请日:2023-04-28

    CPC classification number: G06Q50/16 G06F3/048 G06Q30/0283 G06Q40/03 G06Q40/08

    Abstract: A home cost analysis server is configured to train an image processing program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the machine-learned image processing program, which outputs a feature of the prospective home, access a second database storing historical ancillary costs, and perform a lookup in the second database to retrieve comparable historical ancillary costs associated homes having a comparable feature to the outputted feature. The server is further configured to analyze the metadata associated with the prospective home, the outputted feature, and the comparable historical ancillary costs to determine ancillary home costs associated with the prospective home, and display the ancillary home costs and an overall monthly cost for the prospective home.

    USING HOME TELEMATICS DATA TO IDENTIFY RECOMMENDATIONS ASSOCIATED WITH HOME WARRANTY PRODUCT COVERAGE

    公开(公告)号:US20240393776A1

    公开(公告)日:2024-11-28

    申请号:US16158513

    申请日:2018-10-12

    Abstract: Techniques are disclosed to monitor home telematics data to identify the overall health of home devices to be covered, or that are currently covered, by a home warranty. The home telematics data may include information relating to the electrical usage of various home devices, which may be obtained via an electrical monitoring (EM) device. Using the home telematics data, a home warranty provider may identify the current health of home devices, identify signs of early failure, suggest recommended preventative maintenance, and/or allocate a portion of the premium payments to carrying out the preventative maintenance. Thus, by leveraging collected home telematics data and tracking this data over time, a home warranty provider may accurately price home warranties, mitigate risk, and potentially prevent costlier claims by anticipating and addressing issues before repairs are needed.

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