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.

Abstract: The following relates generally to determining and/or displaying home scores. In some embodiments, one or more processors: (1) display, in a first portion of a display, identifying information of a home; and (2) display, in a second portion of the display: (a) an overall home score determined based upon a plurality of home subscores; (b) the plurality of home subscores comprising: a home safety subscore determined via a home safety subscore machine learning algorithm, a fire protection subscore determined via a fire protection subscore machine learning algorithm, a sustainability subscore determined via a sustainability subscore machine learning algorithm, and/or a home automation subscore determined via a home automation subscore machine learning algorithm; and (c) a relative home score comprising a comparison between the overall home score and scores of other homes.

Abstract: The following relates generally to determining and/or displaying home scores. In some embodiments, one or more processors: (1) receive imagery data; (2) determine a new device based upon the imagery data; (3) determine a home score improvement that adding the new device to the home would make for the overall home score, the home safety subscore, the fire protection subscore, the sustainability subscore, and/or the home automation subscore; and/or (4) display the home score improvement on a display.

Abstract: Systems and methods disclosed herein relates generally to using virtual reality (VR) for creating a digital twin of a home. In some embodiments, image data of a structure and an indication of a modification may be received, a virtual reality (VR) feed including a virtual representation of the modification proximate the structure may be generated, and the VR feed may be provided for presentation to a user within a VR display.

Abstract: The following relates generally to determining and/or displaying home scores. In some embodiments, one or more processors: (1) identify an upgrade and/or service to a home; (2) determine a home score improvement that the upgrade and/or service would make for an overall home score, a home safety subscore, a fire protection subscore, a sustainability subscore, and/or a home automation subscore; and/or (3) display the home score improvement along with an indication of the upgrade and/or service on a display.

Abstract: Systems and methods are described for generating and/or displaying an overall home score for a property. The method may include: retrieving one or more attributes of a property; determining one or more home score factors from the attributes; generating an overall home score; generating a neighborhood score; and displaying the overall home score, the neighborhood score and/or a map.

Abstract: Systems and methods are described for evaluating and gamifying maintenance for a property by a user. The method may include: (1) retrieving first home data for a first property and second home data for a second property, wherein a user is associated with the first property; (2) calculating, using a trained machine learning evaluation model, one or more second home score factors based upon the second home data; (3) detecting that the user is to be associated with the second property; (4) detecting, based upon the first home data and the second home data, one or more local environmental differences between the first property and the second property; and (5) generating a learning module for the user for improving or maintaining the one or more second home score factors based upon the one or more local environmental differences.

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.

Abstract: 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.

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 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.

Abstract: Systems and methods are described for generating and/or displaying an overall home score for a property. The method may include: retrieving one or more attributes of a property; determining one or more home score factors from the attributes; generating an overall home score; generating a neighborhood score; and displaying the overall home score, the neighborhood score and/or a map.

Abstract: Systems and methods are described for generating and/or displaying an overall home score for a property. The method may include: retrieving one or more attributes of a property; determining one or more home score factors from the attributes; generating an overall home score; generating a neighborhood score; and displaying the overall home score, the neighborhood score and/or a map.

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.

Abstract: 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.

Abstract: 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.

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 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.

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.

Abstract: 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.