Abstract: Systems and methods disclosed herein relate generally to using augmented reality (AR) for receiving and displaying recommended devices proximate a structure. In some examples, underlay layer data may be received (e.g., from a camera of an AR viewer device); and overlay layer data may be received (e.g., from a different camera or other overlay layer device). An AR display may be created by correlating the underlay layer data with the overlay layer data. An improved home score indicia may be displayed based upon the recommended device.

Abstract: Systems and methods for initiating an action to improve a condition of a domicile may include (1) receiving, from one or more mobile sensors, a plurality of different types of residential data associated with at least one component or space of the domicile, the plurality of different types of residential data collected by the sensors as the sensors move about at least a portion of the domicile; (2) determining, by processing the plurality of different types of residential data using a machine learning model, at least one of a condition or a status of a device or a system of the domicile, the machine learning model trained to establish a correlation between (i) a subset of the different types of residential data, and (ii) at least one of a condition or a status of a device or system; and (3) initiating the action to improve the condition of the domicile.

Abstract: In various examples, computer systems and computer-implemented methods interface with a plurality of Internet of Things (IoT) devices within a local network of a residential building using one or more artificial intelligence (AI) models. The system may (i) receive at least one transmission of an IoT device of a plurality of IoT devices connected within the local network; (ii) determine, using the at least one transmission, at least one of a protocol, a command, or a data format of the IoT device; (iii) generate and store a device dataset including at least one of the protocol, the command, or the data format of the IoT device; (iv) receive, via a user interface, a natural language input corresponding to the IoT device; and/or (v) generate a natural language response to the natural language input using retrieval-augmented generation.

Abstract: Systems and methods disclosed herein relates generally to using augmented reality (AR) for visualizing recommended updates to devices proximate a structure. In some examples, underlay layer data may be received (e.g., from a camera of an AR viewer device); and overlay layer data may be received (e.g., from a different camera or other overlay layer device). An AR display may be created by correlating the underlay layer data with the overlay layer data. An improved home score indicia may be displayed based upon the recommended update.

Abstract: Systems and methods disclosed herein relates generally to using augmented reality (AR) for visualizing recommended updates to devices proximate a structure. In some examples, underlay layer data may be received (e.g., from a camera of an AR viewer device); and overlay layer data may be received (e.g., from a different camera or other overlay layer device). An AR display may be created by correlating the underlay layer data with the overlay layer data. An improved home score indicia may be displayed based upon the recommended update.

Abstract: A computer system configured to recommend home projects while also identifying a homeowner's level of expertise for implementing the projects. The system may be configured to: (i) cause display of a first interface view of a frontend application to receive inputs for generating profiles of a home and the homeowner; (ii) determine a homeowner-personality type and a current level of the homeowner-personality type using the received inputs, including available features or functionalities at the home, and home improvement projects; (iii) generate a list of actions for the homeowner to take to move to a higher level for the determined homeowner-personality type; and/or (iv) cause display of a second interface view displaying the determined homeowner-personality type, the current level of the homeowner-personality type, and the list of actions to move to the higher level for determined homeowner-personality type.

Abstract: Systems and methods disclosed herein relate generally to using augmented reality (AR) for receiving and displaying recommended devices proximate a structure. In some examples, underlay layer data may be received (e.g., from a camera of an AR viewer device); and overlay layer data may be received (e.g., from a different camera or other overlay layer device). An AR display may be created by correlating the underlay layer data with the overlay layer data. An improved home score indicia may be displayed based upon the recommended device.

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: 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: 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: Systems and methods disclosed herein relates generally to using augmented reality (AR) for visualizing recommended updates to devices proximate a structure. In some examples, underlay layer data may be received (e.g., from a camera of an AR viewer device); and overlay layer data may be received (e.g., from a different camera or other overlay layer device). An AR display may be created by correlating the underlay layer data with the overlay layer data. An improved home score indicia may be displayed based upon the recommended update.

Abstract: The following relates generally to determining and/or displaying home scores. In some embodiments, one or more processors: (1) determine at least one of an overall home score, a home safety subscore, a fire protection subscore, a sustainability subscore, and/or a home automation subscore for a home; (2) identify a device; (3) determine a home score improvement that adding the 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, and/or otherwise visually, graphically, textually, audibly, or verbally outputting the home score improvement, such as via a processor, screen, voice bot, chatbot, or other bot.

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 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 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 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) receiving home telematics data associated with a property for a user; (2) analyzing, according to a machine learning model, the home telematics data to determine age data for one or more components of the property, wherein the one or more components of the property are associated with a structural integrity of the property; (3) determining, based upon at least the determined age data, a home health indicator for the property, wherein the home health indicator for the property is associated with a determined age for the property; and (4) generating, based upon at least the determined home health indicator, 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.