Abstract: The following relates generally to building a ground truth insurance database. In some embodiments, one or more processors: (1) receive potential insurance database information comprising (i) insurance company application (app) information, (ii) anonymized insurance claim information, (iii) police report information, and/or (iv) auxiliary information; (2) retrieve, from an insurance ground truth insurance database, existing ground truth insurance information by querying the ground truth database based upon the potential insurance database information; (3) determine if the potential insurance database information should be added to the insurance ground truth database by comparing the potential insurance database information to the existing ground truth insurance information; and/or (4) if the potential insurance database information should be added to the insurance ground truth database, add the potential insurance database information to the insurance ground truth database.

Abstract: The following relates generally to using artificial intelligence (AI) and/or machine learning (ML) to recommend a change in insurance coverage. In some embodiments, one or more processors: receive customer information of an insurance customer; determine that an insurance change recommendation trigger has occurred by routing the customer information into an insurance recommendation machine learning and/or artificial intelligence algorithm; and in response to determining the insurance change recommendation trigger, send a recommendation for an insurance policy change for the insurance customer.

Abstract: The following relates generally to aiding underwriting and insurance agents. In some embodiments, one or more processors: (1) receive, with an AI chatbot (or voice bot) of the one or more processors, an input statement; (2) determine, with the AI chatbot, from the received input statement, a type of insurance policy; (3) determine, with the AI chatbot, from the input statement, a question corresponding to the type of insurance policy; (4) determine, with the AI chatbot, an answer to the question by retrieving insurance information based upon (i) the type of insurance policy, and/or (ii) the question; and/or (5) present, via the AI chatbot, the answer to the question.

Abstract: A computer system for providing group insurance plans may be provided. The computer system may include a processor in communication with a memory device, and the processor may be configured to: (i) receive registration data associated with a group of users including a list of users included in the group and user data from each user; (ii) generate a plurality of predesignated insurance personal mobility policy plans or usage-based insurance plans for the group including a predesignated coverage amount and a corresponding premium amount over a predesignated time period; (iii) prompt a user of the group to select a predesignated policy; (iv) store the selected predesignated policy along with the group registration data; (v) receive mobility data after each trip of each user of the group; (vi) adjust the selected coverage amount based upon the mobility data; and/or (vii) determine a current coverage amount based upon the adjusted coverage amount.

Abstract: Techniques for detecting damage to a roofing structure and initiating remediation procedures are disclosed herein. An exemplary computer-implemented method may include receiving sensor data from a plurality of sensors located proximate to the roofing structure to monitor a plurality of environmental conditions. The exemplary method may include (1) identifying, by one or more processors, a type of damage within the roofing structure based upon the sensor data; (2) locating a position of the damage within the roofing structure; determining a set of remediation services based upon the type of damage; and (3) identifying one or more remediation service providers to perform the set of remediation services. The exemplary method may include generating and transmitting an alert signal to a computing device identifying the type of damage to the roofing structure and contact information corresponding to at least one or more remediation service providers.

Abstract: Methods and systems for providing emergency heating in an electric vehicle (EV) running out of power are described herein. An on-board computer or mobile device in an EV may determine that an amount of charge remaining for powering the EV is below a threshold charge level. The on-board computer or mobile device may then route the remaining amount of charge to power a heating system in the EV to maintain a temperature in the EV above a threshold temperature level, and shut down power to other components within the EV.

Abstract: The following relates generally to implementing a medical data non-fungible token (NFT). In some embodiments, one or more processors receive medical data of a plurality of users, and store the medical data of the plurality of users in a first storage location in a medical data database. The one or more processors may then detect a request to purchase a data feed for one or more types of medical data, and identify medical data corresponding to the request in the medical data database. The one or more processors may then store the identified medical data in a second storage location, and mint a medical data NFT that indicates the second storage location.

Abstract: A user analytics computing device for processing mobile device telematics data includes a processor in communication with a memory device. The processor is programmed to: (i) store a model to predict a travel mode for a user based upon historical telematics data, (ii) form a first group by assigning a user to the first group, (iii) receive telematics data associated with movement of the user, (iv) input the telematics data into the model to determine a travel mode of the user, (v) parse subsets of the telematics data based upon the determined travel modes, (vi) retrieve an eligibility condition defining eligibility to qualify for a user offering, (vii) aggregate one subset of the telematics data associated with the first travel mode of the user, (viii) determine that the group telematics data satisfies the eligibility condition, and (ix) cause a notification to be displayed on the mobile device of the user.

Abstract: Embodiments described herein receive telematics data collected over a period of time, wherein the telematics data is indicative of operation of a vehicle by an owner of the vehicle during the period of time; analyze the telematics data to identify driving behavior(s) of the owner during the period of time; predict one or more user preference values of a vehicle-sharing platform profile of the owner based on the identified one or more driving behaviors, wherein the one or more user preference values define one or more criteria for vehicle renters with whom the first vehicle can be shared; apply the one or more criteria to a potential vehicle renter; and cause an indication of the first vehicle of the owner to be displayed via a mobile device of the potential renter only if the potential vehicle renter satisfies the one or more criteria.

Abstract: Embodiments described herein, inter alia, receive telematics data collected over a period of time, wherein the telematics data is indicative of operation of a vehicle by a potential renter during the period of time; identify, upon analyzing the telematics data, driving behavior(s) of the renter during the period of time; determine, for each driving behavior, a corresponding state of an environment of the vehicle when the driving behavior occurred; determine renter eligibility value(s) for the renter based on the driving behavior(s) and the corresponding state of an environment of the vehicle; compare the renter eligibility value(s) to user preference value(s) of a profile of a vehicle owner, wherein the user preference value(s) define one or more criteria for vehicle renters with whom the vehicle can be shared; and cause an indication of the vehicle associated with the profile to be displayed only if the renter satisfies the criteria.

Abstract: Techniques are described herein for detecting status changes to fluid flow devices. An exemplary computer-implemented method may include (1) receiving, from a sensor disposed proximate to a fluid flow device, a vibration signal; (2) determining a current flow rate within the fluid flow device based upon the vibration signal; (3) detecting a status change of the fluid flow device based upon a comparison between the current flow rate and a prior flow rate; (4) determining a recommended remediation action to adjust the current flow rate to the prior flow rate; and (5) generating an alert signal indicating the status change and the recommended remediation action.

Abstract: A vehicle analytics (VA) computing device may be configured to: (i) receive, from the connected vehicle, telematics data corresponding to the connected vehicle; (ii) identify a plurality of trips of the vehicle based upon the telematics data; (iii) store the telematics data corresponding to each trip of the plurality of trips in a database in association with a trip identifier corresponding to the trip; (iv) determine, for each of the plurality of trips, a number of passengers present in the vehicle; (v) store the determined number of passengers in the database in association with the trip identifier corresponding to the trip; and (vi) calculate an insurance premium associated with an insurance policy based upon the determined number of passengers in the vehicle.

Abstract: Described herein are methods and systems for generating and applying vehicle maintenance models to vehicle telematics data. A vehicle telematics analytics (VTA) computing device is configured to receive vehicle telematics data associated with operation of a subject vehicle, and apply the received vehicle telematics data to a vehicle maintenance model to determine whether the operation of the subject vehicle is better or worse than standard operation of like vehicles. The VTA computing device may adjust a maintenance cost and/or determine if a user of the vehicle is eligible for a reward based upon this determination. The VTA computing device is configured to transmit an itemized report to the user including the adjusted maintenance cost and/or the reward as well as one or more other vehicle costs.

Abstract: Techniques for detecting water hazard conditions proximate to a structure are disclosed herein. An exemplary computer-implemented method may include receiving, from a sensor disposed proximate to the structure, a water level signal, and determining a water level proximate to the structure based upon the water level signal. The exemplary computer-implemented method may further include detecting, by executing a water hazard model, a water hazard condition based upon the water level proximate to the structure, and determining (i) a recommended mitigation action to mitigate damage to the structure from the water hazard condition and (ii) a cause of the water hazard condition. The exemplary computer-implemented method may further include generating an alert signal indicating the water hazard condition and the recommended mitigation action.

Abstract: Techniques for determining health statuses of devices within a structure are disclosed herein. An exemplary computer-implemented method includes receiving, at one or more processors, usage data corresponding to a device associated with the structure. The usage data may include at least electrical consumption data of the device. The exemplary method may further include determining, by the one or more processors, a usage level of the device based upon the usage data, and determining, by the one or more processors utilizing a device health model, a health status of the device based upon the usage level. The exemplary method may further include generating, by the one or more processors, a recommended usage adjustment for the device based upon the health status; and causing, by the one or more processors, the recommended usage adjustment to be displayed to a user.

Abstract: Techniques for detecting emergency conditions within structures and initiating remediation procedures are disclosed herein. An exemplary computer-implemented method may include detecting, by one or more processors, an emergency condition within a structure; and determining, by the one or more processors, a set of remediation services corresponding to the structure based upon the emergency condition. The exemplary computer-implemented method may further include identifying, by the one or more processors, one or more remediation service providers to perform the set of remediation services; and generating, by the one or more processors, a remediation alert signal that includes contact information corresponding to at least one of the one or more remediation service providers. The exemplary computer-implemented method may further include transmitting, by the one or more processors, the remediation alert signal to a user computing device of a user associated with the structure.

Abstract: Systems and methods for generating a virtual synthetic representative based upon a person or user are disclosed. Personal data associated with a person is collected, including personal data regarding a past communication of the person. One or more attributes indicative of personal mannerisms of the individual person are identified from the personal data. A synthetic virtual representative profile is then created from the identified personal mannerisms, and a synthetic virtual representative is virtually constructed based upon the virtual representative profile. The synthetic representative construction including a visual representation of the representative in a virtual environment.

Abstract: Systems and methods for generating personalized virtual content for a user of a virtual experience system are disclosed. Personal data associated with a customer or a user of a virtual experience device is collected, and a set of keywords representative of customer characteristics is identified from the personal data. Virtual content is generated using a machine learning model trained to generate personalized virtual content based upon keywords. The personalized virtual content is generated based upon the set of keywords representative of the customer characteristics. The personalized virtual content is provided via the virtual experience device to the customer or user in a virtual environment.

Abstract: An on-demand insurance (ODI) server for generating dynamic user offerings may be provided. The ODI server may include at least one processor in communication with a memory device. The at least one processor may be programmed to (i) receive, from a user computing device associated with a user, an insurance policy request for a trip from a start location to an end location, (ii) determine at least one transportation mode available for the trip, (iii) access contextual data associated with the trip, (iv) assess a risk associated with the at least one transportation mode, (v) calculate a risk score associated with the at least one transportation mode based upon at least the contextual data, (vi) generate an insurance offering associated with the at least one transportation mode, and/or (vii) transmit the insurance offering in real time to the user computing device for purchase by the user.

Abstract: In a method for applying penalties or incentives to a driver of a rented vehicle, an indication that the driver has agreed to terms for renting the vehicle from the vehicle owner is received, with the terms including the potential application of penalties or incentives to the driver based on driving behavior. Telematics data, indicative of operation of the rented vehicle by the driver during a period of time, is also received. By analyzing the telematics data, one or more driving behaviors of the driver during the time period is/are identified. One or more characteristics of the rented vehicle are also determined. One or more penalties or incentives are caused to be applied to the driver, based on the driving behavior(s) and the one or more characteristics of the rented vehicle.