Abstract: Method and system for providing carbon offsets. For example, the method includes collecting mindful driving data for one or more vehicle trips made by a user, analyzing the mindful driving data to determine a level of mindful driving of the user, determining a level of carbon offset reward based at least in part upon the level of mindful driving of the user, determining an amount of total carbon emission of the user, and providing an amount of carbon offset reward based at least in part upon the level of carbon offset reward and the amount of total carbon emission.

Abstract: Method and system for generating a personalized landing page for a user are disclosed. For example, the method includes receiving, by a computing device, one or more user data associated with the user, the one or more user data including one or more telematics data of the user, determining, by the computing device, one or more user interface features based at least in part upon the one or more user data, and generating, by the computing device, a personalized landing page customized for the user using the one or more user interface features to increase an effectiveness of the personalized landing page.

Abstract: A telematics analysis (TA) computing device including a processor in communication with a memory device for monitoring driving behavior of a driver of a vehicle may be provided.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: determining a first real-world user based at least in part upon first real-world telematics data associated with the first real-world user; generating one or more first virtual experiences based at least in part upon one or more first real-world driving behaviors; generating a first virtual character; and presenting the one or more first virtual experiences in a virtual game to the first real-world user, wherein the one or more first virtual experiences include one or more first virtual obstacles to be encountered by the first virtual character in the virtual game based at least in part upon the one or more first real-world driving behaviors. Other embodiments are described.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: receiving telematics data from a mobile device during one or more vehicle trips including a previous epoch for a driver and a current epoch for the driver; generating a previous epoch score for the driver based on the telematics data of the previous epoch for the driver; generating, using a trained machine learning model, a predicted epoch score for the driver based on the telematics data of the current epoch for the driver; generating a hybrid epoch score for the driver from at least portions of the previous epoch score for the driver and the predicted epoch score for the driver; and transmitting the hybrid epoch score for the driver. Other embodiments are described.

Abstract: A smart ring includes a housing. The smart ring also can include a power source disposed within or at the housing. The power source can be configured to receive energy. The smart ring can further include a controller disposed within or at the housing. The power source also can be configured to power the controller. The controller can be configured to estimate a charging status for the power source. The controller also can be configured to generate information to indicate the charging status. Other embodiments are disclosed.

Abstract: Systems and methods are provided for determining a health indicator, such as a life expectancy, of a target person using a proxy model comprising an artificial neural network, in lieu of more complex, costly, and/or invasive health assessment processes. The artificial neural network may be constructed from labeled training data comprising a plurality of activity data training sets, each set including personal activity metrics associated with activities performed by a respective training person as derived from sensor data obtained via one or more mobile electronic devices (e.g., a smartphone or a wearable device) of the respective training person. The trained artificial neural network may then obtain and process an activity data set associated with the target person to determine a health indicator of the target person.

Abstract: Systems and methods for facilitating virtual operation of a virtual vehicle within a virtual environment based on real-life vehicle operation are disclosed. According to aspects, a computing device may access a data model indicative of real-world operation of a real-world vehicle by a real-world operator and, based on the data model, determine virtual operation of the virtual vehicle that corresponds to the real-world operation of the real-world vehicle. The computing device may display, in a user interface, the virtual vehicle undertaking the virtual operation such that the real-life operator may review the virtual operation and potentially be motivated to improve his/her real-world vehicle operation.

Abstract: Systems and methods for facilitating virtual operation of a virtual vehicle within a virtual environment are disclosed. According to aspects, a computing device may access a data model indicative of real-life operation of a real-life vehicle by a real-life operator and, based on the data model, generate a set of virtual vehicle movements that are reflective of a performance of the real-life operation of the real-life vehicle by the real-life operator. The computing device may display, in a user interface, the virtual vehicle undertaking the set of virtual vehicle movements such that the real-life operator may review the virtual movements and potentially be motivated to improve his/her real-life vehicle operation.

Abstract: Techniques are disclosed for objectively assessing the driving performance of rideshare drivers and/or vehicles. The techniques include collecting data from various sources to aggregate trip data for several drivers and passengers over several ridesharing trips. This data may include telematics data collected from several passengers and/or drivers during each of their respective ridesharing trips, which indicates various aspects associated with operation of the vehicle. Each driver may then be correlated to his own set of trip data, such that a driving assessment may be made for each individual driver. When a new user subsequently requests a ride via a ridesharing provider, this driver assessment may be made available to the user, thereby providing the user with an objective assessment of the driver prior to the start of the scheduled ride.

Abstract: The described systems and methods determine a driver's fitness to safely operate a moving vehicle based at least in part upon observed impairment patterns. A smart ring, wearable on a user's finger, continuously monitors impairment levels. This impairment data, representing impairment patterns, can be utilized, in combination with driving data, to train a machine learning model, which will predict the user's level of risk exposure based at least in part upon observed impairment patterns. The user can be warned of this risk to prevent them from driving or to encourage them to delay driving. In some instances, the disclosed smart ring system may interact with the user's vehicle to prevent it from starting while the user is in a state of impairment induced by substance intoxication.

Abstract: Systems and methods for analyzing documentation for assessing potential fraudulent user submissions are provided. According to certain aspects, a server computer may receive an initial set of documentation descriptive of damage to a property asset, and may analyze the initial set of documentation to determine whether additional documentation is needed. The server computer may initiate a communication channel with a user device via which the additional documentation may be submitted, and the server computer may similarly analyze the additional documentation to determine a likelihood of fraud. The server computer may process the user submission accordingly.

Abstract: The present embodiments may relate to generating dynamic transit routes based at least in part upon telematics data of users. For instance, a transit analysis (TA) computing device may be configured to: (1) receive telematics data from the plurality of user mobile devices, each user mobile device of the plurality of user mobile devices corresponding to one user identifier of a plurality of user identifiers; (2) build, for each user identifier of the plurality of user identifiers, a transit model; (3) generate, for each user identifier of the plurality of user identifiers, based at least in part upon the transit model associated with the user identifier, one or more transit predictions; and/or (4) generate, based at least in part upon the one or more transit predictions, for each user identifier of the plurality of user identifiers, a dynamic transit route.

Abstract: A smart ring may be configured with a removable power source and an internal power source. The internal power source may enable continued operation of the smart ring disposed at a finger of a user, while the removable power source may be detached from the smart ring for charging or to be replaced with another charged removable power source. The removable power source may be disposed as a platform at an outer surface of a band-shaped housing of the smart ring, for example, via an adapter.

Abstract: Method and system for generating virtual characters. For example, the method includes receiving first real-world telematics data associated with a first real-world user, determining first real-world driving characteristics based upon the first real-world telematics data, determining first virtual characteristics based upon the first real-world driving characteristics, generating and presenting the first virtual character in a virtual game, receiving second real-world telematics data associated with a second real-world user, determining second real-world driving characteristics based upon the second real-world telematics data, determining second virtual characteristics based upon the second real-world driving characteristics, and generating and presenting the second virtual character in the virtual game, where the first and second virtual characters are generated with different virtual characteristics.

Abstract: Systems and methods of generating scenic routes and safe parking locations near scenic points are provided. Based at least in part upon a driver indication of a preference for a scenic route from an origin location to a destination location, a mobile device application may generate a scenic route by selecting route segments between the origin location and the destination location associated with a large number of scenic points. Scenic points may be identified based at least in part upon historical driver telemetry data and POI data. For instance, if historical telemetry data indicates that a large number of drivers stop briefly at a location not known to be near a POI, that location may be a scenic location (e.g., a location where drivers frequently leave their vehicles to take photos). Additionally, safe parking locations near each scenic point may be identified based at least in part upon historical vehicle damage data, and navigation directions to safe parking locations may be provided.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: analyzing telematics data and device interaction data to determine vehicle driving instances in which a user interacts with a mobile device during a vehicle trip for a vehicle; and the device interaction data is generated when the user interacts with the mobile device during the vehicle trip for the vehicle; receiving positioning data associated with one or more positions of the mobile device within the vehicle during the vehicle trip for the vehicle; and identifying whether the user interacting with the mobile device is a driver of the vehicle based at least in part upon the positioning data and the vehicle driving instances. Other embodiments are disclosed.

Abstract: A computer-implemented method can include receiving personal data associated with a user. The method also can include predicting, by a trained predictive possession model, a set of items owned by the user based at least in part upon the personal data associated with the user. The trained predictive possession model is configured to extract data associated with the set of items from the personal data. The method additionally can include assigning, by the trained predictive possession model, a predicted value for each item of the set of items. The method further can include causing information indicative of an item of the set of items and the predicted value for the item to be displayed on a user device of the user. The method additionally can include receiving an adjusted value for the item in the set of items. The method further can include causing the trained predictive possession model to be updated based on the adjusted value for the item. Other embodiments are described.

Abstract: A smart ring includes a body. The body includes a first part including at least a part of a sensor unit. The body also can include a second part including at least a part of an output unit and removably connected to the first part of the body. The body can further include a first pair of removable portions. The first pair of removable portions can include a first removable portion connected to the first part of the body. The first pair of removable portions also can include a second removable portion connected to the second part of the body. The first removable portion can be removable from the body. The second removable portion can be removable from the body. Other embodiments are disclosed.

Abstract: The described systems and methods determine a driver's fitness to safely operate a moving vehicle based at least in part upon observed UVB exposure patterns, where the driver's UVB exposure levels may serve as a proxy for vitamin D levels in that driver's body. A smart ring, wearable on a user's finger, continuously monitors user's exposure to UVB light. This UVB exposure data, representing UVB exposure patterns, can be utilized, in combination with driving data, to train a machine learning model, which will predict the user's level of risk exposure based at least in part upon observed UVB exposure patterns. The user can be warned of this risk to prevent them from driving or to encourage them to get more sunlight exposure before driving. In some instances, the disclosed smart ring system may interact with the user's vehicle to prevent it from starting while exposed to high risk due to deteriorated psychological or physiological conditions stemming from insufficient UVB exposure.