Abstract: Method and system for determining total carbon emissions of a first vehicle are disclosed. For example, the method includes determining a first amount of carbon emissions produced during a commissioning stage of the first vehicle, collecting driving data for one or more trips made by the first vehicle during an operating stage of the first vehicle, determining a second amount of carbon emissions produced during the operating stage of the first vehicle based at least in part upon the driving data, determining a third amount of carbon emissions produced during a decommissioning stage of the first vehicle, and determining the total amount of carbon emissions produced during a life cycle of the first vehicle based at least upon the first amount of carbon emissions, the second amount of carbon emissions, and the third amount of carbon emissions.

Abstract: Telematics systems and methods are described for generating interactive animated guided user interfaces (GUIs). A telematics cloud platform is configured to receive vehicular telematics data from a telematics device onboard a vehicle. A GUI value compression component determines, based on the vehicular telematics data, a plurality of GUI position values and a plurality of corresponding GUI time values. A geospatial animation app receives the plurality of GUI position values and the plurality of corresponding GUI time values. The geospatial animation app implements an interactive animated GUI that renders a plurality of geospatial graphics or graphical routes on a geographic area map via a display device. The geospatial graphics or graphical routes are rendered to have different visual forms based on differences between respective GUI position values and corresponding GUI time values.

Abstract: A smart ring is configured harvest mechanical energy using piezoelectricity. The smart ring includes a ring-shaped housing, a power source disposed within the ring-shaped housing, and a charging circuit. The charging circuit includes a piezoelectric harvesting element, and is configured to charge the power source when user motion causes a mechanical deformation in the piezoelectric harvesting element. The smart ring further includes a component, disposed within the ring-shaped housing and configured to draw energy from the power source, and further configured to perform at least one of: i) sense a physical phenomenon external to the ring-shaped housing, ii) send communication signals to a communication device external to the ring-shaped housing, or iii) implement a user interface.

Abstract: Method, system, device, and non-transitory computer-readable medium for data management. In some examples, a computer-implemented method includes: collecting a plurality of personal data sets continually; collecting a plurality of sensor data sets continually via one or more sensing modules, and generating and continually updating an operator profile, determining and continually updating one or more telematics interferences; generating and continually updating a data profile; and receiving one or more access policies associated with the data profile; and listing and continually updating the data profile onto a telematics marketplace according to the one or more access policies such that only marketplace consumers having one or more consumer classifications satisfying the one or more access polices can access the data profile.

Abstract: Method, system, device, and non-transitory computer-readable medium for managing vehicle operator profiles based on telematics inferences via a telematics marketplace. In some examples, a computer-implemented method includes: collecting a plurality of personal data sets continually; collecting a plurality of sensor data sets continually via one or more sensing modules; for each vehicle operator of the plurality of vehicle operators; generating and continually updating an operator profile; determining and continually updating one or more telematics inferences using one or more imitating predictive models; generating and continually updating a data profile; and listing and continually updating the data profile onto a telematics marketplace; receiving an information request for a target operator profile; and transmitting the target operator profile to the requesting party.

Abstract: Method, system, device, and non-transitory computer-readable medium for managing vehicle operator profiles based on telematics inferences via a telematics marketplace. In some examples, a computer-implemented method includes: collecting a plurality of personal data sets continually; collecting a plurality of sensor data sets continually via one or more tensing modules; for each vehicle operator of the plurality of vehicle operators: generating and continually updating an operator profile including the personal data set: determining and continually updating one or more telematics inferences using a universal predictive model based at least in part upon the sensor data set, the universal predictive model having weights and biases hidden to marketplace participants; generating and continually updating a data profile including the one or more telematics inferences; and listing and continually updating the data profile onto a telematics marketplace to be accessible by a plurality of marketplace participants.

Abstract: Method, system, device, and non-transitory computer-readable medium for data management. In some examples: a computer-implemented method includes: collecting a plurality of personal data sets continually; collecting a plurality of sensor data sets continually via one or mote sensing modules; for each vehicle operator of the plurality of vehicle operators; generating and continually updating an operator profile; determining and continually updating one or hums telematics inferences; generating and continually a data profile, assigning and continually updating an operator tier; and listing and continually updating the data profile onto a telematics marketplace according to the operator tier, receiving an information request for one or more operator profiles; and transmitting the one or more operator profiles to the requesting party.

Abstract: Method, system, device, and non-transitory computer-readable medium for data management.

Abstract: Method, system, device, and non-transitory computer-readable medium for managing vehicle operator profiles based on telematics inferences via a telematics marketplace.

Abstract: A distracted driving analysis system for identifying distracted driving events is provided. The system includes a processor in communication with a memory device programmed to: (i) receive driving event records, each driving event record including phone usage by a user, wherein a driving event record is labeled as an actual distracted driving event or a passenger event, (ii) divide the driving event records into at least two clusters based at least in part upon common features and the labels of each driving event record by processing the plurality of driving event records with a semi-supervised machine learning algorithm, (iii) generate a trained model based at least in part upon the at least two clusters, (iv) process a new driving event using the trained model, (v) assign the new driving event to one of the clusters using the trained model, and/or (vi) determine whether the new driving event is an actual distracted driving event or a passenger event.

Abstract: Method, system, device, and non-transitory computer-readable medium for data management. In some examples, a computer-implemented method includes: collecting a first set of operator data during a first time period prior to a user in management event; applying the user management event; colleting a second set of operator data continually during a second time period after the user management event; determining a first set of telematics inferences indicative of at least the driving characteristics exhibited during the first time period; determining and continually updating a second set of telematics inferences indicative of at least the driving characteristics exhibited during the second time period; determining and continually updating an event evaluation based at least in part upon one or more differences between the first set of the telematics inferences and the second set of telematics inferences; and transmitting the event evaluation to the marketplace participant continually.

Abstract: Method, system, device, and non-transitory computer-readable medium for classifying a vehicular trip. In one aspect, a computer-implemented method includes: obtaining a set of travel data associated with a set of vehicular trips traveled by a plurality of vehicle operators, the set of travel data including a set of location data and a set of timing data; determining, based at least in part upon the set of travel data, a location pattern tracking the paths the plurality of vehicle operators traveled during the set of vehicular trips; determining whether the location pattern qualifies as a hub-and-spokes pattern based at least in part upon one or more pattern definitions; and upon determining that the location pattern qualifies as a hub-and-spokes pattern, classifying the set of vehicular trips as for commute.

Abstract: Method, system, device and non-transitory computer-readable medium for managing vehicle operator profiles based on telematics inferences via a telematics marketplace. In some examples, a computer-implemented method includes: collecting a plurality of personal data sets contimally; collecting a plurality of sensor data sets contimally via one or more sensing modules; for each vehicle operator of the plurality of vehicle operators; generating and continually updating an operator profile; determining and continually updating one or more telematics inferences using a one or more party-specific predictive models; generating and continually updating a data profile; and listing and continually updating the data profile onto a telematics marketplace; receiving an information request for a target operator profile associated with a target data profile selected from the listed data profile of the plurality of vehicle operators; and transmitting the target operator profile to the requesting party.

Abstract: Method, system, device, and non-transitory computer-readable medium for data management. In some examples, a computer-implemented method includes: collecting a plurality of personal data sets continually; collecting a plurality of sensor data sets continually; generating and continually updating an operator profile; determining and continually updating one or more primary telematics inferences; generating and continually updating a data profile; and listing and continually updating the data profile onto a telematics marketplace; receiving a supplemental information request for a first set of operator profiles; determining and continually updating one or more secondary telematics inferences; updating the data profile includes the one or more secondary telematics inferences; receiving a profile information request for a second set of operator profiles; and transmitting operator profiles of the second group of vehicle operators to the requesting party.

Abstract: Method, system, device, and non-transitory computer-readable medium for data management. In some examples, a computer-implemented method includes: collecting a plurality of personal data sets continually; collecting a plurality of sensor data sets associated continually via one or more sensing modules; generating and continually updating an operator profile; determining and continually updating one or more telematics inferences; generating and continually updating a data profile; and listing and continually updating the data profile onto a telematics marketplace; receiving a plurality of bids for a target operator profile; determining a first winning bid, an associated first winning bidder, a second winning bid, and an associated second winning bidder; transmitting the target operator profile to the first winning bidder according to a first award protocol, and transmitting the target operator profile to the second winning bidder according to a second award protocol.

Abstract: A computer system for providing reimbursement controls to insurance policies is provided. The computer system may include a processor in communication with a memory device.

Abstract: A system for displaying information indicative of driving conditions, to a driver, using a smart ring are disclosed. An exemplary system includes a smart ring with a ring band having a plurality of surfaces including an inner surface, an outer surface, a first side surface, and a second side surface. The system further includes a processor, configured to obtain data from a communication module within the ring band, or from one or more sensors disposed within the ring band. The obtained data are representative of information indicative of one or more driving conditions to be displayed to the driver. The smart ring also includes an electronic ink (e-ink) display disposed on at least one of the plurality of surfaces, and configured to present information indicative of the one or more driving conditions.

Abstract: A system for displaying information indicative of driving conditions, to a driver, using a smart ring are disclosed. An exemplary system includes a smart ring with a ring band having a plurality of surfaces including an inner surface, an outer surface, a first side surface, and a second side surface. The system further includes a processor, configured to obtain data from a communication module within the ring band, or from one or more sensors disposed within the ring band. The obtained data are representative of information indicative of one or more driving conditions to be displayed to the driver. The smart ring also includes a projector module display disposed on at least one of the plurality of surfaces, and configured to present information indicative of the one or more driving conditions.

Abstract: A distracted driving analysis system for identifying distracted driving events is provided. The system includes a processor in communication with a memory device programmed to: (i) receive driving event records including phone usage by a user that occurred within a time period of a driving event, (ii) divide the driving event records into at least two clusters based at least in part upon common features of one or more driving event records of the plurality of driving event records by processing the driving event records using an unsupervised machine learning algorithm, (iii) generate a trained model based at least in part upon the at least two clusters including cluster labels, (iv) process a new driving event using the trained model, (v) assign the new driving event to one of the at least two clusters using the trained model, and (vi) based at least in part upon the cluster labels for the assigned cluster, determine whether the new driving event is an actual distracted driving event or a passenger event.

Abstract: A computer system for assessing sound to analyze a user's sleep includes a processor configured to perform operations including: (i) storing sample sound data associated with a plurality of sample sleep events, the sample sound data including a plurality of sample characteristics each respectively associated with at least one sample sleep event of the plurality of sample sleep events; (ii) receiving, from a client device, subject sound data collected during a sleep interval; (iii) analyzing, using a machine learning algorithm, the subject sound data collected during the sleep interval; (iv) identifying, based upon the analyzing, a subject characteristic associated with the subject sound data; (v) comparing the subject characteristic with the plurality of sample characteristics; and (vi) determining, based upon the comparing, whether the subject characteristic substantially matches at least one sample characteristic to identify one or more subject sleep events occurring during the sleep interval.