Abstract: A computer-implemented method for identifying occupants of a vehicle, the computer-implemented method including: receiving, using a sensor associated with a first user device of a first vehicle occupant in the vehicle, an echo signal associated with a first ping signal emitted by the first user device; generating a first relative positioning map based upon the echo signal; and determining that the first vehicle occupant is a driver or a passenger of the vehicle based at least in part upon the first relative positioning map.

Abstract: A computer system for generating a public transportation schedule for users is provided.

Abstract: A computer-implemented method for health assessment includes providing an artificial neural network trained with training data. The method also includes receiving activity data comprising personal activity metrics corresponding to a target person, and determining, by the artificial neural network, a health indicator of the target person based upon the activity data corresponding to the target person. The method further includes outputting the health indicator of the target person to an electronic device for communication of the health indicator to a user of the electronic device. Other embodiments are disclosed.

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: building, using a machine learning algorithm, a transit model based at least in part upon telematics data associated with a user; generating, based at least in part upon the transit model, a dynamic transit route for the user; calculating, based at least in part upon the telematics data associated with the user, a potential benefit comprising an amount of fuel cost savings for the user, reduced travel time for the user, insurance savings, or environmental pollution reduction for the user; generating a notification comprising the dynamic transit route and the potential benefit; and transmitting the notification to a mobile device of the user. Other embodiments are described.

Abstract: A user computing device for identifying a driver of a vehicle on a trip is provided. The user computing device is associated with a first vehicle occupant, and is programmed to: (i) detect a second user computing device associated with a second vehicle occupant, (ii) initiate a ping exchange process including emitting a set of non-audible sonic ping signals and detecting a set of signals from the second user computing device over a duration of the trip, (iii) generate a relative positioning map of the user computing device with respect to the second user computing device, (iv) determine that the first vehicle occupant is one of a driver and a passenger of the vehicle, and (v) transmit, to a driver identification (“DI”) server, a trip report including the determination and the generated relative positioning map.

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: 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: 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: Technology for identifying potentially fraudulent user behavior related to the capture and transmission of vehicle trip telemetry data is provided. Automatic and periodic attempts may be made to wake up (e.g., launch, or change to an active mode) an application installed on a mobile device configured to transmit mobile device data, including captured sensor data, to a remote computer device. Based on the sensor data, the remote computer device may determine a number, frequency, and/or duration of vehicle trips associated with the user of the mobile device. When one or more types of expected mobile device data are not received by the remote computer device after a particular attempt to wake the application, data indicating a failure to receive expected mobile device data may be recorded in a log. Based on the log, an alert indicating potentially fraudulent behavior associated with the user of the mobile device may be generated.

Abstract: Technology for identifying potentially fraudulent user behavior related to the capture and transmission of vehicle trip telemetry data is provided. Automatic and periodic attempts may be made to wake up (e.g., launch, or change to an active mode) an application installed on a mobile device configured to transmit mobile device data, including captured sensor data, to a remote computer device. Based on the sensor data, the remote computer device may determine a number, frequency, and/or duration of vehicle trips associated with the user of the mobile device. When one or more types of expected mobile device data are not received by the remote computer device after a particular attempt to wake the application, data indicating a failure to receive expected mobile device data may be recorded in a log. Based on the log, an alert indicating potentially fraudulent behavior associated with the user of the mobile device may be generated.

Abstract: A user computing device for identifying a driver of a vehicle on a trip is provided. The user computing device is associated with a first vehicle occupant, and is programmed to: (i) detect a second user computing device associated with a second vehicle occupant, (ii) initiate a ping exchange process including emitting a set of non-audible sonic ping signals and detecting a set of signals from the second user computing device over a duration of the trip, (iii) generate a relative positioning map of the user computing device with respect to the second user computing device, (iv) determine that the first vehicle occupant is one of a driver and a passenger of the vehicle, and (v) transmit, to a driver identification (“DI”) server, a trip report including the determination and the generated relative positioning map.

Abstract: A system for analyzing wireless telematics data to determine that a vehicle is engaged in an extended period of travel and prompt additional devices within the vehicle regarding the extended period of travel. The system may comprise a telematics server and a plurality of mobile applications to be implemented on a plurality of telematics devices belonging to a plurality of users. The plurality of telematics devices transmit telematics data to the telematics server. The data is analyzed and the telematics server transmits an indication to the telematics devices, causing the mobile applications to execute in a driver application mode or passenger application mode. Messages containing notifications to change drivers or pull over are sent to the telematics devices.

Abstract: A user computing device for identifying a driver of a vehicle on a trip is provided. The user computing device is associated with a first vehicle occupant, and is programmed to: (i) detect a second user computing device associated with a second vehicle occupant, (ii) initiate a ping exchange process including emitting a set of non-audible sonic ping signals and detecting a set of signals from the second user computing device over a duration of the trip, (iii) generate a relative positioning map of the user computing device with respect to the second user computing device, (iv) determine that the first vehicle occupant is one of a driver and a passenger of the vehicle, and (v) transmit, to a driver identification (“DI”) server, a trip report including the determination and the generated relative positioning map.

Abstract: Technology for identifying potentially fraudulent user behavior related to the capture and transmission of vehicle trip telemetry data is provided. Automatic and periodic attempts may be made to wake up (e.g., launch, or change to an active mode) an application installed on a mobile device configured to transmit mobile device data, including captured sensor data, to a remote computer device. Based on the sensor data, the remote computer device may determine a number, frequency, and/or duration of vehicle trips associated with the user of the mobile device. When one or more types of expected mobile device data are not received by the remote computer device after a particular attempt to wake the application, data indicating a failure to receive expected mobile device data may be recorded in a log. Based on the log, an alert indicating potentially fraudulent behavior associated with the user of the mobile device may be generated.

Abstract: A system for analyzing wireless telematics data to determine that a vehicle is engaged in an extended period of travel and prompt additional devices within the vehicle regarding the extended period of travel. The system may comprise a telematics server and a plurality of mobile applications to be implemented on a plurality of telematics devices belonging to a plurality of users. The plurality of telematics devices transmit telematics data to the telematics server. The data is analyzed and the telematics server transmits an indication to the telematics devices, causing the mobile applications to execute in a driver application mode or passenger application mode. Messages containing notifications to change drivers or pull over are sent to the telematics devices.

Abstract: A computer system for generating a public transportation schedule for users is provided.

Abstract: A system for analyzing wireless telematics data to determine that a vehicle is engaged in an extended period of travel and prompt additional devices within the vehicle regarding the extended period of travel. The system may comprise a telematics server and a plurality of mobile applications to be implemented on a plurality of telematics devices belonging to a plurality of users. The plurality of telematics devices transmit telematics data to the telematics server. The data is analyzed and the telematics server transmits an indication to the telematics devices, causing the mobile applications to execute in a driver application mode or passenger application mode. Messages containing notifications to change drivers or pull over are sent to the telematics devices.

Abstract: A user computing device for identifying a driver of a vehicle on a trip is provided. The user computing device is associated with a first vehicle occupant, and is programmed to: (i) detect a second user computing device associated with a second vehicle occupant, (ii) initiate a ping exchange process including emitting a set of non-audible sonic ping signals and detecting a set of signals from the second user computing device over a duration of the trip, (iii) generate a relative positioning map of the user computing device with respect to the second user computing device, (iv) determine that the first vehicle occupant is one of a driver and a passenger of the vehicle, and (v) transmit, to a driver identification (“DI”) server, a trip report including the determination and the generated relative positioning map.

Abstract: A system for analyzing wireless telematics data to determine that a vehicle is engaged in an extended period of travel and prompt additional devices within the vehicle regarding the extended period of travel. The system may comprise a telematics server and a plurality of mobile applications to be implemented on a plurality of telematics devices belonging to a plurality of users. The plurality of telematics devices transmit telematics data to the telematics server. The data is analyzed and the telematics server transmits an indication to the telematics devices, causing the mobile applications to execute in a driver application mode or passenger application mode. Messages containing notifications to change drivers or pull over are sent to the telematics devices.

Abstract: A user computing device for identifying a driver of a vehicle on a trip is provided. The user computing device is associated with a first vehicle occupant, and is programmed to: (i) detect a second user computing device associated with a second vehicle occupant, (ii) initiate a ping exchange process including emitting a set of non-audible sonic ping signals and detecting a set of signals from the second user computing device over a duration of the trip, (iii) generate a relative positioning map of the user computing device with respect to the second user computing device, (iv) determine that the first vehicle occupant is one of a driver and a passenger of the vehicle, and (v) transmit, to a driver identification (“DI”) server, a trip report including the determination and the generated relative positioning map.