Abstract: A computer-implemented method for generating an indication of whether a vehicle crash has occurred is presented. It may be determined whether data output by a base sensor(s) of a mobile computing device indicates that a vehicle crash condition has occurred. An additional sensor(s) of the mobile computing device may begin outputting additional sensor data when the data output by the base sensor(s) indicates that the vehicle crash condition has occurred. The additional sensor(s) may be caused to output the additional sensor data for an amount of time after the additional sensor(s) begins outputting the additional sensor data. An indication of whether a crash of a vehicle has occurred may be generated based on the additional sensor data output by the additional sensor(s) for the amount of time after the additional sensor(s) begins outputting the additional sensor data.

Abstract: A computer-implemented method for generating an indication of whether a vehicle crash has occurred is presented. It may be determined whether data output by a base sensor(s) of a mobile computing device indicates that a vehicle crash condition has occurred. An additional sensor(s) of the mobile computing device may begin outputting additional sensor data when the data output by the base sensor(s) indicates that the vehicle crash condition has occurred. The additional sensor(s) may be caused to output the additional sensor data for an amount of time after the additional sensor(s) begins outputting the additional sensor data. An indication of whether a crash of a vehicle has occurred may be generated based on the additional sensor data output by the additional sensor(s) for the amount of time after the additional sensor(s) begins outputting the additional sensor data.

Abstract: A computer-implemented method for detecting vehicle crashes is presented. The method may include detecting, at a first mobile computing device a condition corresponding to a potential crash of a vehicle. The method may also include operating a beacon receive mode in response to detecting the potential crash condition, and receiving data from a second mobile computing device operating in a beacon transmit mode, the data indicating that the second mobile computing device detected an actual crash condition of the vehicle. The method may further include confirming, based on the potential crash condition and the data received from the second mobile computing device, that the potential crash is an actual crash.

Abstract: A computer-implemented method for generating vehicle crash data is presented. It may be determined whether a first mobile computing device has detected that a crash of a vehicle has occurred. It may also be determined whether a second mobile computing device(s) has detected that the crash has occurred. Sensor data output by at least one sensor of the first mobile computing device and/or the second mobile computing device(s) may be received when it is determined that the first mobile computing device and/or the second mobile computing device(s) has detected that the crash has occurred. Vehicle crash data may be generated based on such sensor data, and may include an initial confirmation that the crash has occurred, an indication of crash severity, an indication of a number of vehicle occupants, and/or an indication that the crash has not occurred.

Abstract: A computer-implemented method for generating data regarding a vehicle crash is presented. Initial sensor data output by a sensor(s) of a mobile computing device may be received. It may be determined whether the initial sensor data includes sensor data indicating that a crash of a vehicle has occurred. Additional sensor data output by the sensor(s) of the mobile computing device may be received when it is determined that the initial sensor data includes sensor data indicating the crash has occurred. The additional sensor data may be received for a first amount of time after it is determined that the initial sensor data includes sensor data indicating the crash has occurred. Combined sensor data may be generated based on the initial sensor data and the additional sensor data, where the combined sensor data may include sensor data corresponding to time before the crash and corresponding to time after the crash.

Abstract: The method, system, and computer-readable medium facilitates monitoring a vehicle operator during the course of vehicle operation to determine whether the vehicle operator is impaired (e.g., distracted, drowsy, intoxicated) and alerting the vehicle operator using a haptic alert delivered by a wearable computing device worn by the vehicle operator when impairment is detected. The method, system, and computer-readable medium may monitor the vehicle operator, the environment surrounding the vehicle, and/or forces acting on the vehicle using a variety of sensors, including optical sensors or accelerometers. In particular, optical sensors may monitor the vehicle operator to detect eye blinks, head nods, head rotations, and/or gaze fixation. Optical sensors may also monitor the road ahead of the vehicle to detect lane deviation, lane centering, and time to collision. Accelerometers may detect acceleration in the direction of vehicle travel and/or lateral acceleration.

Abstract: A computer-implemented method includes detecting a plurality of faces within one or more images, and, for each of the plurality of faces, registering the face with a contact. The method further includes receiving a selection of one of the plurality of faces from a user, and, in response to the selection of the one of the plurality of faces, determining the contact associated with the selected one of the plurality of faces. Still further, the method includes retrieving information about the contact, and generating a list of selectable communication types to be displayed to the user on a display device.

Abstract: A computer-implemented method for generating vehicle crash data is presented. It may be determined whether a first mobile computing device has detected that a crash of a vehicle has occurred. It may also be determined whether a second mobile computing device(s) has detected that the crash has occurred. Sensor data output by at least one sensor of the first mobile computing device and/or the second mobile computing device(s) may be received when it is determined that the first mobile computing device and/or the second mobile computing device(s) has detected that the crash has occurred. Vehicle crash data may be generated based on such sensor data, and may include an initial confirmation that the crash has occurred, an indication of crash severity, an indication of a number of vehicle occupants, and/or an indication that the crash has not occurred.

Abstract: The method, system, and computer-readable medium facilitates monitoring a vehicle operator during the course of vehicle operation to determine whether the vehicle operator is impaired (e.g., distracted, drowsy, intoxicated) and alerting the vehicle operator using a haptic alert delivered by a wearable computing device worn by the vehicle operator when impairment is detected. The method, system, and computer-readable medium may monitor the vehicle operator, the environment surrounding the vehicle, and/or forces acting on the vehicle using a variety of sensors, including optical sensors or accelerometers. In particular, optical sensors may monitor the vehicle operator to detect eye blinks, head nods, head rotations, and/or gaze fixation. Optical sensors may also monitor the road ahead of the vehicle to detect lane deviation, lane centering, and time to collision. Accelerometers may detect acceleration in the direction of vehicle travel and/or lateral acceleration.

Abstract: The method, system, and computer-readable medium facilitates monitoring a vehicle operator during the course of vehicle operation to determine whether the vehicle operator is impaired (e.g., distracted, drowsy, intoxicated) and alerting the vehicle operator using a haptic alert delivered by a wearable computing device worn by the vehicle operator when impairment is detected. The method, system, and computer-readable medium may monitor the vehicle operator, the environment surrounding the vehicle, and/or forces acting on the vehicle using a variety of sensors, including optical sensors or accelerometers. In particular, optical sensors may monitor the vehicle operator to detect eye blinks, head nods, head rotations, and/or gaze fixation. Optical sensors may also monitor the road ahead of the vehicle to detect lane deviation, lane centering, and time to collision. Accelerometers may detect acceleration in the direction of vehicle travel and/or lateral acceleration.

Abstract: A computer-implemented method includes detecting a plurality of faces within one or more images, and, for each of the plurality of faces, registering the face with a contact. The method further includes receiving a selection of one of the plurality of faces from a user, and, in response to the selection of the one of the plurality of faces, determining the contact associated with the selected one of the plurality of faces. Still further, the method includes retrieving information about the contact, and generating a list of selectable communication types to be displayed to the user on a display device.

Abstract: A crash detection system is disclosed that utilizes a mobile computing device to detect a vehicular accident via one or more sensors integrated into the mobile computing device. The system monitors the sensor metrics measured by one or more sensors and generates an event sensor profile that may include the plurality of sensor metrics and additional status data, such as an indication of whether the mobile computing device was located within a vehicle when the event occurred. By comparing the plurality of sensor metrics to other crash sensor metrics, a determination may be made whether the event requires emergency assistance, which may be confirmed by determining whether the data included in the event sensor profile meets one or more exception conditions. If the event requires emergency assistance and an exception condition is not met, the mobile computing device may place a call to the appropriate emergency response personnel.

Abstract: The method, system, and computer-readable medium facilitates monitoring a vehicle operator during the course of vehicle operation to determine whether the vehicle operator is impaired (e.g., distracted, drowsy, intoxicated) and alerting the vehicle operator using a haptic alert delivered by a wearable computing device worn by the vehicle operator when impairment is detected. The method, system, and computer-readable medium may monitor the vehicle operator, the environment surrounding the vehicle, and/or forces acting on the vehicle using a variety of sensors, including optical sensors or accelerometers. In particular, optical sensors may monitor the vehicle operator to detect eye blinks, head nods, head rotations, and/or gaze fixation. Optical sensors may also monitor the road ahead of the vehicle to detect lane deviation, lane centering, and time to collision. Accelerometers may detect acceleration in the direction of vehicle travel and/or lateral acceleration.

Abstract: The method, system, and computer-readable medium facilitates monitoring a vehicle operator during the course of vehicle operation to determine whether the vehicle operator is impaired (e.g., distracted, drowsy, intoxicated) and alerting the vehicle operator using a haptic alert delivered by a wearable computing device worn by the vehicle operator when impairment is detected. The method, system, and computer-readable medium may monitor the vehicle operator, the environment surrounding the vehicle, and/or forces acting on the vehicle using a variety of sensors, including optical sensors or accelerometers. In particular, optical sensors may monitor the vehicle operator to detect eye blinks, head nods, head rotations, and/or gaze fixation. Optical sensors may also monitor the road ahead of the vehicle to detect lane deviation, lane centering, and time to collision. Accelerometers may detect acceleration in the direction of vehicle travel and/or lateral acceleration.