Abstract: Techniques are described for improving driver efficiency. An example method can include a device accessing sparse location data indicative of one or more geographic locations along a route of the user device during a first time period. The route includes a starting location data point and an ending location data point. The device can access motion data collected by the sensors of the user device. The motion data can be collected by the sensors during the first time period. After a conclusion of the first time period, the device can generate, using the sparse location data and the motion data, a dense data set to reconstruct a route that includes the starting location data point and the ending location data point. The reconstructed route can include second dense location data and velocity data. The device can store the reconstructed route in a local memory of the user device.

Abstract: Described herein are techniques to enable a mobile device to perform multi-source estimation of an altitude for a location. A baseline altitude may be determined at ground level for a location and used to calibrate a barometric pressure sensor on the mobile device. The calibrated barometric pressure sensor can then estimate changes in altitude relative to ground level based on detected pressure differentials, allowing a relative altitude to ground to be determined. Baseline calibration for the barometric sensor calibration can be performed to determine an ambient ground-level barometric pressure.

Abstract: Described herein are techniques to enable a mobile device to perform multi-source estimation of an altitude for a location. A baseline altitude may be determined at ground level for a location and used to calibrate a barometric pressure sensor on the mobile device. The calibrated barometric pressure sensor can then estimate changes in altitude relative to ground level based on detected pressure differentials, allowing a relative altitude to ground to be determined. Baseline calibration for the barometric sensor calibration can be performed to determine an ambient ground-level barometric pressure.

Abstract: The subject technology provides for route identification and clustering for real-time mapping. Various clustering techniques can identify groupings of relevant prior routes that can later be mapped against a current route. Filtering and matching techniques can be applied to identify and cluster prior routes. Tracked activity can also be compared against applicable prior activities to provide movement metrics and real-time comparisons between current and one or more recorded activities.

Abstract: Described herein are techniques to enable a mobile device to perform multi-source estimation of an altitude for a location. A baseline altitude may be determined at ground level for a location and used to calibrate a barometric pressure sensor on the mobile device. The calibrated barometric pressure sensor can then estimate changes in altitude relative to ground level based on detected pressure differentials, allowing a relative altitude to ground to be determined. Baseline calibration for the barometric sensor calibration can be performed to determine an ambient ground-level barometric pressure.