Verizon Patent and Licensing Inc.

Jerry Gamble, Jr

Natasha Avinash Shah

Matthew William Turlington

Leonardo Taccari

Francesco Sambo

Vidhya Seran

Leonardo Sarti

Douglas Coimbra De Andrade

Tommaso Bianconcini

Aurel Pjetri

Corbin Pierce Moline

Sagar Deepak Mahurkar

Syed B Aziz

Peter Brockmann

Aleena Taufiq

A device may receive video data and corresponding GPS data and IMU data associated with a vehicle, and may remove video frames from the video data to generate modified video data. The device may select objects and image regions of video frames of the modified video data, and may determine a current speed and a current turn angle of the vehicle based on the GPS data, the IMU data, and the modified video data. The device may mask the objects of the video frames of the modified video data to learn first features, and may mask the image regions of the video frames of the modified video data to learn second features. The device may generate a trained neural network model based on the current speed, the current turn angle, the first features, and the second features, and may implement the trained neural network model in the vehicle.

Systems and methods for training a driving agent based on real-world driving data

A device may receive simulation information associated with iteratively simulating movement of a geolocation unit. The device may generate simulated true paths for simulations of the movement of the geolocation unit. The device may configure, based on the simulation information, noise parameters associated with simulating distortion of a signal received by the geolocation unit during the simulations to generate simulated measured paths. The device may execute the simulations to correspondingly generate sets of simulation data, training, using the sets of simulation data, a geolocation correction model based on differences between true location data of the simulated true paths and simulated measured data of the simulated measured paths. The device may configure the geolocation correction model to process a geolocation signal of an active geolocation unit to determine a location of the active geolocation unit based on the differences between the true location data and the simulated measured data.

Systems and methods for denoising GPS signals using simulated models

One or more computing devices, systems, and/or methods for elevation tracking of devices are provided. Barometric pressure data points and elevation data points associated with a set of barometric measurement devices proximate a device are obtained. An interpolated field of barometric pressure is generated using the barometric pressure data points and the elevation data points. x, y location coordinates of the device are projected onto the interpolated field as a projected point within the interpolated field. Barometric leveling is executed upon a device barometric pressure value provided by the device and a barometric pressure data point at the projected point to determine a relative height difference between the device and the projected point. An elevation of the device is determined based upon the relative height difference.

Systems and methods for elevation tracking of devices

One or more computing devices, systems, and/or methods for synthetic data point generation are provided. In an example, error bounds for generating synthetic data points from a set of data points collected from mobile devices may be determined. Paths associated with groups of data points of the set of data points may be determined. Error bounds may be applied to limit the paths to generate limited path data. Synthetic data points may be generated based upon the limited path data.

Crowdsourced building structure detection with synthetic data generation

One or more computing devices, systems, and/or methods for calibrating barometric sensors and/or determining altitudes of devices are provided. In an example, one or more barometric pressure measures are determined using a barometric sensor of a device. One or more locations of the device are determined based upon one or more global navigation satellite system (GNSS) signals and one or more corrective signals associated with the one or more GNSS signals. One or more reference values are determined based upon the one or more locations. A barometric offset is determined based upon the one or more barometric pressure measures and the one or more reference values. A first barometric measurement is performed using the barometric sensor to determine a first barometric pressure measure. An adjusted barometric pressure measure and/or an altitude of the device are determined based upon the first barometric pressure measure and the barometric offset.

Barometric sensor calibration with locations determined using corrective signals

One or more computing devices, systems, and/or methods for calibrating barometric sensors and/or determining altitudes of devices are provided. In an example, a device is determined to be outdoors. In response to determining that the device is outdoors, a calibration process associated with a barometric sensor of the device is performed. The calibration process includes performing one or more barometric measurements using the barometric sensor to determine one or more barometric pressure measures, determining one or more locations of the device, wherein the one or more locations are associated with the one or more barometric measurements, and determining a barometric offset based upon the one or more barometric pressure measures and one or more reference values. An adjusted barometric pressure and/or an altitude of the device is determined based upon a first barometric pressure measure and the barometric offset.

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Grapevine, TX, United States of America

Jerry Gamble, Jr