Xevo Inc.

Netdrones, Inc.

Neural Enterprises Inc.

Richard Chia Tsing Tong

Samuel James McKelvie

Robert Victor Welland

John Hayes Ludwig

John Palmer Cordell

Matthew Laurence Arksey

Satoshi Nakajima

Deon Blaauw

Lucas Thomas Hahn

John Gordon Mcqueen

Guy David Byron Shefner

Paul Krzyzanowski

A method for controlling a plurality of drones to survey a location, the method comprising, at a computing system: automatically generating preliminary flight plans for a plurality of drones to survey the location based on a 3D model; receiving survey data from the plurality of drones as the plurality of drones are surveying the location based on the preliminary flight plans; updating the 3D model based on the survey data received from the plurality of drones; and automatically updating at least a portion of the flight plans based on the updated 3D model

Systems and methods for 3D model based drone flight planning and control

A method comprising receiving a plurality of images of a scene captured by at least one drone; identifying features within the plurality of images; identifying similar images of the plurality of images based on the features identified within the plurality of images; comparing the similar images based on the features identified within the similar images to determine a proportion of features shared by the similar images; selecting a subset of the plurality of images that have a proportion of shared features that meets a predetermined range; generating a first 3D model of the scene from the subset of images using a first 3D model building algorithm; generating a second 3D model of the scene from the subset of images using a second 3D model building algorithm; computing errors for the first and second 3D models; and selecting as the model of the scene the first or second 3D model.

Systems and methods for generating 3D models from drone imaging

One embodiment of the present invention discloses a process of providing a report predicting potential risks relating to an operator driving a vehicle using information obtained from various interior and exterior sensors, vehicle onboard computer ('VOC'), and cloud network. After activating interior and exterior sensors mounted on a vehicle operated by a driver for obtaining data relating to external surroundings and internal environment, the data is forwarded to VOC for generating a current fingerprint associated with the driver. The current fingerprint represents current driving status in accordance with the collected real-time data. Upon uploading the current fingerprint to the cloud via a communications network, a historical fingerprint which represents historical driving information associated with the driver is retrieved. In one aspect, the process is capable of generating a driving analysis report which predicts potential risks associated with the driver according to the current and historical fingerprints.

Method and system for providing artificial intelligence analytic (AIA) services using operator fingerprints and cloud data

Embodiments are directed towards providing a system that provides an environment in which multiple user applications can be executed in the background of a vehicle head unit without direct interaction by a user of the head unit. A category-management application is configured to communicate with the user applications. The category-management application receives a request for content. The category-management application provides a request to one or more of the user applications to cause the user applications to execute as background processes to fulfill the request. The category-management application receives responses from the user applications. The category-management application selects and presents content associated with the fulfilled request to the user.

System and method for managing multiple applications in a display-limited environment

Embodiments are directed towards providing a system that presents content to a user of a vehicle based on where the vehicle is going. A microphone captures audio signals within the vehicle, which are analyzed for route information. These audible commands may be said by a person in the vehicle, such as a passenger telling the driver where to turn, or they may be received from a mobile computing device, such as a smartphone executing a map application that is providing audible directions. An anticipated route of the vehicle is determined based on the audible route information. Content is selected and presented to the user of the vehicle based on the anticipated route. Images of a display screen of the mobile computing device may also be analyzed to identify the route information.

System and method for providing content to a user based on a predicted route identified from audio or images

One embodiment discloses an automobile having multiple distributed subsystems configured to provide communication via a network system. The automobile includes an outward facing camera ('OFC') subsystem and a vehicle onboard computer ('VOC'). The OFC subsystem, having at least one OFC, OFC processor, and OFC database, is configured to recognize a predefined exterior object from a set of exterior images captured by the OFC based on an OFC query. The VOC includes a VOC central processing unit, VOC database, and network manager, wherein the network manager includes an internal network circuit and an external network circuit. The internal network circuit is used for communicating with the OFC subsystem while the external network circuit is used to interface with a cloud system. In one aspect, the VOC provides a data stream representing a recognized event in accordance with a query retrieved from the VOC database.

Method and system for providing predictions via artificial intelligence (AI) models using a distributed system

One embodiment of the present invention predicts a vehicular event relating to machinal performance using information obtained from interior and exterior sensors, vehicle onboard computer ('VOC'), and cloud data. The process of predication is able to activate interior and exterior sensors mounted on a vehicle operated by a driver for obtaining current data relating to external surroundings, interior settings, and internal mechanical conditions of the vehicle. After forwarding the current data to VOC to generate a current vehicle status representing real-time vehicle performance in accordance with the current data, retrieving a historical data associated with the vehicle including mechanical condition is retrieved. In one aspect, a normal condition signal is issued when the current vehicle status does not satisfy with the optimal condition based on the historical data. Alternatively, a race car condition is issued when the current vehicle status meets with the optimal condition.

Method and system for providing artificial intelligence analytic (AIA) services for performance prediction

One embodiment of the present invention is able to provide an interactive parking management ('IPM') in accordance with information obtained from interior and exterior sensors, vehicle onboard computer ('VOC'), and cloud data. The process, in one embodiment, is capable of acknowledging a parking activity initiated by a vehicle traveling in a geographic location via a communications network. Upon providing parking information to the vehicle based on the data obtained from the current parking status, historical parking status, and big data for facilitating the parking activity, the movement of the vehicle is monitored in accordance with the current parking status. After recording a physical location where the vehicle is parked and parking duration, a parking invoice is generated in response to information relating to the recorded information such as physical location and parking duration.

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Seattle, WA, United States of America

Richard Chia Tsing Tong