Microsoft Technology Licensing, LLC

Xevo Inc.

John Palmer Cordell

Samuel James McKelvie

Robert Victor Welland

John Hayes Ludwig

Richard Chia Tsing Tong

Christopher David Brown

Joseph Paul-Emile Pierre Cote

Christopher Matthew Franklin

Joseph H Matthews, Iii

Stephen P Capps

Benjamin W Slivka

Richard Wales Stoakley

Bradley M Schick

Bharat Shyam

Walter W Smith

Thomas R Reardon

Arthur E Blume

Joseph Paul-Emile-Pierre Cote

Joe D Belfiore

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 presents customized content to a user in an automobile based on the usage patterns of the automobile or its current occupant. Accessory data from the automobile is monitored to learn the automobile-usage patterns. The automobile-usage patterns are mapped to a plurality of content items, such as by mapping the content items to services, which are then mapped to the automobile-usage patterns. The plurality of content items are prioritized for display to the user based on the automobile-usage patterns and the frequency of those automobile-usage patterns. The prioritized content items can be presented to the user sequentially or in response to accessory data that matches an automobile-usage pattern.

System and method for prioritizing content based on automobile-usage patterns

Embodiments are directed towards providing a system that presents customized content to a user of an automobile based on what the user of the automobile is looking at. A first camera captures images of the user of the interior of the automobile, and a second camera captures images of a scene that the user is viewing. The images are analyzed to determine if the user is looking at, or not looking at, an object in the scene. If the user is looking at such an object, content associated with the object is selected and presented to the user.

System and method for correlating user attention direction and outside view

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

A method and/or system is able to provide driver fingerprint via metadata extraction managed by a driver rating ('DR') model trained by a machine learning center ('MLC') coupled to a cloud based network (&#x201c;CBN&#x201d;). In one embodiment, a DR system includes a set of outward facing cameras, a set of inward facing cameras, and a vehicle onboard computer (&#x201c;VOC&#x201d;). The set of outward facing cameras mounted on a vehicle is used to collect external images representing a surrounding environment in which the vehicle operates. The set of inward facing cameras mounted in the vehicle is used to collect internal images including operator body expression representing at least operator's attention. The VOC is configured to determine the identity of operator and current operating style in response to the collected internal images, the collected external images, and historical stored data.

Method and apparatus for providing driver information via audio and video metadata extraction

A method or system is able to refine Global Positioning System ('GPS') information for guiding a vehicle via extracted metadata using a GPS refinement ('GR') model managed by a virtuous cycle containing sensors, machine learning center (&#x201c;MLC&#x201d;), and a cloud based network (&#x201c;CBN&#x201d;). The GR system includes a set of outward facing cameras, a vehicle onboard computer (&#x201c;VOC&#x201d;), and GR model. The outward facing cameras mounted on a vehicle are capable of collecting external images representing a surrounding environment in which the vehicle operates. The VOC is configured to generate a positional vehicle location with respect to the surrounding environment in accordance with the external images and historical stored data obtained from CBN. The GR model is configured to generate a driving guidance based on combined information between the positional vehicle location and GPS data.

Method and apparatus for providing goal oriented navigational directions

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.

Method and system for providing interactive parking management via artificial intelligence analytic (AIA) services using cloud network

A user may discover and navigate among hyperlinks through the use of a keyboard. For example, a user may press a tab key to discover and navigate to a first hyperlink that is part of a hypertext document. The first hyperlink is, in response, given focus and a focus shape is drawn around the text or graphics for the hot region of the hyperlink. If the user again presses the tab key, the next hyperlink is given focus and a focus shape (i.e., an outline that surrounds the next hyperlink) is drawn around the next hyperlink. A user may also tab to a placeholder for an image in order to make a decision whether the image should be downloaded or not.

Discoverability and navigation of hyperlinks

Discoverability and navigation of hyperlinks via tabs

Stopping the downloading of at least one image on a browser by selecting a placeholder representing the image

A user interface for navigating among screens on a personal computer. The screens, which include layers of a shell user interface and various locations within applications, are presented as pages. In addition, commands and help information of an application are presented as a web of command pages. To this end, a unit of measure, called a 'place' is defined. In general, an application is a place, and separate documents within an application may also define a place. Separate command windows and dialog boxes within an application or a document typically do not define a place. Backwards navigation takes the user to the previous place, and forward navigation (if possible) takes the user to the next place. Because the underlying data for a page may change between an initial visit to a page and navigation back to the page, data objects and page code are maintained separately, and are combined only when a request for a page is made.

Unified navigation shell user interface

A new reference tag is provided as an extension to the HyperText Markup Language (HTML). The new reference tag allows nesting of HTML and other electronic documents within a main HTML document obtained from a computer network such as the Internet or an intranet while maintaining all the layout and presentation capabilities of HTML in both the main and nested documents. The new reference tag is implemented as a container tag. If a client network applications understands the new reference tag, nested documents are displayed for a user. If the client network application does not understand the new reference tag, then the other HTML information tags contained between the beginning and end of the reference tag (i.e. the reference tag container) are used to display information for a user.

Growing community of inventors

Los Angeles, CA, United States of America

John Palmer Cordell