Microsoft Technology Licensing, LLC

The Invention Science Fund I LLC

Xevo Inc.

Other

Wayfarer Communications, Inc.

Zhigu Holdings Limited

Robert Victor Welland

Aamer Hydrie

Galen Clyde Hunt

Bassam Tabbara

Steven P Levi

Samuel James McKelvie

Geoffrey Hugh Outhred

Kevin Grealish

Lowell L Wood, Jr

Roderick A Hyde

Clarence T Tegreene

Edward K Y Jung

Jordin T Kare

Nathan P Myhrvold

Robert W Lord

Charles Whitmer

James Robert Hamilton

William Henry Mangione-Smith

Craig J Mundie

Howard Lee Davidson

Richard F Rashid

Burton Jordan Smith

Arne M Josefsberg

Michael J Manos

Kenneth Lustig

Anders Bertil Vinberg

Rob M Mensching

David S Stutz

John Palmer Cordell

John Hayes Ludwig

Robert M Fries

Rene Antonio Vega

John M Parchem

Eric Joseph Winner

Jeffrey A Woolsey

Richard Chia Tsing Tong

Edwin R Lassettre

Ashvinkumar J Sanghvi

Vij Rajarajan

Vitaly Voloshin

Glenn R Peterson

Jakob Rehof

David Searle Noble

Anand Lakshminarayanan

Mark D Van Antwerp

Charlie D Chase

Alexander Torone

Mathilde C Brown

Vladimir Sadovsky

Joseph M Joy

Richard Chia-Tsing Tong

Noah Harrison Fradin

Gary Shon Katzenberger

Sean B House

Phillip Lee Bogle

Joseph H Matthews, Iii

Stephen P Capps

Abolade Gbadegesin

Bryan M Willman

Raymond W McCollum

Sanjay N Kaniyar

Efstathios Papaefstathiou

David C James

Richard Wales Stoakley

Dimitris Achlioptas

Bruce Wayne Copeland

Michael Joseph Healy

Bradley M Schick

Christopher Lee Fraley

John H Wilson

Mazhar Naveed Mohammed

Jonathan C Hardwick

Victor A Stone

Rajagopalan Badri Narayanan

Walter W Smith

Zhengkai Kenneth Pan

Kevin D J Grealish

Christopher L Darling

Landon M Dyer

Przemek Pardyak

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

A method or system is capable of detecting operator behavior ('OB') utilizing a virtuous cycle containing sensors, machine learning center ('MLC'), and cloud based network (&#x201c;CBN&#x201d;). In one aspect, the process monitors operator body language captured by interior sensors and captures surrounding information observed by exterior sensors onboard a vehicle as the vehicle is in motion. After selectively recording the captured data in accordance with an OB model generated by MLC, an abnormal OB (&#x201c;AOB&#x201d;) is detected in accordance with vehicular status signals received by the OB model. Upon rewinding recorded operator body language and the surrounding information leading up to detection of AOB, labeled data associated with AOB is generated. The labeled data is subsequently uploaded to CBN for facilitating OB model training at MLC via a virtuous cycle.

Method and system for providing behavior of vehicle operator using virtuous cycle

A method or system capable of managing automobile parking space ('APS') using containerized sensors, machine learning center, and cloud based network is disclosed. A process, in one aspect, monitors the surrounding information observed by a set of onboard sensors of a vehicle as the vehicle is in motion. After selectively recording the surrounding information in accordance with instructions from a containerized APS model which is received from a machine learning center, an APS and APS surrounding information are detected when the vehicle is in a parked condition. Upon rewinding recorded surrounding information leading up to the detection of APS, labeled data associated with APS is generated based on APS and the recorded surrounding information. The process subsequently uploads the labeled data to the cloud based network for facilitating APS model training at the machine learning center via a virtuous cycle.

Method and system for providing auto space management using virtuous cycle

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

Model-based virtual system provisioning includes accessing a model of a workload to be installed on a virtual machine of a system as well as a model of the system. A workload refers to some computing that is to be performed, and includes an application to be executed to perform the computing, and optionally includes the operating system on which the application is to be installed. The workload model identifies a source of the application and operating system of the workload, as well as constraints of the workload, such as resources and/or other capabilities that the virtual machine(s) on which the workload is to be installed must have. An installation specification for the application is also generated, the installation specification being derived at least in part from the model of the workload and the model of the virtual system.

Model-based virtual system provisioning

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 data center for executing a data processing application includes processing units, sub-units or servers. Each of the processing units, sub-units or servers can execute a part or all of the data processing application. The processing units, sub-units or servers are electrical disjoint with respect to data communications, but can communicate with each other over free space optical links.

Data center with free-space optical communications

A method and apparatus of providing a configurable computer system capable of being modeled are disclosed. The system, in one embodiment, includes a configurable component and a clock distributor. The configurable component includes multiple programmable devices arranged in a predefined configuration. The predefined configuration, for example, is a cubical shape having multiple neighboring nodes. The configurable component is capable of being modeled in accordance with policies from a system program for data transmission. The clock distributor further includes a first clock element, which provides long-term accuracy, and a second clock element, which provides short-term accuracy.

Method and apparatus for providing a synthetic system using a GPS clock

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Seattle, WA, United States of America

Robert Victor Welland