Xevo Inc.

Surround.io

Other

John Hayes Ludwig

Richard Tong

Samuel James McKelvie

Robert Victor Welland

John Palmer Cordell

Richard Chia Tsing Tong

John Zagula

Jon Anderson

Jonathan Winslow Anderson

Jonathan Anderson

Technologies are disclosed herein for selecting one or more content instances of a plurality of content instances for display on a head unit of a vehicle. The content instances correspond to a location of a vehicle and are received by the head unit. The head unit obtains vehicle specific information from memory of the head unit. Based on the vehicle specific information, the head unit selects the one or more content instances using a set of criteria for determining which, if any, content instances to display. Selection of the one or more content instances using the set of criteria may involve consideration of information associated with individual instances of the plurality of content instances. The selected one or more content instances are displayed on a display of the head unit.

Systems and methods for adaptive content filtering

A system includes a plurality of cameras each enabled to operate independently of the others as a component camera. The system includes logic operable to form the component cameras into a network operable as a single federated camera device. The lens types of the component cameras are non-heterogeneous, and the federated camera forms a virtual lens comprising characteristics combining the lens types of the component cameras.

Redundant array of inexpensive cameras

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

Technologies are disclosed herein for selecting a content instance for enforcing a protocol on a head unit of a vehicle. The content instance corresponds to a geographic region of a vehicle and is received by the head unit in the geographic region. The content instance includes a set of criteria for determining whether to enforce the protocol. Enforcement of the protocol by the head unit may adjust operation of the head unit or how the head unit presents media content. The head unit may establish communication connections with head units of other vehicles. The head units may communicate vehicle specific information over the communication connections and implement protocols as a result of the communications.

Systems and methods for adaptive protocol implementation for vehicle head units

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

A system includes an analytical router including an I/O interface to a plurality of external devices or sensors; logic to identify a device id and a time or location for measurements or feeds received from the plurality of external devices or sensors; logic to apply the device id to associate the measurements or feeds with a device id grouping of the measurements or feeds; logic to apply the time or location, or both, to associate the measurements or feeds with a temporal or geo grouping of the measurements or feeds; and a web page generator to generate a web page comprising one or more links pointing to the measurements or feeds for at least one of the temporal or geo grouping of the measurements or feeds and the device id grouping of the measurements or feeds.

Naming services extensions to URLs to handle inconstant resources, non-addressable resources, and large numbers of resources

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 machine system includes monitor devices each having a camera, the monitor devices distributed over a physical area; layout logic forms images from the cameras of the monitor devices into a scene layout for the area; user interface logic receives training signals from sensors directed to a person physically present in the area and to correlate those signals to subareas of the layout; and analytical logic analyzes the layout and training signals to ascertain subareas of the area at which the monitor devices should focus machine sensor and processing resources.

Growing community of inventors

Bellevue, WA, United States of America

John Hayes Ludwig