Intel Corporation

Rahul C Shah

Lama Nachman

Chieh-Yih Wan

Giuseppe Beppe Raffa

Jonathan J Huang

Junaith Ahemed Shahabdeen

Rita H Wouhaybi

Mark D Yarvis

Wendy March

Hong Lu

Jennifer Anne Healey

Cagri Tanriover

Ke-Yu Chen

Bran Ferren

Glen J Anderson

Yi Wu

Lei Yang

Adam Jordan

Douglas P Bogia

Alexander Essaian

Ashwini Asokan

Saurav Sahay

Omar Florez

John Cross Neumann

Kieran Del Pasqua

Sushmita Subramanian

Matthew William Webb

Hong C Li

Arvind A Kumar

Venkatraman Iyer

Shao-Wen Yang

David Sonnier

Lakshman Krishnamurthy

Stephen T Palermo

Darren S Jue

Mrittika Ganguli

Lenitra M Durham

William G Burroughs

Sangita R Sharma

Niall D McDonnell

Addicam V Sanjay

Shrikant M Shah

David Matthew Jones

Jack Schulze

James Lundell

Abhishek Khade

Michael J Payne

Gage Eads

Abhirupa Layek

Timothy E Hansen

Sarita Maini

Jinwon Lee

Bradley Chaddick

Nick Ludlam

Scott Thomas

Yong Wang

Ana P Rosario

Aaron D Davies

Carol A Wilder

Joseph A Malia

Techniques are disclosed for performing RFID motion tracking in an intelligent manner that facilitates the generation of accurate and useful metrics for marketing and other applications. The techniques function to reduce problematic false positive rates on RFID tags attached to items to improve the accuracy of the motion presence of a small subset of browsed items among a much larger set of tagged items in the same space. This accurate motion inference enables the calculation of metrics such as customer-item interaction duration, pauses in interactions (potentially indicating close examining), and the extraction of patterns of motion that can indicate interest leading to realized sales, as well as concurrent motion detection of multiple items indicating which related items shall be placed in close proximity to increase sales of matching items.

Probabilistic contextual inference using RFID tag-interactions

System and techniques for tracking caloric expenditure using sensor driven fingerprints are described herein. A set of outputs may be obtained from a plurality of sensors. A fingerprint may be generated using the set of outputs. The fingerprint may correspond to an activity observed by the plurality of sensors. The generated fingerprint may be compared to a set of fingerprints stored in a database. Each fingerprint of the set of fingerprints may correspond to a respective caloric expenditure. A caloric expenditure may be calculated for the activity based on the comparison. An exercise profile of a user may be updated using the caloric expenditure.

Tracking caloric expenditure using sensor driven fingerprints

In one embodiment, an apparatus comprises processing circuitry to: receive wireless signal data corresponding to an RFID tag, wherein the wireless signal data comprises signal strength data and signal phase data corresponding to wireless signals transmitted by the RFID tag and received by an RFID reader; generate decomposed signal strength data based on a seasonal decomposition of the signal strength data; generate a frequency-phase curve based on the signal phase data; extract a set of signal strength features based on the decomposed signal strength data; extract a set of signal phase features based on the frequency-phase curve; and detect a motion state of the RFID tag using a machine learning classifier, wherein the machine learning classifier is trained to detect the motion state based on the set of signal strength features and the set of signal phase features.

RFID motion detection for dense RFID tag environments

Methods, apparatus, systems, and articles of manufacture are disclosed for dynamic load balancing for multi-core computing environments. An example apparatus includes a first and a plurality of second cores of a processor, and circuitry in a die of the processor separate from the first and the second cores, the circuitry to enqueue identifiers in one or more queues in the circuitry associated with respective ones of data packets of a packet flow, allocate one or more of the second cores to dequeue first ones of the identifiers in response to a throughput parameter of the first core not satisfying a throughput threshold to cause the one or more of the second cores to execute one or more operations on first ones of the data packets, and provide the first ones to one or more data consumers to distribute the first data packets.

Dynamic load balancing for multi-core computing environments

Behavior detection using RFID in environments with high RFID tag density

In one embodiment, an apparatus may comprise a sensor to detect a plurality of radio signals from one or more transmitters. The apparatus may further comprise a processor to: identify the plurality of radio signals detected by the sensor; detect a proximity of one or more assets based on the plurality of radio signals, wherein the one or more assets are associated with the one or more transmitters; identify the one or more assets based on an identity of the one or more transmitters, wherein each transmitter is associated with a particular asset; identify a plurality of signal characteristics associated with the plurality of radio signals; detect a proximity of a human based on the plurality of signal characteristics; and detect one or more human-asset interactions based on the plurality of signal characteristics.

Privacy-preserving behavior detection

A method is provided. The method includes receiving inputs typed by a user of a keyboard and analyzing the inputs to identify typing errors made by the user. The method also includes customizing a layout of the keyboard to reduce the identified typing errors.

Adaptive keyboard for ultra-mobile devices

Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.

Technologies for automated context-aware media curation

Technologies for representing alternate reality characters in a real-world environment include receiving sensor data from sensors of a sensor network of a home location of an alternate reality character, determining available response to the stimuli represented by the sensor data, and determining an activity of the alternate reality character for a time period based on the available responses. The technologies may also include generating a video of the alternate reality character performing the determined activity superimposed on an image map of a real-world environment of the home location during the time period. Users may view the video in real time or during a time period subsequent to the time period represented in the video. Additionally, the alternate reality character may be transferred to remote computing devices in some embodiments.

Asynchronous representation of alternate reality characters

A portable electronic device may generate a (RF) radio frequency fingerprint that includes information representative of at least a portion of RF signals received at a given physical location. The RF fingerprint may include, for example, a unique identifier and a signal strength that are both logically associated with at least a portion of the received RF signals. The portable electronic device may also receive data representative of a number of environmental parameters about the portable electronic device. These environmental parameters may be measured using sensors carried by the portable electronic device. Considered in combination, these environmental parameters provide an environmental signature for a given location. When combined into a data cluster, the RF fingerprint and the environmental signature may provide an indication of the physical subdivision where the portable electronic device is located. The portable electronic device may then generate a proposed semantic label for the physical subdivision.

Autonomous semantic labeling of physical locations

A serial data link is to be adapted during initialization of the link. Adaptation of the link is to include receiving a pseudorandom binary sequence (PRBS) from a remote agent, analyzing the PRBS to identify characteristics of the data link, and generating metric data describing the characteristics.

High performance interconnect physical layer

A portable consumer device, such as a mobile phone or a tablet computer, may be configured to collect measurements data associated with at least one of movement of the portable consumer device or orientation of the portable consumer device, as well as data associated with an external environment of the portable consumer device. The collected data may be evaluated in order to determine motion of the portable consumer device over time and contextual information associated with the portable consumer device. A user activity may be determined based upon the determined motion and the determined contextual information. As desired, the user activity may be evaluated in association with a suitable application scenario, such as a gaming application scenario.

Detection of user activities by a portable device

A mechanism is described for facilitating personal assistance for curation of multimedia and generation of stories at computing devices according to one embodiment. A method of embodiments, as described herein, includes receiving, by one or more capturing/sensing components at a computing device, one or more media items relating to an event, and capturing a theme from the one or more media items, where the theme is captured based on at least one of activities, textual content, and scenes associated with the event. The method may further include forming a plurality of story elements to generate a story relating to the event, where the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices.

Facilitating personal assistance for curation of multimedia and generation of stories at computing devices

A method may include calculating a first distance between first and second devices and determining a direction of a movement of the first device. The method may further include calculating a second distance between the first and second devices after the movement of the first device and determining the relative position of the first device with respect to the second device based on the direction of the movement, the first distance, and the second distance.

Mobile device position detection

Growing community of inventors

San Francisco, CA, United States of America

Rahul C Shah