Intel Corporation

Apple Inc.

Ke-Yu Chen

Rahul C Shah

Chieh-Yih Wan

Cagri Tanriover

Shao-Wen Yang

Gierad Laput

Addicam V Sanjay

Jun Gong

James T Curran

Scott Thomas

Embodiments described herein provide techniques to enable spatial sensor data from multiple devices to be fused into a single coordinate space. This fused sensor data can then be processed into a point cloud. Point cloud data can then be transformed to enable the classification of objects detected within the sensor data. Features within multiple feature spaces can be extracted from the point cloud data for use in classification. Classification of objects can also be used to correlate objects detected by multiple sensor equipped devices to determine a coordinate space transformation between those devices.

Machine learning based object identification

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

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

Growing community of inventors

San Ramon, CA, United States of America

Ke-Yu Chen