Abstract:
The present disclosure provides techniques for automatically changing device display orientation. A computing device includes an inertial measurement unit (IMU), a camera to detect user eye position on a continuing basis, a display, memory, and at least one processor to execute machine-readable instructions to cause the at least one processor to: access data from the inertial measurement unit IMU; analyze IMU data for changes in an orientation of the electronic device; determine the user eye position in relation to the display; and orient the display in accordance with the orientation of the electronic device.
Abstract:
Apparatuses, methods, and computer-readable media for a proximity-based connection facilitation device (“PBC”) may be described which may facilitate discovery and connection to computing devices. The PBC may present visual elements representing devices based on their locations, such as their proximity to the PBC. The PBC may present visual elements for a limited set of devices. The PBC may present computing devices in a visual manner that may depict their proximity to the PBC. The PBC may also provide for facilitated connection to devices that are not as proximate to the PBC. The PBC may facilitate identification of devices that are proximate to an identified device. By facilitating a user in selecting a first device and then visualizing devices proximate to the first device, the PBC may facilitate a user in chaining from a first device to devices that are less easily identified. Other embodiments may be described and/or claimed.
Abstract:
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.
Abstract:
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.
Abstract:
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.
Abstract:
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.
Abstract:
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.
Abstract:
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.
Abstract:
Apparatuses, methods, and computer-readable media for a proximity-based connection facilitation device (“PBC”) may be described which may facilitate discovery and connection to computing devices. The PBC may present visual elements representing devices based on their locations, such as their proximity to the PBC. The PBC may present visual elements for a limited set of devices. The PBC may present computing devices in a visual manner that may depict their proximity to the PBC. The PBC may also provide for facilitated connection to devices that are not as proximate to the PBC. The PBC may facilitate identification of devices that are proximate to an identified device. By facilitating a user in selecting a first device and then visualizing devices proximate to the first device, the PBC may facilitate a user in chaining from a first device to devices that are less easily identified. Other embodiments may be described and/or claimed.
Abstract:
Systems and methods may provide for identifying a virtual geo-fence for a plurality of devices. Additionally, a condition may be detected with respect to two or more devices in the plurality of devices, wherein a status determination may be conducted as to whether at least one of the two or more devices has left the virtual geo-fence based on the condition.