Abstract:
Some demonstrative embodiments include apparatuses, systems and/or methods of wireless power transfer. For example, an apparatus may include a wireless power controller to communicate between a Wireless Power Receiver (WPR) and a Wireless Power Transmitter (WPT) an indication of a requested amount of power to be provided from the WPT to the WPR via a wireless power signal, said indication is in the form of a load modulation event within a predefined time interval, said load modulation event comprises a change in a level of a magnetic field of said wireless power signal, a duration of said load modulation event is based on the requested amount of power to be provided from the WPT to the WPR.
Abstract:
Some demonstrative embodiments include apparatuses, systems and/or methods of wireless power transfer. For example, an apparatus may include a wireless power controller to communicate between a Wireless Power Receiver (WPR) and a Wireless Power Transmitter (WPT) an indication of a requested amount of power to be provided from the WPT to the WPR via a wireless power signal, said indication is in the form of a load modulation event within a predefined time interval, said load modulation event comprises a change in a level of a magnetic field of said wireless power signal, a duration of said load modulation event is based on the requested amount of power to be provided from the WPT to the WPR.
Abstract:
Some demonstrative embodiments include apparatuses, systems and/or methods of wireless power transfer. For example, an apparatus may include a controller to control a Wireless Power Transmitter (WPT) to transmit a sequence of probes during a detection period, to detect a Wireless Power Receiver (WPR) based on a detected induced load on the WPT during transmission of probe of the sequence of probes, and, upon detection of the WPR, to control the WPT to transmit a wireless charging signal to the WPR.
Abstract:
Various embodiments for automatically distinguishing between users of a handheld device are described. An embodiment includes collecting sensor data from a user interacting with a handheld device, where the sensor data is collected via embedded sensors in the handheld device. The embodiment further includes distinguishing the user from other users of the handheld device via the collected sensor data, at least one embedded machine learning algorithm and a profile for the user. Other embodiments are described and claimed.
Abstract:
Various embodiments for automatically distinguishing between users of a handheld device are described. An embodiment includes collecting sensor data from a user interacting with a handheld device, where the sensor data is collected via embedded sensors in the handheld device. The embodiment further includes distinguishing the user from other users of the handheld device via the collected sensor data, at least one embedded machine learning algorithm and a profile for the user. Other embodiments are described and claimed.