Verizon Patent and Licensing Inc.

Vijaya Paduvalli

Jin Yang

Krishna K Bellamkonda

Greg Augustus Rusu

Arda Aksu

Ahmed Moussa

Laszlo Joseph Herczku

In some implementations, a system may obtain dynamic radio frequency (RF) response information associated with a user equipment and additional dynamic information associated with the user equipment. The system may determine, based on the dynamic RF response information and the additional dynamic information, a current behavior profile of the user equipment. The system may compare the current behavior profile and a baseline behavior profile of the user equipment to generate comparison information. The system may grant or deny, based on the comparison information, the user equipment access to a resource of a private network.

Systems and methods for authentication based on dynamic radio frequency response information

A system receives, from a user equipment, a request for access to a wireless communication network and identifies, based on the request, baseline radio frequency (RF) response information associated with the user equipment. The system obtains dynamic RF response information associated with the user equipment and authenticates, based on the dynamic RF response information and the baseline RF response information, the user equipment. The system thereby grants the user equipment access to the wireless communication network and determines context information associated with the user equipment. The system generates, based on the baseline RF response information and the context information, user equipment profile information and sends, to a base station associated with the wireless communication network, the user equipment profile information to facilitate access to the wireless communication network by the user equipment.

Systems and methods for providing access to a wireless communication network based on radio frequency response information and context information

A device may receive device data identifying Internet of Things (IoT) devices and may receive network data identifying network traffic patterns associated with the IoT devices. The device may process the device data and the network data, with a machine learning model, to determine parameters for charging each of the IoT devices and may determine that a particular IoT device of the IoT devices requires charging based on particular parameters associated with the particular IoT device. The device may receive location data identifying a location of the particular IoT device and may cause, based on the location data, one or more chargers to wirelessly provide a radio frequency power beam to the particular IoT device based on the particular parameters.

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Fremont, CA, United States of America

Vijaya Paduvalli