At&t Mobility II LLC

AT&T Intellectual Property I, LP

Bellsouth Intellectual Property Corporation

Other

At&t Mobolity II LLC

Stephen Thomas Hardin

Erie Lai Har Lau

Robert Osterwise

Brian Greaves

Charles Martin Link, Ii

Megan Klenzak

John Potts Davis, Iii

Zachary Orlynn Morsbach

Venson Shaw

Jeffrey Mikan

Fulvio Cenciarelli

Jason Sikes

Charles Carey

Thomas Becker

Darwin Parra

Jordan Alexander

Robert Holden

Marvin U Fuller, Jr

Tracey Green

Johnathan Bradley Webb

Sangar Dowlatkhah

Mark D Austin

Jay Daryl Rector

Justin Michael Anthony McNamara

Clifton J Barber

J Brad Webb

Brad Webb

Dennis McCain

Systems and methods may provide for deactivating the Idle mode discontinuous reception (iDRX) for services that require latency that is less than the conventional paging channel values.

Modifying idle mode drx on wireless devices

Power conservation for devices is facilitated based on likelihood of power usage level. An example method can comprise determining, by a first device comprising a processor, that a second device is within a defined proximity of a third device, wherein the third device is determined to be operating in a mode according to a first power consumption operation that satisfies a defined condition, and wherein the operating in the mode according to the first power consumption operation is based on the third device being located at a defined location. The method can also comprise facilitating, by the first device, modification of the mode of the third device based on a determination of a likelihood of usage of a second power consumption operation by the third device. In various embodiments, the third device is configured to operate according to the power save mode or the extended discontinuous reception mode.

Facilitating power conservation for devices based on likelihood of power usage level

Modifying idle mode DRX on wireless devices

Centralized management of the Internet of Things resolves user difficulties. Connected devices may be associated with an owner's or user's electronic profile. The electronic profile may be represented as a graphical user interface (such as a webpage), thus allowing remote management of the connected devices. The owner or user may thus configure the electronic profile to define what electronic data is shared and with whom.

Personalized management of connected devices

Internet-of-things (IOT) devices can be identified based on specific behavioral patterns when their identification data is unknown. Previously identified IOT devices with similar behavioral patterns can be used as a baseline from which to compare data that is available about unknown IOT devices. For example, an IOT device can be pooled with a group of IOT devices based on the frequency with which they connect to a wireless network. Additionally, a confidence level of the unknown device being associated with the group of IOT devices can be generated based on such comparison data.

Facilitation of predictive internet-of-things device identification

A lightweight machine-to-machine (LWM2M) protocol can be utilized as a management layer for other applications pertaining to communication and retrieval of information from hardware peripherals. The applications can be managed via a client and the applications can communicate to the client via a standard proxy or message broker. Consequently, sensor codes can be decoupled from the client codes, thus allowing them to both be independent interchangeable components of a specific device's architecture. Therefore, sensors can be added, removed, and/or manipulated without modifying the underlying management layer.

Facilitation of container management for internet of things devices for 5G or other next generation network

An aspect includes storing data elements in a storage space of a memory device. The storage space is allocated for an account of a subscriber of a universal subscriber identification system. An aspect also includes assigning subscriber-inputted security levels to the data elements. The security levels define varying degrees of access protections associated with the data elements. An aspect further includes generating a security envelope that includes a data element selected from the storage space. The security envelope is configured with an access protection scheme that is commensurate with a corresponding assigned security level. An aspect also includes providing access to the selected data element by another subscriber of the universal subscriber identification system via the security envelope. The access is provided in accordance with the access protection scheme.

Universal subscriber identity recognition and data classification

A method includes receiving, from an aerial vehicle, information related to a plurality of radio-frequency signals detected by the aerial vehicle, and identifying access points that transmitted at least one of the plurality of radio-frequency signals based on at least the information. The method also includes determining a first geographical location of the aerial vehicle based on at least the information and locations associated with the access points and identifying a second geographical location, the second geographical location associated with at least one of an obstacle or a restricted zone. The method also includes controlling a navigation of the aerial vehicle based on at least the first geographical location and the second geographical location.

Radio frequency-based obstacle avoidance

The disclosed subject matter provides for traffic analysis employing timed fingerprint location information. In an aspect, TFL information can be associated with location characteristics for a UE. These location characteristics can describe the motion of the UE. As such, with proper analysis, the motion of the UE can be correlated to traffic patterns. Transportation analytics can employ TFL information to provide real time or near real time traffic information, forecast traffic conditions, or automate response to traffic conditions based on TFL information. Whereas TFL can provide advantages over other types of location information systems, leveraging TFL information in traffic analysis can reflect these advantages. Further, whereas TFL information can be gathered from nearly all modern and many legacy mobile devices, large volumes of TFL information can be employed in related transportation analytics.

Transportation analytics employing timed fingerprint location information

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Suwanee, GA, United States of America

Stephen Thomas Hardin