Provided are systems and methods for contextually providing services via a portable computer at a selected location. According to some embodiments, the systems and methods include processes for determining location-specific information about the selected location, determining status information about a user of the portable computer interface, and displaying an available service to the user on a display screen of the portable computer, the available service being selected based on the location-specific information and the status information.

A disclosed example includes aggregating first performance results of computer-generated machine learning models to generate aggregated performance results, the first performance results based on a comparison of audience member demographic data to training results, the training results generated by the computer-generated machine learning models based on at least one of: (a) a composition of a household, (b) a type of first media, (c) a daypart during which the first media was accessed, or (d) a time at which the first media was accessed; selecting at least one of the computer-generated machine learning models based on a comparison of ones of the first performance results to the aggregated performance results; and applying the at least one of the computer-generated machine learning models to correct a computer-generated error in computer-collected audience measurement data, the computer-collected audience measurement data corresponding to accesses to second media.

A disclosed example includes aggregating first performance results of computer-generated machine learning models to generate aggregated performance results, the first performance results based on a comparison of audience member demographic data to training results, the training results generated by the computer-generated machine learning models based on at least one of: (a) a composition of a household, (b) a type of first media, (c) a daypart during which the first media was accessed, or (d) a time at which the first media was accessed; selecting at least one of the computer-generated machine learning models based on a comparison of ones of the first performance results to the aggregated performance results; and applying the at least one of the computer-generated machine learning models to correct a computer-generated error in computer-collected audience measurement data, the computer-collected audience measurement data corresponding to accesses to second media.

A method of providing a user interface on a mobile communication device to control smart devices in an environment. The method comprises discovering a plurality of smart devices in an environment by a client application executing on a mobile communication device by initiating wireless communication between the mobile communication device and the plurality of smart devices, wherein the client application learns an electronic model identity of each of the discovered smart devices, communicating with a data store by the client application to look-up control interfaces of the discovered smart devices based on the electronic model identities of the smart devices, looking-up predefined environmental preferences associated with the mobile communication device in the data store by the client application, transmitting control commands by the client application to the plurality of smart devices based in part on the looked-up predefined environmental preferences.

Methods and systems are provided for cloud processing data streamed from a vehicle and a home (e.g., any location) associated with a user account. One method includes receiving a data stream from the vehicle entity, where the data stream from the vehicle entity includes metadata from one or more data producing objects of the vehicle entity. And, receiving a data stream from the home entity, where the data stream from the home entity includes metadata from one or more data producing objects of the home entity. The method includes accessing action conditions associated with a user account. The action conditions identify a position where at least one or more states of the metadata from each of the home entity and the vehicle entity intersect. And, each action condition identifies a type or types of control information to be processed. The method includes processing the received metadata from the vehicle entity and the home entity. The processing identifies metadata of the home entity and the vehicle entity that includes an intersection of said at least one or more states of said respective metadata of the home entity and the vehicle entity. The intersection is indicative that a specific action condition being satisfied. The method includes sending, in response to the specific action condition being satisfied, control information to the user account. The logic associated with the user account determines when the control information is sent to the vehicle entity or the home entity for surfacing information or making a setting regarding the satisfied specific action condition. Intersections can also be identified with user devices that may be associated with the user account.

Methods and systems are provided for cloud processing data streamed from a vehicle and a home (e.g., any location) associated with a user account. One method includes receiving a data stream from the vehicle entity, where the data stream from the vehicle entity includes metadata from one or more data producing objects of the vehicle entity. And, receiving a data stream from the home entity, where the data stream from the home entity includes metadata from one or more data producing objects of the home entity. The method includes accessing action conditions associated with a user account. The action conditions identify a position where at least one or more states of the metadata from each of the home entity and the vehicle entity intersect. And, each action condition identifies a type or types of control information to be processed. The method includes processing the received metadata from the vehicle entity and the home entity. The processing identifies metadata of the home entity and the vehicle entity that includes an intersection of said at least one or more states of said respective metadata of the home entity and the vehicle entity. The intersection is indicative that a specific action condition being satisfied. The method includes sending, in response to the specific action condition being satisfied, control information to the user account. The logic associated with the user account determines when the control information is sent to the vehicle entity or the home entity for surfacing information or making a setting regarding the satisfied specific action condition. Intersections can also be identified with user devices that may be associated with the user account.

Embodiments of the present invention provide techniques, systems, and methods for crowdsourcing device recognition to collect device information and identification data from a limited number of network devices and then leverage the collected information with machine learning techniques to expand the starting set in way that the prediction of device attributes like device type, device brand, family and model can be applied on billions of devices.

Embodiments of the present invention provide techniques, systems, and methods for crowdsourcing device recognition to collect device information and identification data from a limited number of network devices and then leverage the collected information with machine learning techniques to expand the starting set in way that the prediction of device attributes like device type, device brand, family and model can be applied on billions of devices.

An information handling system is disclosed and may include a processor, a memory, and a power management unit (PMU). The processor may execute code instructions of a dynamic antenna mapping task agent that is configured to generate an optimized antenna mapping plan for one or more applications, one or more containers of related applications, or a combination thereof, wherein the optimized mapping plan determines which of the one or more applications, one or more containers, or a combination thereof is to use which one of one or more antennas, one or more wireless connections, or a combination thereof within the information handling system while the one or more application, one or more container, or combination thereof is operating within the information handling system.

An information handling system is disclosed and may include a processor, a memory, and a power management unit (PMU). The processor may execute code instructions of a dynamic antenna mapping task agent that is configured to generate an optimized antenna mapping plan for one or more applications, one or more containers of related applications, or a combination thereof, wherein the optimized mapping plan determines which of the one or more applications, one or more containers, or a combination thereof is to use which one of one or more antennas, one or more wireless connections, or a combination thereof within the information handling system while the one or more application, one or more container, or combination thereof is operating within the information handling system.