Aspects of the subject disclosure may include, for example, obtaining quality of experience (QoE) information associated with a service from each communication device of a first group of communication devices over a communication network resulting in a group of QoE information. Each communication device of the first group of communication devices generates biometric information resulting in a group of biometric information. Each communication device of the first group of communication devices determines the QoE information based on the biometric information. Further embodiments include generating a group of QoE metrics associated with the service based on the group of QoE information, and adjusting an allocation of first network resources associated with the service based on the group of QoE metrics. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, obtaining quality of experience (QoE) information associated with a service from each communication device of a first group of communication devices over a communication network resulting in a group of QoE information. Each communication device of the first group of communication devices generates biometric information resulting in a group of biometric information. Each communication device of the first group of communication devices determines the QoE information based on the biometric information. Further embodiments include generating a group of QoE metrics associated with the service based on the group of QoE information, and adjusting an allocation of first network resources associated with the service based on the group of QoE metrics. Other embodiments are disclosed.

In general, in one aspect, embodiments relate to a method for managing technical support sessions, the method comprising: generating a first plurality of local technical support sessions, transmitting at least a portion of the first plurality of local technical support sessions to a technical support hub, and receiving a local technical support session from a second technical support system, wherein the local technical support session is presented to a technical support person (TSP) during a technical support session performed on a first technical support system.

In general, in one aspect, embodiments relate to a method for managing technical support sessions, the method comprising: generating a first plurality of local technical support sessions, transmitting at least a portion of the first plurality of local technical support sessions to a technical support hub, and receiving a local technical support session from a second technical support system, wherein the local technical support session is presented to a technical support person (TSP) during a technical support session performed on a first technical support system.

Methods and systems of notifying a service provider regarding Wi-Fi gateway issues are shown and disclosed. In one embodiment, the method includes detecting, via a Wi-Fi gateway, an issue related to the Wi-Fi gateway, and embedding, via the Wi-Fi gateway, information related to the detected issue in an IEEE 802.11 management frame. The method additionally includes broadcasting, via the Wi-Fi gateway, the IEEE 802.11 management frame with the embedded information, and receiving, via an application running on a Wi-Fi device, the IEEE 802.11 management frame with the embedded information. The method further includes transmitting, via the application running on the Wi-Fi device, the embedded information to the service provider.

Methods and systems of notifying a service provider regarding Wi-Fi gateway issues are shown and disclosed. In one embodiment, the method includes detecting, via a Wi-Fi gateway, an issue related to the Wi-Fi gateway, and embedding, via the Wi-Fi gateway, information related to the detected issue in an IEEE 802.11 management frame. The method additionally includes broadcasting, via the Wi-Fi gateway, the IEEE 802.11 management frame with the embedded information, and receiving, via an application running on a Wi-Fi device, the IEEE 802.11 management frame with the embedded information. The method further includes transmitting, via the application running on the Wi-Fi device, the embedded information to the service provider.

System trains machine learning model to determine content data, metadata, and context data for support ticket communications, in response to receiving support ticket communications. Machine learning model receives communication associated with support ticket, and determines content data, metadata, and context data for communication. System converts content data, metadata, and context data for communication into first impulse for first channel and second impulse for second channel. System determines first channel value based on first type of conversion of first impulse and any impulses for first channel that are converted from data that is determined for support ticket event. System determines second channel value based on second type of conversion of second impulse and any impulses for second channel that are converted from data that is determined for support ticket event. System uses first channel value and second channel value to generate priority associated with support ticket, and outputs priority.

Embodiments relate to the autonomous remediation of IT asset records in accordance with rules-based asset management policies. An IT asset record associated with an IT asset and having a first piece of IT asset information is received and evaluated for compliance in accordance with defined asset management rules. The asset management rules require the IT asset record to include both the first piece and a second piece of IT asset information. In view of the rules, a determination is made that the IT asset record requires remediation. Based on a determination that the IT asset record requires remediation, a decision-tree machine learning model is utilized to infer, based on IT asset information available in the IT asset record, at least the second piece of IT asset information to place the IT asset record in compliance with the asset management rules.

Embodiments relate to the autonomous remediation of IT asset records in accordance with rules-based asset management policies. An IT asset record associated with an IT asset and having a first piece of IT asset information is received and evaluated for compliance in accordance with defined asset management rules. The asset management rules require the IT asset record to include both the first piece and a second piece of IT asset information. In view of the rules, a determination is made that the IT asset record requires remediation. Based on a determination that the IT asset record requires remediation, a decision-tree machine learning model is utilized to infer, based on IT asset information available in the IT asset record, at least the second piece of IT asset information to place the IT asset record in compliance with the asset management rules.

A method of an automatic support service that includes receiving a request for additional assistance for an error from a user interface, retrieving error information from a logging system for the error, generating an error information collection interface, in response to the request, populating the error information collection interface with the error information from the logging system, sending the error information collection interface to be displayed to the user by the user interface, and receiving additional error information from the user via the error information collection interface.