Abstract: A digital network assistant which can detect network anomalies, identify actions likely to remediate them, and assist the user in carrying out those actions. In particular, a digital network assistant constantly monitors data streams associated with the network to determine key performance indicators for the network. When these key performance indicators indicate a network anomaly, the digital network assistant associates it with a digital string to one or more actions likely to remediate similar network issues. The digital network assistant can take these actions automatically or present them to a user to be taken. The system can also aid the user in taking the required actions via an augmented reality interface. In addition, the system can create narratives embedding findings from data analysis eliminating subjectivity. The system can also find optimal parameter sets by continuously analyzing anomaly-free parts of the network and their key performance indicators.

Abstract: A digital network assistant which can detect network anomalies, identify actions likely to remediate them, and assist the user in carrying out those actions. In particular, a digital network assistant constantly monitors data streams associated with the network to determine key performance indicators for the network. When these key performance indicators indicate a network anomaly, the digital network assistant associates it with a digital string to one or more actions likely to remediate similar network issues. The digital network assistant can take these actions automatically or present them to a user to be taken. The system can also aid the user in taking the required actions via an augmented reality interface. In addition, the system can create narratives embedding findings from data analysis eliminating subjectivity. The system can also find optimal parameter sets by continuously analyzing anomaly-free parts of the network and their key performance indicators.

Abstract: A digital network assistant which can detect network anomalies, identify actions likely to remediate them, and assist the user in carrying out those actions. In particular, a digital network assistant constantly monitors data streams associated with the network to determine key performance indicators for the network. When these key performance indicators indicate a network anomaly, the digital network assistant associates it with a digital string to one or more actions likely to remediate similar network issues. The digital network assistant can take these actions automatically or present them to a user to be taken. The system can also aid the user in taking the required actions via an augmented reality interface. In addition, the system can create narratives embedding findings from data analysis eliminating subjectivity. The system can also find optimal parameter sets by continuously analyzing anomaly-free parts of the network and their key performance indicators.

Abstract: Computer implemented methods and systems are provided for intelligent service traffic management. A request is received from a mobile device for mobile device service. A location of the mobile device is determined. One or more retail service centers is identified based on the location of the mobile device. A wait for the mobile device service is estimated at each of the retail service centers. The estimated wait and each location of the retail service centers are provided to the mobile device.