Oracle

Systems, methods, and other embodiments associated with detecting an electric vehicle charging event. In one embodiment, from electricity consumption data from a known set of electric vehicle owners, the method encodes usage values from time intervals with a symbol from a series of symbols representing a level of electricity consumption during the time interval. The encoding generates an encoded consumption pattern of symbols for each electrical vehicle owner. An EV charge motif is identified that represents an EV charging event. One or more machine learning classifiers is trained to identify the EV charge motifs from the known set of electric vehicle owners and to distinguish from non-charge motifs to identify EV charges from unknown data sets.

Various embodiments of the present technology generally relate to systems and methods for providing a network function (NF) capacity engine. In an example, the NF capacity engine executing on a NF instance, publishes a plurality of session type capacities of the NF instance. The session type capacities include a first session type capacity indicating a storage availability of the NF instance for a first session type and a second session type capacity indicating a storage availability of the NF instance for a second session type. When a network repository function (NRF) receives a discovery request including a plurality of discovery parameters associated with a first session from a consumer NF, the NF capacity engine identifies an NF profile based on the first session type capacity matching the discovery parameters and transmits discovery response identifying the NF instance and containing the first session type capacity to the consumer NF.

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