Abstract: A computer-implemented method, a computer system and a computer program for controlling electric vehicle charging infrastructure that is used by a plurality of electric vehicles, wherein the infrastructure comprises a plurality of charging points. The method comprises receiving schedule information for the electric vehicles, the schedule information including, for each of the electric vehicles, at least one vehicle power characteristic. The method further comprises determining at least one power constraint for each of the electric vehicles based on the vehicle power characteristic. The method further comprises receiving an arrival indication for a respective one of the electric vehicles. The method further comprises assigning the respective electric vehicle to charge at one of the charging points for at least one time interval according to the respective power constraint.

Abstract: A computer-implemented method, a computer system and a computer program for controlling electric vehicle charging infrastructure that is used by a plurality of electric vehicles, wherein the infrastructure comprises a plurality of charging points. The method comprises receiving schedule information for the electric vehicles, the schedule information including, for each of the electric vehicles, at least one vehicle power characteristic. The method further comprises determining at least one power constraint for each of the electric vehicles based on the vehicle power characteristic. The method further comprises receiving an arrival indication for a respective one of the electric vehicles. The method further comprises assigning the respective electric vehicle to charge at one of the charging points for at least one time interval according to the respective power constraint.

Abstract: Methods, systems, and computer-readable storage media for ranking anomaly detection algorithms, including operations of receiving a set of unlabeled data from one or more sensors in a plurality of sensors of an internet of things, generating a plurality of data distributions corresponding to the set of unlabeled data by using a plurality of anomaly detection algorithms, and ranking the plurality of anomaly detection algorithms relative to the set of unlabeled data based on a distance between a first quantile and a second quantile of each of the plurality of data distributions.

Abstract: Methods, systems, and computer-readable storage media for ranking anomaly detection algorithms, including operations of receiving a set of unlabeled data from one or more sensors in a plurality of sensors of an internet of things, generating a plurality of data distributions corresponding to the set of unlabeled data by using a plurality of anomaly detection algorithms, and ranking the plurality of anomaly detection algorithms relative to the set of unlabeled data based on a distance between a first quantile and a second quantile of each of the plurality of data distributions.