Abstract: A method for facilitating vehicle servicing is provided. A first plurality of feature values corresponding to a first plurality of features are determined, for each of a plurality of vehicles. A second plurality of feature values corresponding to a second plurality of features are determined, for each of a plurality of service centers at which the plurality of vehicles were serviced. Based on the first and second pluralities of feature values, a machine learning model is trained to predict service completion times for servicing vehicles. For determining a service completion time for servicing a first vehicle at a first service center, a vehicular dataset of the first vehicle is provided as input to the machine learning model. The machine learning model predicts the service completion time based on the inputted vehicular dataset. The first vehicle is serviced at the first service center in compliance with the predicted service completion time.

Abstract: A method for dynamic maintenance scheduling includes receiving, by a server, first maintenance data, first vehicle data, first booking data, and a plurality of maintenance plans associated with a plurality of vehicles. The plurality of maintenance plans is indicative of historical scheduled maintenance sessions of a corresponding vehicle of the plurality of vehicles. The method includes determination of a plurality of features and a corresponding plurality of feature values for each of the plurality of vehicles. The method includes training a prediction model based on the plurality of features and the corresponding feature values. The method includes determination of a maintenance criterion for a target vehicle based on the trained prediction model and a target dataset associated with the target vehicle. The maintenance criterion indicates an odometer reading range of the target vehicle during which a scheduled maintenance of the target vehicle is to be performed.

Abstract: A method for asset health management is provided. The method includes receiving, first maintenance data, first booking data, first vehicle data, first operational data, and a labelled dataset for a set of vehicles over a first time-interval. The labelled dataset includes at least an actual health index for each vehicle observed over the first time-interval. The method includes determining a first plurality of features and a corresponding first plurality of feature values based on the first maintenance data, the first booking data, the first vehicle data, and the first operational data. The method includes training a prediction model based on the first plurality of features, the first plurality of feature values, and the labelled dataset. The method includes determining a health index of a target vehicle based on the trained first prediction model and a first dataset associated with the target vehicle.

Abstract: A predictive maintenance method for determining a health status of a vehicular system included in a first vehicle is provided. A first dataset is collected for a plurality of vehicles. The first dataset is processed to determine a plurality of features corresponding to the vehicular system and a plurality of feature values for the plurality of features. A classifier is trained, based on the plurality of features, for determining the health status of the vehicular system. A second dataset including second operational data, second vehicle data, second trip data, and second service data for the first vehicle is collected. The second dataset is provided as input to the trained classifier. The health status of the vehicular system included in the first vehicle is determined based on an output of the trained classifier for the second dataset.

Abstract: The present invention relates to triaminopyrimidines and to pharmaceutically acceptable salts thereof, to their use in the treatment and/or prevention of malaria caused by plasmodium species, and to their methods of preparation.

Abstract: The present invention relates to triaminopyrimidines and to pharmaceutically acceptable salts thereof, to their use in the treatment and/or prevention of malaria caused by plasmodium species, and to their methods of preparation.