Abstract: A cognitive cartography system receives a set of legacy documents, such as maps, in the form of physical hardcopy or as simple graphic images. The system, using rules derived from prior training and experience, revises the documents to resolve formal inconsistences like differences in resolution, orientation, or scale. The system assembles the adjusted documents into a seamless composite document represented as a computerized model. Applying learned rules and logic to contextual information received from extrinsic sources, the system infers semantic meaning from features represented by the composite, such as geographical features of a map. These inferences allow the system to derive new knowledge about the represented features, which is added to the model. When additional documents or contextual information are received, the system further refines the model by repeating this procedure. When the model has been sufficiently refined, the system makes the knowledge available to downstream systems.

Abstract: This disclosure relates generally to vehicle diagnostics, and more particularly to systems and methods for vehicle tracking and service prediction. In one embodiment, a processor-implemented vehicle tracking and prediction method is disclosed. The method includes sending an electronic signal to activate in-vehicle data collection by an on-board data aggregator disposed in communication with each of an on-board vehicle computer, via an on-board diagnostic port, and one or more user devices. The method further includes receiving aggregated in-vehicle data from the on-board data aggregator, predicting a future vehicle service event based on the aggregated data, and generating a vehicle valuation metric based on the aggregated data. The method further includes sending a notification to at least one of the on-board vehicle computer and the one or more user devices, where the notification is based on the predicted future vehicle service event and the generated vehicle valuation metric.

Abstract: A method and system for providing a plurality of host systems shared access to data files from a file server. The method includes monitoring a control file for updates, the control file located within a corresponding host directory located within the file server; receiving a request for access to a data file stored on the file server, the access request being written to the control file, the access request including a requested data file operation; performing the requested data file operation in response to the control file being updated with the access request; creating a status file in the host directory in which the requested data file operation was performed upon completion of the requested data file operation; writing status data in the status file, the status data including a result of the performance of the requested data file operation; and allowing access to the host directory in which the requested data file operation was performed in response to the status data being written to the status file.

Abstract: This disclosure relates generally to vehicle diagnostics, and more particularly to systems and methods for vehicle tracking and service prediction. In one embodiment, a processor-implemented vehicle tracking and prediction method is disclosed. The method includes sending an electronic signal to activate in-vehicle data collection by an on-board data aggregator disposed in communication with each of an on-board vehicle computer, via an on-board diagnostic port, and one or more user devices. The method further includes receiving, aggregated in-vehicle data from the on-board data aggregator, predicting a future vehicle service event based on the aggregated data, and generating a vehicle valuation metric based on the aggregated data. The method further includes sending a notification to at least one of the on-board vehicle computer and the one or more user devices, where the notification is based on the predicted future vehicle service event and the generated vehicle valuation metric.

Abstract: A cognitive cartography system receives a set of legacy documents, such as maps, in the form of physical hardcopy or as simple graphic images. The system, using rules derived from prior training and experience, revises the documents to resolve formal inconsistences like differences in resolution, orientation, or scale. The system assembles the adjusted documents into a seamless composite document represented as a computerized model. Applying learned rules and logic to contextual information received from extrinsic sources, the system infers semantic meaning from features represented by the composite, such as geographical features of a map. These inferences allow the system to derive new knowledge about the represented features, which is added to the model. When additional documents or contextual information are received, the system further refines the model by repeating this procedure. When the model has been sufficiently refined, the system makes the knowledge available to downstream systems.

Abstract: This disclosure relates generally to vehicle diagnostics, and more particularly to systems and methods for vehicle tracking and service prediction. In one embodiment, a processor-implemented vehicle tracking and prediction method is disclosed. The method includes sending an electronic signal to activate in-vehicle data collection by an on-board data aggregator disposed in communication with each of an on-board vehicle computer, via an on-board diagnostic port, and one or more user devices. The method further includes receiving aggregated in-vehicle data from the on-board data aggregator, predicting a future vehicle service event based on the aggregated data, and generating a vehicle valuation metric based on the aggregated data. The method further includes sending a notification to at least one of the on-board vehicle computer and the one or more user devices, where the notification is based on the predicted future vehicle service event and the generated vehicle valuation metric.