Abstract: The present invention relates to a system and method for performing vehicle onboard analysis on the data associated with the vehicle and implementing a cloud-based distributed data stream mining algorithm for detecting patterns from vehicle diagnostic and correlating the pattern with the contextual data. The system applies the distributed data mining algorithms for mining the results of the vehicle onboard analytics sent over the wireless network to the server and correlates the analyzed data with the contextual data of the vehicle. The system extracts performance patterns from data, builds predictive models from vehicle diagnostic, and correlates the predicted model with the business process using state of the art link analysis techniques.

Abstract: An improvement of methods and systems using mobile and distributed data stream mining algorithms for mining continuously generated data from different components of a vehicle. The system is designed for both on-board and remote mining and management of the data in order to (1) detect the effect of various engine parameters on fuel consumption behavior, (2) predictive classification of driving patterns and associative indexing of driver performance matrix, (3) resource-constrained anomaly detection for onboard health monitoring, (4) vehicle-to-vehicle social networking and distributed data mining, (5) adaptive placement of advertisements based on vehicle performance profile and (6) onboard emissions analytics computation for wireless emissions monitoring and smog test.

Abstract: The method and system use onboard data stream mining for extracting data patterns from data continuously generated by different components of a vehicle. The system stores the data patterns in an onboard micro database and discards the data. The system uses a resource-constrained, small, lightweight onboard data stream management processor, with onboard data stream mining, an onboard micro database, and a privacy-preserving communication module, which periodically and upon request communicates stored data patterns to a remote control center. The control center uses the data patterns to characterize the typical and unusual vehicle health, driving and fleet behavior.