Abstract: Approaches, techniques, and mechanisms are disclosed for large scale vehicle data collaborative analysis. According to one embodiment, a large amount of data streams is received from a multitude of vehicles. A distributed event streaming system is applied to parse the data streams based on an attribute, such as time sensitive data, location-specific data, or vehicle maintenance, operational, or fault-prevention data. A data container platform instance hosts applications that receive the parsed data streams. Output of an application is transformed into data streams having a common topic. Other applications may access the data streams by topic. Upon receiving an indication that an application has processed a data stream by topic, a decision point may be reached and executed by an external application, triggering an action on a vehicle from the multitude of vehicles.

Abstract: Approaches, techniques, and mechanisms are disclosed for large scale vehicle data collaborative analysis. According to one embodiment, a large amount of data streams is received from a multitude of vehicles. A distributed event streaming system is applied to parse the data streams based on an attribute, such as time sensitive data, location-specific data, or vehicle maintenance, operational, or fault-prevention data. A data container platform instance hosts applications that receive the parsed data streams. Output of an application is transformed into data streams having a common topic. Other applications may access the data streams by topic. Upon receiving an indication that an application has processed a data stream by topic, a decision point may be reached and executed by an external application, triggering an action on a vehicle from the multitude of vehicles. A vehicle computing system accesses topic data streams and performs an action on the vehicle.

Abstract: Approaches, techniques, and mechanisms are disclosed for large scale vehicle data collaborative analysis. According to one embodiment, a large amount of data streams is received from a multitude of vehicles. A distributed event streaming system is applied to parse the data streams based on an attribute, such as time sensitive data, location-specific data, or vehicle maintenance, operational, or fault-prevention data. A data container platform instance hosts applications that receive the parsed data streams. Output of an application is transformed into data streams having a common topic. Other applications may access the data streams by topic. Upon receiving an indication that an application has processed a data stream by topic, a decision point may be reached and executed by an external application, triggering an action on a vehicle from the multitude of vehicles.