System and methods for predictive vehicle maintenance

A computer-implemented method for activating one or more system-based actions for one or more target vehicles based upon telematics data, the computer-implemented method performed by one or more processors of a computing system in communication with one or more data sources, the computer-implemented method comprising:

• receiving, in real-time by the one or more processors, the telematics data from one or more sensors associated with the one or more target vehicles;
• processing, by the one or more processors, the telematics data to derive a plurality of features;
• inputting, by the one or more processors, the plurality of features into a trained machine-learning model configured to identify one or more mechanical issue patterns corresponding to one or more mechanical issues;
• receiving, by the one or more processors, the one or more mechanical issues from the trained machine-learning model;
• determining, by the one or more processors, whether the one or more mechanical issues exceeds a severity threshold;
• in response to determining that the one or more mechanical issues exceeds the severity threshold, automatically activating, by the one or more processors, the one or more system-based actions for the one or more target vehicles;
• and
• outputting, by the one or more processors, one or more notifications on a user interface of one or more devices associated with one or more users of the one or more target vehicles, wherein the one or more notifications include the one or more system-based actions and one or more recommended actions.

A system for monitoring an operational condition of one or more target vehicles for predicting an inoperability period to activate one or more system-based actions, comprising:

• one or more processors of a computing system;
• and
• at least one non-transitory computer readable medium storing instructions which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving telematics data or historical data associated with the one or more target vehicles, wherein the telematics data includes one or more of engine diagnostics data, sensor data, or performance data, and wherein the historical data includes one or more of past claims data, past repair and maintenance data, or model-specific performance data;
• processing the telematics data or the historical data associated with the one or more target vehicles to derive a plurality of features;
• inputting the plurality of features into a trained machine-learning model configured to determine the operational condition of the one or more target vehicles and predict the inoperability period for the one or more target vehicles;
• receiving a predicted inoperability period for the one or more target vehicles from the trained machine-learning model;
• automatically executing the one or more system-based actions based upon the predicted inoperability period;
• determining one or more recommended actions based upon the operational condition of the one or more target vehicles;
• and
• outputting one or more notifications on a user interface of one or more devices associated with one or more users of the one or more target vehicles, wherein the one or more notifications includes the one or more recommended actions and an indicator corresponding to the one or more system-based actions.