Automatic event annotation

A method of automatically predicting and assigning an annotative classification to a new vehicle event, the method comprising:

• using a processor to train a neural network stored in a computer memory on both pre-post event (PPE) data collected from a plurality of vehicle sensors for a plurality of past vehicle events and from image data corresponding to the PPE data for each of the plurality of past vehicle events;
• receiving at a processor, new event data, including new pre-post event (PPE) data collected from a plurality of vehicle sensors, representing a new vehicle event that occurred when a vehicle condition occurred while a driver was driving a vehicle;
• executing, on a processor, the neural network to automatically predict and assign an annotative classification, selected among an array of annotative classifications associated with a vehicle event, to the new vehicle event;
• and
• outputting, to a user display, a representation of the new event data based on the automatically assigned annotative classification for the new vehicle event to reduce a user's time spent reviewing the new event data.

A system of automatically predicting and assigning an annotative classification to a new vehicle event, the system comprising:

• a memory on a vehicle;
• and
• a processor, on the vehicle, coupled to the memory, wherein the processor is configured to receive new vehicle event data, including new pre-post event (PPE) data collected from a plurality of vehicle sensors, representing a new vehicle event that occurred when a vehicle condition occurred while a driver was driving a vehicle;
• a server including a server memory and receiving the PPE data from the processor, wherein the server is configured to execute a neural network stored in the server memory using the new vehicle event data to automatically predict and assign an annotative classification associated with a vehicle event to the new vehicle event, wherein the neural network is trained on both pre-post event (PPE) data collected from a plurality of vehicle sensors for a plurality of past vehicle events and from image data corresponding to the PPE data for each of the plurality of past vehicle events;
• and
• an output display, communicatively coupled to the server, that outputs a representation of the new event data, to a user, based on the automatically assigned annotative classification for the new vehicle event to reduce a user's time spent reviewing the new event data.

A system of automatically predicting and assigning an annotative classification to a new vehicle event, the system comprising:

• a memory on a vehicle;
• a processor, on the vehicle, coupled to the memory, wherein the processor is configured to receive new vehicle event data, including new pre-post event (PPE) data collected from a plurality of vehicle sensors, representing a new vehicle event that occurred when a vehicle condition occurred while a driver was driving a vehicle;
• and
• means for automatically predicting and assigning an annotative classification associated with a vehicle event to the new vehicle event based on a previous manually assigned annotative classification, the means including a neural network stored in a computer memory trained on both pre-post event (PPE) data collected from a plurality of vehicle sensors for a plurality of past vehicle events and from image data corresponding to the PPE data for each of the plurality of past vehicle events;
• and
• an output display that outputs a representation of the new event data, to a user, based on the automatically assigned annotative classification for the new vehicle event to reduce a user's time spent reviewing the new event data.