Patent ID: 11922378
Assignee: TEKION CORP
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 12:
13. A non-transitory computer-readable medium comprising memory with instructions encoded thereon that, when executed, cause one or more processors to perform operations, the instructions comprising instructions to:
receive, by way of human input into a user interface relating to a vehicle inspection, current vehicle data describing a current state of each of a plurality of components of a vehicle;
responsive to receiving the current vehicle data, access historical vehicle data associated with the vehicle, the historical vehicle data describing a set of services previously performed on the vehicle;
accessing user profile data indicating one or more vehicle servicing preferences of an owner of the vehicle;
apply the current vehicle data, the historical vehicle data, and the one or more vehicle servicing preferences of the owner of the vehicle as input to a supervised machine learning model configured to generate a set of recommended services to be performed on the vehicle, wherein the supervised machine learning model was trained by:
responsive to determining that insufficient training data exists for a same vehicle type to the vehicle, determining a set of additional vehicles that have a threshold similarity to the vehicle by applying an unsupervised machine learning model to attributes of the vehicle and receiving as output from the unsupervised machine learning model an identification of each of the set of additional vehicles;
responsive to determining the set of additional vehicles that have the threshold similarity to the vehicle, accessing labeled training data corresponding to each additional vehicle of the set of additional vehicles, wherein each label of each training example of the labeled training data indicates a set of services performed on a respective additional vehicle, and
training the supervised machine learning model using the labeled training data, the supervised machine learning model trained to output a set of recommended services to be performed for a given vehicle based on inputs of given current vehicle data and given historical vehicle data for the given vehicle and the one or more vehicle servicing preferences of the owner of the vehicle, the one or more vehicle servicing preferences of the owner of the vehicle influencing whether a given service is included in the set of recommended service based on a likelihood that a person having that set of preferences would accept the given service; and

output for display the set of recommended services to be performed on the vehicle to a user.