Facial recognition technology for improving motor carrier regulatory compliance

1. A system comprising:

one or more computer processors;

one or more computer memories; and

a set of instructions incorporated into the one or more computer processors, the set of instruction configuring the one or more computer processors to perform operations for improving compliance with one or more regulations pertaining to vehicle driving records, the operations comprising:

receiving one or more digital images from a camera mounted in a vehicle, the camera configured to capture the one or more digital images when a predefined event occurs, the one or more digital images having timestamps; and

based on a determination that the vehicle has hours of service that have not been assigned to a driver, identifying a subset of the one or more digital images corresponding to the hours of service based on the timestamps, processing the subset of the one or more digital images to identify a correspondence between an image of a face of a person included in the one or more digital images and an image of a face of a known person, wherein the identification of the correspondence is based on the image of the face of the person having a degree of similarity to a club of images that transgresses a threshold degree of similarity, the club of images captured while the known person was operating the vehicle or an additional vehicle, and based on the correspondence transgressing a threshold level of correspondence, generating a user interface for presentation on a client device, the user interface including an interactive user interface element for accepting or rejecting a recommendation to assign the known person as the driver.

2. The system of claim 1 , the operations further comprising, based on the accepting or rejecting of the recommendation, modifying the club, the modifying including adding the image of the face of the person to the club or removing an image from the club.

3. The system of claim 1 , the operations further comprising generating a training data set based on the accepting or rejecting of the recommendation, the training data set to be used to generate a replacement machine-learned model for a machine-learned model used to identify the correspondence.

4. The system of claim 1 , the operations further comprising, based on the accepting or rejection of the recommendation, generating an additional user interface, the additional user interface including an interactive user interface element for accepting or rejecting an additional recommendation to assign the known person as the driver for additional unassigned hours of service.

5. The system of claim 1 , the operations further comprising generating an additional user interface for presentation on a client device, the additional user interface including one or more user interface elements for selecting the one or more predefined events from a plurality of predefined events, the plurality of predefined events including a starting of movement of the vehicle after a length of time of resting of the vehicle.

6. The system of claim 1 , the operations further comprising based on a determination that the vehicle or an additional vehicle has additional hours of service that have not been assigned, automatically assigning the driver to the additional hours of service, the automatically assigning based on an application of a machine-learned model to one or more additional digital images captured from the camera mounted in the vehicle or a camera mounted in the additional vehicle, the machine-learned model having been trained using a configurable threshold amount of training data pertaining to the driver.

7. A method comprising:

performing operations for improving compliance with one or more regulations pertaining to vehicle driving records, the operations comprising:

receiving one or more digital images from a camera mounted in a vehicle, the camera configured to capture the one or more digital images when a predefined event occurs, the one or more digital images having timestamps; and

based on a determination that the vehicle has hours of service that have not been assigned to a driver, identifying a subset of the one or more digital images corresponding to the hours of service based on the timestamps, processing the subset of the one or more digital images to identify a correspondence between an image of a face of a person included in the one or more digital images and an image of a face of a known person, wherein the identification of the correspondence is based on the image of the face of the person having a degree of similarity to a club of images that transgresses a threshold degree of similarity, the club of images captured while the known person was operating the vehicle or an additional vehicle, and based on the correspondence transgressing a threshold level of correspondence, generating a user interface for presentation on a client device, the user interface including an interactive user interface element for accepting or rejecting a recommendation to assign the known person as the driver.

8. The method of claim 7 , the operations further comprising, based on the accepting or rejecting of the recommendation, modifying the club, the modifying including adding the image of the face of the person to the club or removing an image from the club.

9. The method of claim 7 , the operations further comprising generating a training data set based on the accepting or rejecting of the recommendation, the training data set to be used to generate a replacement machine-learned model for a machine-learned model used to identify the correspondence.

10. The method of claim 7 , the operations further comprising, based on the accepting or rejection of the recommendation, generating an additional user interface, the additional user interface including an interactive user interface element for accepting or rejecting an additional recommendation to assign the known person as the driver for additional unassigned hours of service.

11. The method of claim 7 , the operations further comprising generating an additional user interface for presentation on a client device, the additional user interface including one or more user interface elements for selecting the one or more predefined events from a plurality of predefined events, the plurality of predefined events including a starting of movement of the vehicle after a length of time of resting of the vehicle.

12. The method of claim 7 , the operations further comprising generating an additional user interface for presentation on a client device, the additional user interface including one or more user interface elements for specifying a different rate of capture of the one or more digital images for the predefined event and an additional predefined event.

13. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations for improving compliance with one or more regulations pertaining to vehicle driving records, the operations comprising:

receiving one or more digital images from a camera mounted in a vehicle, the camera configured to capture the one or more digital images when a predefined event occurs, the one or more digital images having timestamps; and

based on a determination that the vehicle has hours of service that have not been assigned to a driver, identifying a subset of the one or more digital images corresponding to the hours of service based on the timestamps, processing the subset of the one or more digital images to identify a correspondence between an image of a face of a person included in the one or more digital images and an image of a face of a known person, wherein the identification of the correspondence is based on the image of the face of the person having a degree of similarity to a club of images that transgresses a threshold degree of similarity, the club of images captured while the known person was operating the vehicle or an additional vehicle, and based on the correspondence transgressing a threshold level of correspondence, generating a user interface for presentation on a client device, the user interface including an interactive user interface element for accepting or rejecting a recommendation to assign the known person as the driver.

14. The non-transitory machine-readable storage medium of claim 13 , the operations further comprising, based on the accepting or rejecting of the recommendation, modifying the club, the modifying including adding the image of the face of the person to the club or removing an image from the club.

15. The non-transitory machine-readable storage medium of claim 13 , the operations further comprising generating a training data set based on the accepting or rejecting of the recommendation, the training data set to be used to generate a replacement machine-learned model for a machine-learned model used to identify the correspondence.

16. The non-transitory machine-readable storage medium of claim 13 , the operations further comprising, based on the accepting or rejection of the recommendation, generating an additional user interface, the additional user interface including an interactive user interface element for accepting or rejecting an additional recommendation to assign the known person as the driver for additional unassigned hours of service.

17. The non-transitory machine-readable storage medium of claim 13 , the operations further comprising generating an additional user interface for presentation on a client device, the additional user interface including one or more user interface elements for selecting the one or more predefined events from a plurality of predefined events, the plurality of predefined events including a starting of movement of the vehicle after a length of time of resting of the vehicle.