Biometric-based punch-in/punch-out management

1. A method comprising:

capturing, by use of a processor, training biometrics for a plurality of users;

training a biometric algorithm with the training biometrics;

presenting a threshold user interface to an administrator that compares a punch-in match level and a punch-out match level for one or more identification biometrics that do not satisfy a match threshold for the plurality of users and a match threshold control for adjusting the match threshold;

adjusting the match threshold in response to the match threshold control;

capturing an identification biometric in a punch-in operation/punch-out operation for a first user of the plurality of users;

determining a match level for the identification biometric based on the biometric algorithm;

in response to the match level not satisfying the match threshold during the punch-in operation/punch-out operation, presenting an attendance user interface comprising punch-in/punch-out times, corresponding identification biometrics and match levels, and attendance information for the first user, wherein suspect identification biometrics are highlighted; and

receiving a validation or invalidation of the punch-in operation/punch-out operation from the administrator.

2. The method of claim 1 , the method further comprising determining an identification biometric location.

3. The method of claim 2 , wherein the suspect identification biometrics are identified as a function of one or more of the punch-in/punch-out times, the corresponding match levels, the attendance information, the identification biometric location relative to a geo-fence, a time discrepancy, a manual override, a punch-in device, and tangible assets.

4. The method of claim 3 , wherein the punch-in/punch-out times, the corresponding match levels, the attendance information, the identification biometric location relative to the geofence, the time discrepancy, the manual override, the punch-in device, and the tangible assets are searchable.

5. The method of claim 1 , the method further comprising automatically validating the identification biometric if the match level satisfies the match threshold.

6. The method of claim 1 , wherein the biometrics are a biometric type selected from the group consisting of an image, a voice print, a retina scan, and a fingerprint.

7. The method of claim 1 , the method further comprising recursively training the biometric algorithm with the suspect identification biometrics.

8. The method of claim 1 , wherein the training biometrics are filtered by one or more of the punch-in/punch-out times, the corresponding match levels, the attendance information, an identification biometric location relative to a geofence, a time discrepancy, a manual override, a punch-in device, and tangible assets.

9. The method of claim 1 , wherein the biometric algorithm is selected from the group consisting of a statistical algorithm, a recursive neural network, a convolutional neural network, and a long short term memory (LSTM) network.

10. An apparatus comprising:

a processor;

a memory storing code executable by the processor to perform:

capturing training biometrics for a plurality of users;

training a biometric algorithm with the training biometrics;

presenting a threshold user interface to an administrator that compares a punch-in match level and a punch-out match level for one or more identification biometrics that do not satisfy a match threshold for the plurality of users and a match threshold control for adjusting the match threshold;

adjusting the match threshold in response to the match threshold control;

capturing an identification biometric in a punch-in operation/punch-out operation for a first user of the plurality of users;

determining a match level for the identification biometric based on the biometric algorithm; and

in response to the match level not satisfying the match threshold during the punch-in operation/punch-out operation, presenting an attendance user interface comprising punch-in/punch-out times, corresponding identification biometrics and match levels, and attendance information for the first user, wherein suspect identification biometrics are highlighted, and

receiving a validation or invalidation of the punch-in operation/punch-out operation from the administrator.

11. The apparatus of claim 10 , the processor further determining an identification biometric location.

12. The apparatus of claim 11 , wherein the suspect identification biometrics are identified as a function of one or more of the punch-in/punch-out times, the corresponding match levels, the attendance information, the identification biometric location relative to a geo-fence, a time discrepancy, a manual override, a punch-in device, and tangible assets.

13. The apparatus of claim 12 , wherein the punch-in/punch-out times, the corresponding match levels, the attendance information, the identification biometric location relative to the geofence, the time discrepancy, the manual override, the punch-in device, and the tangible assets are searchable.

14. The apparatus of claim 10 , the processor further automatically validating the identification biometric if the match level satisfies the match threshold.

15. The apparatus of claim 10 , wherein the biometrics are a biometric type selected from the group consisting of an image, a voice print, a retina scan, and a fingerprint.

16. The apparatus of claim 10 , the method further comprising recursively training the biometric algorithm with the suspect identification biometrics.

17. The apparatus of claim 10 , wherein the training biometrics are filtered by one or more of the punch-in/punch-out times, the corresponding match levels, the attendance information, an identification biometric location relative to a geofence, a time discrepancy, a manual override, a punch-in device, and tangible assets.

18. The apparatus of claim 10 , wherein the biometric algorithm is selected from the group consisting of a statistical algorithm, a recursive neural network, a convolutional neural network, and a long short term memory (LSTM) network.

19. A program product comprising a non-transitory computer readable storage medium storing code executable by a processor to perform:

capturing training biometrics for a plurality of users;

training a biometric algorithm with the training biometrics;

presenting a threshold user interface to an administrator that compares a punch-in match level and a punch-out match level for one or more identification biometrics that do not satisfy a match threshold for the plurality of users and a match threshold control for adjusting the match threshold;

adjusting the match threshold in response to the match threshold control;

capturing an identification biometric in a punch-in operation/punch-out operation for a first user of the plurality of users;

determining a match level for the identification biometric based on the biometric algorithm;

in response to the match level not satisfying the match threshold during the punch-in operation/punch-out operation, presenting an attendance user interface comprising punch-in/punch-out times, corresponding identification biometrics and match levels, and attendance information for the first user, wherein suspect identification biometrics are highlighted; and

receiving a validation or invalidation of the punch-in operation/punch-out operation from the administrator.

20. The program product of claim 19 , wherein the suspect identification biometrics are identified as a function of one or more of the punch-in/punch-out times, the corresponding match levels, the attendance information, the identification biometric location relative to a geo-fence, a time discrepancy, a manual override, a punch-in device, and tangible assets.