IP Library Granted Patent US 11,073,907
Granted Patent B1
US 11,073,907 · App. 16/774,491 · Granted Jul 27, 2021

System and method of adjusting of an environment associated with a user

Inventors: Spencer G. Bull (Cedar Park, TX); Tyler Ryan Cox (Austin, TX); Michiel Sebastiaan Emanuel Petrus Knoppert (Amsterdam, NL); Michael S. Gatson (Austin, TX); Vivek Viswanathan Iyer (Austin, TX); Jake Mitchell Leland (Round Rock, TX)
Assignee: Dell Products L.P.
G06F3/013G06F9/453
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Quick Facts
Patent No.
US 11,073,907
App. No.
16/774,491
Granted
Jul 27, 2021
Kind
B1
Abstract

In one or more embodiments, one or more systems, methods, and/or processes may: determine multiple gaze vectors of a user viewing content of a foreground application displayed via a display; determine a pattern based at least on the multiple gaze vectors; determine if the pattern is a search pattern, a static pattern, or a reading pattern; if not so, make a first adjustment of an environment associated with the user; if so, determine if the foreground application is a productivity application; if not so, make the first adjustment of the environment associated with the user; if so, determine if the content of the foreground application is classified as productive; if not so, make the first adjustment of the environment associated with the user; and if so, make a second adjustment of the environment associated with the user, different from the first adjustment of the environment associated with the user.

Claims (60)

1. An information handling system, comprising:

at least one processor; and

a memory medium, coupled to the at least one processor, that stores instructions executable by the at least one processor, which when executed by the at least one processor, cause the information handling system to:

determine a plurality of gaze vectors of a user viewing content of a foreground application displayed via a display;

determine a pattern based at least on the plurality of gaze vectors;

determine if the pattern is a search pattern, a static pattern, or a reading pattern;

if the pattern is the search pattern, the static pattern, or the reading pattern, determine if the foreground application is a productivity application;

if the foreground application is the productivity application, determine if the content of the foreground application is classified as productive;

if the pattern is not the search pattern, the static pattern, or the reading pattern; if the foreground application is not the productivity application; or if the content of the foreground application is not classified as productive, make a first adjustment of an environment associated with the user; and

if the content of the foreground application is classified as productive, make a second adjustment of the environment associated with the user, different from the first adjustment of the environment associated with the user.

2. The information handling system of claim 1 ,

wherein the instructions further cause the information handling system to, if the content of the foreground application is classified as productive, determine that the user is in a micro focus session; and

wherein making the second adjustment of the environment associated with the user is performed in response to determining that the user is in the micro focus session.

3. The information handling system of claim 1 , wherein, to make the second adjustment of the environment associated with the user, the instructions further cause the information handling system to suspend notifications to the user.

4. The information handling system of claim 1 , wherein, to make the second adjustment of the environment associated with the user, the instructions further cause the information handling system to provide light emissions that indicate that the user is not to be interrupted.

5. The information handling system of claim 1 , wherein, to determine the pattern based at least on the plurality of gaze vectors, the instructions further cause the information handling system to utilize an artificial intelligence model to determine the pattern based at least on the plurality of gaze vectors.

6. The information handling system of claim 1 , further comprising:

an artificial intelligence model configured to provide at least one output probability;

wherein the instructions further cause the information handling system to determine that the at least one output probability is greater than or equal to a threshold probability; and

wherein making the second adjustment of the environment associated with the user is performed in response to determining that the at least one output probability is greater than or equal to the threshold probability.

7. The information handling system of claim 1 , further comprising:

an eye tracking device coupled to the at least on processor and configured to track a plurality of movements of an eye of the user;

wherein, to determine the plurality of gaze vectors, the instructions further cause the information handling system to utilize the eye tracking device to track the plurality of movements of the eye of the user.

8. A method, comprising:

determining a plurality of gaze vectors of a user viewing content of a foreground application displayed via a display;

determining a pattern based at least on the plurality of gaze vectors;

determining if the pattern is a search pattern, a static pattern, or a reading pattern;

if the pattern is the search pattern, the static pattern, or the reading pattern, determining if the foreground application is a productivity application;

if the foreground application is the productivity application, determining if the content of the foreground application is classified as productive;

if the pattern is not the search pattern, the static pattern, or the reading pattern; if the foreground application is not the productivity application; or if the content of the foreground application is not classified as productive, making a first adjustment of an environment associated with the user; and

if the content of the foreground application is classified as productive, making a second adjustment of the environment associated with the user, different from the first adjustment of the environment associated with the user.

9. The method of claim 8 , further comprising:

if the content of the foreground application is classified as productive, determining that the user is in a micro focus session;

wherein the making the second adjustment of the environment associated with the user is performed in response to the determining that the user is in the micro focus session.

10. The method of claim 8 , wherein the making the second adjustment of the environment associated with the user includes suspending notifications to the user.

11. The method of claim 8 , wherein the making the second adjustment of the environment associated with the user includes providing light emissions that indicate that the user is not to be interrupted.

12. The method of claim 8 , wherein the determining the pattern based at least on the plurality of gaze vectors includes an artificial intelligence model determining the pattern based at least on the plurality of gaze vectors.

13. The method of claim 8 , further comprising:

an artificial intelligence model providing at least one output probability; and

determining that the at least one output probability is greater than or equal to a threshold probability;

wherein the making the second adjustment of the environment associated with the user is performed in response to the determining that the at least one output probability is greater than or equal to the threshold probability.

14. The method of claim 8 , wherein the determining the plurality of gaze vectors includes an eye tracking device tracking a plurality of movements of an eye of the user.

15. A computer-readable non-transitory memory medium that includes instructions that, when executed by at least one processor of an information handling system, cause the information handling system to:

determine a plurality of gaze vectors of a user viewing content of a foreground application displayed via a display;

determine a pattern based at least on the plurality of gaze vectors;

determine if the pattern is a search pattern, a static pattern, or a reading pattern;

if the pattern is the search pattern, the static pattern, or the reading pattern, determine if the foreground application is a productivity application;

if the foreground application is the productivity application, determine if the content of the foreground application is classified as productive;

if the pattern is not the search pattern, the static pattern, or the reading pattern; if the foreground application is not the productivity application; or if the content of the foreground application is not classified as productive, make a first adjustment of an environment associated with the user; and

if the content of the foreground application is classified as productive, make a second adjustment of the environment associated with the user, different from the first adjustment of the environment associated with the user.

16. The computer-readable non-transitory memory medium of claim 15 ,

wherein the instructions further cause the information handling system to, if the content of the foreground application is classified as productive, determine that the user is in a micro focus session; and

wherein making the second adjustment of the environment associated with the user is performed in response to determining that the user is in the micro focus session.

17. The computer-readable non-transitory memory medium of claim 15 , wherein, to make the second adjustment of the environment associated with the user, the instructions further cause the information handling system to suspend notifications to the user.

18. The computer-readable non-transitory memory medium of claim 15 , wherein, to make the second adjustment of the environment associated with the user, the instructions further cause the information handling system to provide light emissions that indicate that the user is not to be interrupted.

19. The computer-readable non-transitory memory medium of claim 15 , wherein, to determine the pattern based at least on the plurality of gaze vectors includes an artificial intelligence model, the instructions further cause the information handling system to determine the pattern based at least on the plurality of gaze vectors.

20. The computer-readable non-transitory memory medium of claim 15 ,

wherein the information handling system includes an artificial intelligence model that is configured to provide at least one output probability;

wherein the instructions further cause the information handling system to determine that the at least one output probability is greater than or equal to a threshold probability; and

wherein making the second adjustment of the environment associated with the user is performed in response to determining that the at least one output probability is greater than or equal to the threshold probability.

Assignments (9)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053311/0169) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC
Reel/Frame 060438/0742 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053546/0001) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL MARKETING L.P. (ON BEHALF OF ITSELF AND AS SUCCESSOR-IN-INTEREST TO CREDANT TECHNOLOGIES, INC.); DELL INTERNATIONAL L.L.C.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; DELL MARKETING CORPORATION (SUCCESSOR-IN-INTEREST TO FORCE10 NETWORKS, INC. AND WYSE TECHNOLOGY L.L.C.); EMC IP HOLDING COMPANY LLC
Reel/Frame 071642/0001 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (052216/0758) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060438/0680 →
RELEASE OF SECURITY INTEREST AF REEL 052243 FRAME 0773 Recorded Nov 2, 2021
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 058001/0152 →
SECURITY INTEREST Recorded Jun 5, 2020
From: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 053311/0169 →
SECURITY AGREEMENT Recorded Apr 22, 2020
From: CREDANT TECHNOLOGIES INC.; DELL INTERNATIONAL L.L.C.; DELL MARKETING L.P.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; FORCE10 NETWORKS, INC.; WYSE TECHNOLOGY L.L.C.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A.
Reel/Frame 053546/0001 →
SECURITY AGREEMENT Recorded Mar 26, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 052243/0773 →
PATENT SECURITY AGREEMENT (NOTES) Recorded Mar 24, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 052216/0758 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 28, 2020
From: BULL, SPENCER G.; COX, TYLER RYAN; KNOPPERT, MICHIEL SEBASTIAAN EMANUEL PETRUS; GATSON, MICHAEL S.; IYER, VIVEK VISWANATHAN; LELAND, JAKE MITCHELL
To: DELL PRODUCTS L.P.
Reel/Frame 051643/0786 →