Generating multi-monitor recommendations
Systems and methods for generating multi-monitor recommendations. In some embodiments, an Information Handling System (IHS) may include: a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: collect window information during use of the IHS; and create a multi-monitor recommendation based, at least in part, upon the window information.
1. An Information Handling System (IHS), comprising:
a processor; and
a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to:
collect window information of a current arrangement of a plurality of existing monitors during use of the IHS;
determine an expected productivity gain of a user using the collected window information, the expected productivity gain comprising an estimated productivity via use of an adopted arrangement of the existing monitors and one or more yet to be implemented monitors relative to a measured productivity via use of only the existing monitors; and
create a multi-monitor recommendation based, at least in part, upon the expected productivity gain, the multi-monitor recommendation comprising information associated with a suggestion to implement the adopted arrangement of the plurality of monitors that are configured to display one or more windows associated with the window information.
2. The IHS of claim 1 , wherein the collected window information comprises: an identification of a foreground window, and coordinates of the foreground window.
3. The IHS of claim 1 , wherein the collected window information comprises: an identification of a background window, coordinates of the background window, and a last time the background window received at least one of a keyboard or mouse input.
4. The IHS of claim 1 , wherein the program instructions, upon execution, cause the IHS to remove at least one record from the collected window information in response to the record being associated with an application that has been closed.
5. The IHS of claim 1 , wherein the program instructions, upon execution, cause the IHS to remove at least one record from the collected window information in response to the record being associated with an application that has not received at least one of a keyboard or mouse input for a specified amount of time.
6. The IHS of claim 1 , wherein the program instructions, upon execution, cause the IHS to use the collected window information to determine a number of background windows that overlap a foreground window, and wherein the multi-monitor recommendation is created, at least in part, based upon the number of background windows.
7. The IHS of claim 1 , wherein the program instructions, upon execution, cause the IHS to use the collected window information to determine a number of instances of background and foreground window swapping within a specified time duration, and wherein the multi-monitor recommendation is created, at least in part, based upon the number of instances of background and foreground window swapping.
8. The IHS of claim 1 , wherein the program instructions, upon execution, cause the IHS to use the collected window information to determine an amount of overlap between a background window and a foreground window, and wherein the multi-monitor recommendation is created, at least in part, based upon the amount of overlap.
9. The IHS of claim 1 , wherein the program instructions, upon execution, cause the IHS to use the collected window information to identify at least one edge of a current display that is insufficient to render an entire background or foreground window, and wherein the multi-monitor recommendation is created, at least in part, based upon the identified edge.
10. The IHS of claim 1 , wherein to generate the multi-monitor recommendation, the program instructions, upon execution, cause the IHS to compare the collected window information against one or more recommendation thresholds set based upon historical recommendations.
11. The IHS of claim 1 , wherein to generate the multi-monitor recommendation, the program instructions, upon execution, cause the IHS to process the collected window information using a machine learning (ML) engine.
12. A memory storage device having program instructions stored thereon that, upon execution by one or more processors of an Information Handling System (IHS), cause the IHS to:
collect window information of a current arrangement of a plurality of existing monitors during use of the IHS;
determine an expected productivity gain using the collected window information, the expected productivity gain comprising an estimated productivity via use of an adopted arrangement of the existing monitors and one or more yet to be implemented monitors relative to a measured productivity via use of only the existing monitors; and
create a multi-monitor recommendation based, at least in part, upon the expected productivity gain of a user, wherein the multi-monitor recommendation comprises information associated with a suggestion to implement the adopted arrangement of the plurality of monitors that are configured to display one or more windows associated with the window information, wherein the suggested adopted arrangement comprises a suggested arrangement of the existing monitors and one or more yet to be implemented monitors relative to one another.
13. A method, comprising:
collecting window information of a current arrangement of a plurality of existing monitors during use of an Information Handling System (IHS);
determining an expected productivity gain using the collected window information, the expected productivity gain comprising an estimated productivity via use of an adopted arrangement of the existing monitors and one or more yet to be implemented monitors relative to a measured productivity via use of only the existing monitors; and
creating a multi-monitor recommendation based, at least in part, upon the expected productivity gain of a user, wherein the multi-monitor recommendation comprises a suggested number of additional monitors, and wherein the multi-monitor recommendation comprises information associated with a suggestion to implement the adopted arrangement of the plurality of monitors that are configured to display one or more windows associated with the window information.
14. The method of claim 13 , further comprising removing at least one record from the collected window information in response to the record being associated with an application that has been closed.
15. The method of claim 13 , further comprising removing at least one record from the collected window information in response to the record being associated with an application that has not received at least one of a keyboard or mouse input for a specified amount of time.
16. The method of claim 13 , further comprising using the collected window information to determine a number of background windows that overlap a foreground window, and wherein the multi-monitor recommendation is created, at least in part, based upon the number of background windows.
17. The method of claim 13 , further comprising using the collected window information to determine a number of instances of background and foreground window swapping within a specified time duration, and wherein the multi-monitor recommendation is created, at least in part, based upon the number of instances of background and foreground window swapping.
18. The method of claim 13 , further comprising using the collected window information to determine an amount of overlap between a background window and a foreground window, and wherein the multi-monitor recommendation is created, at least in part, based upon the amount of overlap.
19. The method of claim 13 , further comprising using the collected window information to identify at least one edge of a current display that is insufficient to render an entire background or foreground window, and wherein the multi-monitor recommendation is created, at least in part, based upon the identified edge.
20. The method of claim 13 , further comprising comparing the collected window information against one or more recommendation thresholds set based upon historical recommendations.