US 12,224,069 B2
Workstation assignment
Igor S. Ramos, Round Rock, TX (US); Kimberly J. Taft, Austin, TX (US); Angelo Danducci, II, Austin, TX (US); and Devon E. Mensching, Austin, TX (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Mar. 29, 2021, as Appl. No. 17/215,156.
Prior Publication US 2022/0310262 A1, Sep. 29, 2022
Int. Cl. F24F 11/63 (2018.01); G06N 5/04 (2023.01); G06Q 10/02 (2012.01); G06Q 10/0635 (2023.01); G06Q 10/067 (2023.01); G06Q 10/105 (2023.01); G06Q 10/20 (2023.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/80 (2018.01); G16H 10/20 (2018.01)
CPC G16H 50/30 (2018.01) [F24F 11/63 (2018.01); G06N 5/04 (2013.01); G06Q 10/02 (2013.01); G06Q 10/0635 (2013.01); G06Q 10/067 (2013.01); G06Q 10/105 (2013.01); G06Q 10/20 (2013.01); G16H 50/20 (2018.01); G16H 50/80 (2018.01); G16H 10/20 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
collecting, via sensors of a workspace having one or more workstations, data about the workspace, the data including at least one member selected from a group consisting of airflow over each workstation, intensity of airflow over each workstation, and positioning of the workstation with respect to the airflow;
generating, by a processor and based on the collected data, a workstation characteristics model for the workspace, the workstation characteristics model comprising an airflow direction plan for the workspace;
receiving user data associated with users, wherein the user data is received by way of a questionnaire administered by an artificial intelligence agent;
analyzing, by the processor, the user data associated with the users to identify a respective risk level for the users;
generating a user characteristic model based on the risk levels of the users, the user characteristic model producing a ranking of respective risk levels for the users, a first user having a highest risk level of the users;
storing the collected data, the workstation characteristics model, and the user characteristic model in a network-connected storage device;
analyzing the user characteristic model and the workstation characteristic model to identify a likelihood of transmission, the analyzing including statistical and probability analysis;
assigning some of the users to a particular workstation from the one or more workstations, wherein the assigning reduces the likelihood of transmission and is based on placing a first user in a workstation in a most upstream position of the airflow direction plan in the workspace;
assigning via the user characteristic model and the workstation characteristic model a respective user pass for allowing or denying permission to all of the users to visit the workspace for a respective time period, wherein a first user pass for the first user grants permission to enter the workspace and includes the workstation assignment for the most upstream position of the airflow direction plan in the workspace, a second user pass for a second user denies permission to enter and instructs the second user to work remotely, and a third user pass for a third user is randomly selected and denies permission to enter and instructs the third user to work remotely; and
transmitting, over a computer network and in real time and as part of notifications, the user passes including the first, second, and third user passes to computers respectively associated with the users so that all of the users have immediate access to up-to-date user pass information about visiting the workspace for the time period.