US 11,889,149 B2
Intelligent mitigation of concentration conflicts
Hernan A. Cunico, Holly Springs, NC (US); Sarbajit K. Rakshit, Kolkata (IN); Jonathan Dunne, Dungarvan (IE); and Martin G. Keen, Cary, NC (US)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Sep. 11, 2018, as Appl. No. 16/128,497.
Prior Publication US 2020/0084510 A1, Mar. 12, 2020
Int. Cl. H04N 21/442 (2011.01); G06N 5/022 (2023.01); H04W 4/38 (2018.01); H04N 21/466 (2011.01); G06F 17/10 (2006.01); G06N 20/00 (2019.01); H04L 67/1396 (2022.01)
CPC H04N 21/44218 (2013.01) [G06F 17/10 (2013.01); G06N 5/022 (2013.01); G06N 20/00 (2019.01); H04L 67/1396 (2022.05); H04N 21/4667 (2013.01); H04W 4/38 (2018.02)] 20 Claims
OG exemplary drawing
 
1. A method for intelligent mitigation of concentration conflicts by a processor, comprising:
identifying, by a machine learning analysis using a plurality of Internet of Things (IOT) computing devices, one or more primary activities currently being performed by a user according to detection of a physical level of activity of the user in conjunction with detection of audiovisual and spatial characteristics of a focus area of the user, wherein the one or more primary activities are unknown prior to the identifying and are categorized based on detected behavior of the user, and a level of certainty in identifying the one or more primary activities is associated with a number of the plurality of IoT devices performing the identifying;
determining, from one or more data sources, a concentration level of the user required for the one or more primary activities;
determining a distraction level indicating a possible impact to the concentration level caused by one or more secondary objects identified by the machine learning analysis; and
performing one or more actions to mitigate the possible impact to the concentration level.