| CPC G06Q 10/1095 (2013.01) [G06Q 30/0283 (2013.01)] | 20 Claims |
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1. A system, comprising:
one or more processors; and
memory coupled to the one or more processors, the memory including one or more modules that are executable by the one or more processors to perform operations to infer a meeting expense for a proposed meeting, calculate an actual meeting expense for an actual meeting, and recommend a change in meeting format, the operations to infer a meeting expense comprising:
intercepting, from a scheduler device, a meeting request for a proposed meeting of in-person meeting attendees at a first meeting location, wherein the first meeting location is a geolocation;
inferring a meeting expense for the proposed meeting based at least in part on the meeting request, wherein an inferring of the meeting expense includes:
determining time lost due to travel of the in-person meeting attendees to the first meeting location that contributes to lost work time (LWT) values of the in-person meeting attendees, the determining the time lost being performed at least using one or more trained machine-learning algorithms to infer a start location of each individual in-person meeting attendee, the machine-learning algorithms having been trained on historical calendar data of the each individual in-person meeting attendee and environmental factors that historically impact meeting at the first meeting location; and
in response to the inferred meeting expense being greater than a predetermined meeting expense threshold, suspending the meeting request, and
the operations to calculate an actual meeting expense for an actual meeting comprising:
for in-person meeting attendees attending the actual meeting at a meeting site:
interacting with sensors located at the meeting site to capture sensor data that includes video from the in-person meeting attendees during the meeting;
analyzing the sensor data, including comparing the sensor data to biometric profile data of the in-person meeting attendees, to identify in-person meeting attendees based on the comparison; and
determining an actual expense of the identified in-person meeting attendees based on their respective LWT values;
for virtual meeting attendees attending the meeting virtually via a virtual meeting platform:
interacting with the virtual meeting platform to capture attendance data that comprises Internet Protocol (IP) addresses associated with the virtual meeting attendees;
identifying the virtual meeting attendees from the IP addresses in the attendance data;
determining, based on historical profile data of the virtual meeting attendees identified in the attendance data, an expense of setting up the virtual meeting at a second meeting location for the virtual meeting attendees that contributes to LWT values of the virtual meeting attendees; and
determining an actual expense of the virtual meeting attendees based on their respective LWT values; and
calculating the actual meeting expense by aggregating the actual expense of the in-person meeting attendees and the actual expense of the virtual meeting attendees; and
the operations to recommend a change in meeting format comprising:
sensing virtual meeting connectivity of the virtual meeting attendees to the actual meeting;
receiving telemetry data that indicates Quality of Service (QOS) of the virtual meeting connectivity; and
recommending a change in meeting format from a virtual meeting to an in-person meeting for at least a subset of the virtual meeting attendees based on the telemetry data indicating that virtual meeting connectivity for the at least a subset of the virtual meeting attendees is below a predetermined QoS threshold.
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