Video Feed Dynamics for Conference Call Resource Efficiency
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Solution Overview
Problem
Traditional conferencing systems are one-dimensional, limiting users to either maintaining or ending a conference call without options to adjust the audio or video feed, leading to inefficiencies such as unnecessary resource usage and irrelevant information exchange during breaks or disruptions.
Innovation Solution
A computer-implemented method and system that monitors and modifies video-based communications during a conference call by identifying unwanted image or audio components and actively removing them, allowing for dynamic adjustments based on contextual activity and user profiles, such as pausing video during a coffee break or removing background noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users maintain video feed on during conference calls, then communication continuity is ensured, but resource usage increases and irrelevant information is exchanged during breaks
Solution Approach 1:
The system dynamically adjusts the video feed state based on detected contextual activities. Instead of maintaining a static on/off state, the video feed transitions between active and paused states according to real-time analysis of user behavior patterns, such as detecting when a user has left their workstation or when contextual indicators suggest a break period.
Solution Approach 2:
The system implements feedback loops where contextual sensors continuously monitor environmental and user state data, analyze this information against defined criteria, and automatically adjust video feed transmission accordingly. This closed-loop control ensures communication continuity when needed while pausing during irrelevant periods.
2Reliability
If users maintain video feed on during conference calls, then communication readiness is maintained, but irrelevant information is exchanged during disruptions
Solution Approach 1:
The video feed transmission dynamically responds to contextual changes by transitioning between active and paused states. The system monitors multiple contextual indicators simultaneously and adjusts feed transmission in real-time, ensuring readiness when appropriate while filtering out irrelevant information during disruptions or breaks.
3Ease of operation
If conferencing systems provide simple on/off feed control, then ease of operation is maintained, but adaptability to different contextual situations is limited
Solution Approach 1:
The system performs automatic contextual analysis and video feed management without requiring direct user intervention. Users define contextual criteria once, and the system autonomously monitors contextual indicators, analyzes detected activities against these criteria, and adjusts video feed transmission accordingly, providing both simplicity and adaptability.
Solution Approach 2:
The system transforms static on/off control into a dynamic, context-responsive mechanism. Multiple contextual indicators are monitored simultaneously, and the video feed state transitions dynamically based on real-time analysis, enabling the system to adapt to various situations while maintaining operational simplicity for users.
4Speed
If video feed remains active during breaks, then quick resumption is enabled, but productivity is reduced due to unnecessary resource usage
Solution Approach 1:
The system dynamically determines when to pause and when to maintain video feed based on contextual analysis. By detecting break patterns and predicting resumption needs, the system optimizes the balance between quick resumption capability and resource efficiency, pausing during confirmed breaks while maintaining readiness when resumption is anticipated.
Data Source
AI summary
A computer-implemented method for modifying video-based communications produced during a conference call, is disclosed. The computer-implemented method can include monitoring a plurality of images transmitted via a video feed of a device connected to the conference call. The computer-implemented method can include identifying a first unwanted image component transmitted via the video feed. The computer-implemented method can include actively modifying the video feed by removing the first unwanted image component from the video feed.