Video Stream Quality Feedback for Dynamic Session Optimization
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Solution Overview
Problem
Participants in video communication sessions lack the ability to be notified of quality discrepancies between the transmitted and received video streams, and there is a lack of dynamic, automated quality optimization to address these discrepancies.
Innovation Solution
A system that identifies video parameter data for both the outgoing and incoming video streams, determines quality discrepancies, and provides notifications or performs adjustments to optimize video quality dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration settings are provided for video optimization, then users can adjust video quality parameters, but users lack awareness of actual quality discrepancies and system complexity increases
Solution Approach 1:
The system implements automatic feedback mechanisms by monitoring video stream quality parameters and providing real-time notifications to users about quality discrepancies between transmitted and received video streams, eliminating the need for manual configuration while keeping users informed
Solution Approach 2:
The system performs self-service by automatically detecting, analyzing, and optimizing video quality parameters without requiring user intervention, while still maintaining user awareness through notifications about quality issues
2Reliability
If video stream quality is maintained at high standards throughout transmission, then video quality remains consistent, but network bandwidth consumption increases
Solution Approach 1:
The system dynamically adjusts video quality parameters based on real-time network conditions and receiving device capabilities, optimizing the balance between video quality consistency and bandwidth consumption by adapting transmission parameters rather than maintaining fixed high standards
Solution Approach 2:
The system changes video stream parameters such as resolution, frame rate, and compression level based on detected quality discrepancies and network conditions, allowing flexibility in maintaining acceptable quality while reducing bandwidth consumption when appropriate
3Reliability
If automated quality optimization is implemented, then video quality improves dynamically, but system complexity increases
Solution Approach 1:
The system introduces an intermediary quality analysis component that automatically monitors video streams, compares transmitted and received quality parameters, and coordinates optimization actions, managing system complexity through a dedicated mediation layer
Data Source
AI summary
Methods and systems provide dynamic adjustments for video optimization in a communication session. In one embodiment, the system receives, at a server, an outgoing video stream from a transmitting device to a receiving device; identifies a first set of video parameter data corresponding to the quality of the outgoing video stream; receives, from the receiving device, a second set of video parameter data corresponding to the quality of the video stream; determines one or more quality discrepancies between the first set of video parameter data and the second set of video parameter data; and provides notification of at least a subset of the quality discrepancies to one or both of the transmitting device and the receiving device.