Virtual Conference Endpoint Configuration Using Device Diagnostics
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Solution Overview
Problem
Existing video conferencing systems face challenges in efficiently configuring multiple disparate devices from different manufacturers to provide optimal audio and video experiences, especially in dynamic and changing environments, requiring time-intensive manual adjustments.
Innovation Solution
A system utilizing artificial intelligence and machine learning to dynamically configure endpoint devices in real-time, determining optimal settings based on device diagnostics, room conditions, and user interactions, enabling adaptive switching and integration of new devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual configuration methods are used for multiple disparate endpoint devices, then configuration precision can be achieved, but configuration time increases significantly
Solution Approach 1:
The system enables endpoint devices to automatically self-configure by performing diagnostic operations, determining optimal settings, and adjusting their own configurations without manual intervention. The processing engine analyzes device diagnostics and autonomously determines optimal configurations for each endpoint device, allowing the system to serve itself rather than requiring external manual configuration.
Solution Approach 2:
The system performs diagnostic operations and determines optimal settings configurations in advance before the video conferencing session begins. By pre-configuring devices based on their diagnostic outputs and room conditions, the system eliminates the need for time-consuming manual adjustments during actual use.
2Adaptability or versatility
If devices from multiple manufacturers are integrated, then device versatility increases, but configuration complexity increases
Solution Approach 1:
The processing engine serves as a universal configuration system that can handle multiple types of endpoint devices from different manufacturers. It performs diagnostic operations and determines optimal settings for various device types (cameras, microphones, speakers, displays) through a single unified interface, making the system versatile without requiring separate configuration procedures for each device type.
Solution Approach 2:
The processing engine acts as an intermediary between disparate endpoint devices and the video conferencing system. It standardizes communication by receiving diagnostic outputs from different device manufacturers and translating them into unified optimal settings configurations, thereby simplifying the integration of heterogeneous devices.
3Adaptability or versatility
If dynamic reconfiguration is performed when devices are added or removed, then system adaptability improves, but processing time increases
Solution Approach 1:
The system dynamically adjusts endpoint device configurations in response to changing conditions such as devices being added or removed from the room. The processing engine continuously monitors device diagnostics and automatically reconfigures the system without requiring manual intervention, enabling the configuration to adapt dynamically to environmental changes.
Solution Approach 2:
The system uses feedback from diagnostic operations performed on endpoint devices to automatically determine and apply optimal settings configurations. When devices are added or removed, the processing engine receives feedback through diagnostic outputs and automatically adjusts configurations accordingly, enabling rapid adaptation without manual reconfiguration.
Data Source
AI summary
An addition of a new endpoint device to a virtual conference that includes one or more current endpoint devices is identified. Diagnostic data is received from the new endpoint device responsive to a diagnostic operation initiated in response to identifying the addition of the new endpoint device. A setting configuration for one of the one or more current endpoint devices is determined based on the diagnostic data and on current configuration settings associated with at least some of the one or more current endpoint devices. The one of the one or more current endpoint devices is caused to be configured based on the setting configuration.