Display Input Channel Switching via Camera-Based Fail Detection
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Solution Overview
Problem
Existing conferencing software systems fail to detect certain issues with shared device displays that render them incapable of functional operation for video conferencing, such as incorrect input channels, malfunctioning lighting panels, or unplugging, which conventional client applications cannot reliably identify.
Innovation Solution
Perform illumination testing by outputting a test pattern to the display and capturing an image with a camera, comparing it to a reference image to determine the display's operational state, and iteratively adjusting input channels to resolve fail states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional client applications are used to monitor display status, then the system is simple to operate, but the detection capability is insufficient and cannot reliably identify display failures
Solution Approach 1:
The patent introduces an intermediary illumination testing system that includes a camera, image processing logic, and automated testing software. This intermediary system acts as a mediator between the display and the monitoring system, capturing images of the display output and analyzing them to detect failures. The intermediary handles the complex detection tasks, allowing the overall system to maintain simplicity while achieving high detection precision.
Solution Approach 2:
The patent replaces manual or conventional software-based display monitoring with an automated optical inspection system. Instead of using software to query display status, the system uses a camera to capture visual output and image processing algorithms to analyze display functionality. This substitution of mechanical/optical methods for software-based monitoring enables reliable detection of physical display failures that software cannot detect.
2Measurement precision
If illumination testing with image capture and comparison is performed, then display issue detection accuracy is improved, but the testing process time increases
Solution Approach 1:
The patent implements preliminary action by pre-capturing reference images of the display under known good conditions and storing them for comparison. During actual testing, the system only needs to capture a current test image and compare it against the pre-prepared reference images. This eliminates the need to perform complex analysis from scratch during testing, significantly reducing testing time while maintaining high accuracy through systematic image comparison.
Solution Approach 2:
The system implements feedback by automatically comparing captured test images against reference images and using the comparison results to determine display status. The feedback loop includes automated image capture, comparison against stored references, failure detection, and triggering of remediation actions. This automated feedback mechanism enables rapid testing cycles with high accuracy, as the system learns from each comparison and can quickly identify deviations from expected display behavior.
3Reliability
If the system automatically changes input channels to resolve fail states, then operational reliability is improved, but the automation complexity increases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically detect display failures and perform remediation actions without human intervention. When a display failure is detected through image analysis, the system automatically attempts to resolve the issue by changing input channels, adjusting display settings, or triggering other predefined remediation sequences. This self-service capability maintains high operational reliability while managing automation complexity through standardized, pre-programmed response protocols.
Solution Approach 2:
The system applies parameter changes as a remediation strategy, automatically modifying display parameters such as input channel selection, brightness levels, or refresh rates when failures are detected. By systematically changing these parameters and monitoring the results, the system can resolve many display issues automatically. This approach balances reliability improvement with manageable automation complexity, as parameter changes are straightforward, reversible operations that can be automated without requiring complex decision-making logic.
Data Source
AI summary
Illumination testing is performed to passively check the health of a display of a shared device within a physical space, such as a conference room. A test pattern is output to the display within the physical space. Using a camera within the physical space, a test image of the physical space is captured while the test pattern is output to the display. A determination is then made as to whether the display is in a fail state by comparing the test image against a reference image depicting an expected illumination of the physical space according to the test pattern. Where the device is determined to be in a fail state, a notification indicating the fail state is transmitted to an administrator device to alert an administrator associated therewith of the fail state.