Video Audio Analytics for Device Malfunction Diagnosis
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Solution Overview
Problem
Users face challenges in accurately reporting device issues, leading to incorrect diagnoses due to unfamiliarity with standard terminology and overlooked details, which hinders quick repair and increases costs.
Innovation Solution
A computer-implemented method and system that captures video and audio of a malfunctioning device, performs analytics to detect anomalies, and generates a confidence score for accurate diagnosis, facilitating correct reporting and identification of specific causes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users report device issues using their own terminology, then the reporting process is easier and faster, but the accuracy of the diagnosis deteriorates due to incorrect or non-standard terminology
Solution Approach 1:
The system introduces an intermediary component - the video/audio capture and analysis system - that bridges the gap between user-reported issues and accurate diagnosis. This intermediary captures visual and audio evidence of the device malfunction, providing objective data that translates user observations into accurate diagnostic information without requiring users to master technical terminology.
Solution Approach 2:
The patent replaces the manual description process with an automated video/audio capture and analysis system. Instead of relying on users to verbally or written describe the issue using potentially incorrect terminology, the system uses computer vision and audio processing to automatically detect and report the actual malfunction, substituting human description with machine analysis.
2Loss of information
If users provide detailed narrations of device issues, then more diagnostic information is available, but the time required for reporting increases
Solution Approach 1:
The system performs preliminary capture and analysis of video and audio evidence automatically when the device reports a malfunction. This preliminary action occurs before the diagnosis process begins, ensuring that all relevant visual and audio information is already captured and processed, eliminating the need for users to spend time providing detailed narrations.
Solution Approach 2:
The device performs self-diagnosis by automatically capturing and analyzing its own malfunction through video and audio sensors. The system serves itself by generating diagnostic reports without requiring user intervention for detailed description, thereby reducing reporting time while maintaining complete diagnostic information.
3Measurement precision
If automated video and audio analytics are performed, then diagnosis accuracy is improved, but the system complexity increases
Solution Approach 1:
The system uses universal video and audio capture capabilities that can detect multiple types of malfunctions across different device types. The same video/audio sensors and analysis algorithms serve multiple diagnostic purposes, reducing the need for specialized complex subsystems for each specific malfunction type.
Solution Approach 2:
The system changes the parameters of data collection from traditional user input (text, voice commands) to visual and audio evidence capture. By transforming the type of data collected into video and audio streams that can be automatically analyzed, the system achieves high diagnosis accuracy while managing complexity through standardized processing pipelines.
Data Source
AI summary
A method, system and computer program product for diagnosing a malfunctioning or misused electronic device is disclosed. The method includes performing analytics on at least one of video and audio to automatically detect at least one anomaly exhibited by the electronic device or exhibited in relation to user interaction with the electronic device, the at least one anomaly being distinguishable from other non-present anomalies detectable by a computer system that carries out the performing of the analytics.