User Experience Event Processing for Mobile Storage Systems
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Solution Overview
Problem
Current storage system design for mobile platforms focuses primarily on inner measurements, neglecting user experience (UX) and often results in inaccurate and subjective assessments of storage performance, particularly in terms of time lags on graphical user interfaces (GUI), which can be attributed to either storage devices or host applications.
Innovation Solution
A method and system for user experience event processing and analysis, utilizing computer vision and image processing algorithms to automatically detect and correlate user interface events with storage system activity, generating reports and graphs to analyze the impact of storage systems on mobile device performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual user experience measurements are conducted, then subjectivity and inaccuracy are reduced, but measurement time and labor requirements increase
Solution Approach 1:
The system enables automated self-measurement of user experience metrics by having the mobile device itself record GUI videos and provide activity data without requiring external manual observation. The device captures its own performance characteristics through integrated sensors and software tools.
Solution Approach 2:
The patent replaces manual mechanical observation with automated electronic detection systems. Computer vision algorithms automatically analyze recorded GUI videos to detect user experience events, substituting human visual inspection with automated image processing and pattern recognition.
2Reliability
If storage system design focuses on inner measurements, then storage performance is optimized, but user experience impact is overlooked
Solution Approach 1:
The patent adds a new dimension of analysis by correlating storage activity data with visual GUI recordings. Instead of measuring only storage metrics internally, the system integrates external user experience observations to create a comprehensive view of storage impact on device performance.
Solution Approach 2:
The system establishes feedback loops where GUI performance observations are fed back into storage system analysis. By detecting user experience events from recorded videos and correlating them with storage activity, the system continuously refines understanding of storage impact and can drive iterative improvements.
3Extent of automation
If automated user experience detection is implemented, then measurement objectivity is improved, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by using a single recorded video of the GUI to detect multiple types of user experience events simultaneously. The same video data is analyzed to identify various event types (app launches, page transitions, etc.) and correlate them with storage activity, eliminating the need for separate detection systems for each metric.
Data Source
AI summary
A method and system for user experience event processing and analysis are provided. In one embodiment, a method is provided comprising: receiving a recorded video of a display of the host device and a reference video; comparing the recorded video with the reference video to identify differences, wherein the recorded video and the reference video are synchronized based on content rather than time; receiving data indicating activity of a storage device of the host device; correlating the differences with the data indicating activity of the storage device; and generating an analysis of the correlation. Other embodiments are possible, and each of the embodiments can be used alone or together in combination.