Application Trial Platform Hot Update via Interface Image Analysis
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Solution Overview
Problem
The existing methods for updating applications on mobile terminals are inefficient, requiring significant time for users to download and install updates, and existing application trial platforms struggle to ensure users have the latest version without manual intervention or hardware changes.
Innovation Solution
A method that involves obtaining and analyzing interface images of running application instances to detect updates, extracting attributes, and automatically updating the application when a new version is detected, using image recognition and knowledge models to facilitate 'hot updates' without manual operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually download and install application updates, then the application version is kept up-to-date, but the user spends a large amount of time on downloading and installing
Solution Approach 1:
The system enables automatic update detection and installation by having the application trial platform autonomously check for updates, extract update information from interface images, and install updates without requiring user intervention. This self-service mechanism resolves the contradiction by eliminating manual update operations while ensuring the application remains current.
Solution Approach 2:
The system performs preliminary update checks by analyzing interface images to detect update notifications before the user would normally need to manually check for updates. By proactively identifying update availability through image recognition and attribute extraction, the system prepares for automatic update installation, thereby reducing the time users would spend on manual update processes.
2Adaptability or versatility
If application trial platforms continuously update the application version, then users can use the latest application, but the update process becomes complex and requires manual intervention
Solution Approach 1:
The system replaces manual mechanical update processes with automated image recognition and analysis. By using computer vision technology to detect update notifications in interface images and automatically extracting update information, the system eliminates the need for complex manual update operations while maintaining version flexibility. This substitution of automated visual recognition for manual processes resolves the contradiction between adaptability and complexity.
Solution Approach 2:
The system introduces an intermediary automated update detection mechanism that acts as a mediator between the application trial platform and the user. This intermediary automatically analyzes interface images, detects update notifications, and manages the update process, thereby simplifying the complexity for users while maintaining the ability to continuously update to the latest version.
3Ease of operation
If users install applications on their mobile terminals, then they can use the application functions, but they need to spend significant time downloading and installing
Solution Approach 1:
The system performs preliminary update detection by analyzing interface images to identify update notifications before the user would need to manually download and install updates. This preliminary action allows the system to automatically initiate update processes in the background, reducing the time users would otherwise spend on manual download and installation while maintaining application accessibility.
Solution Approach 2:
The application trial platform implements self-service update capabilities by automatically detecting updates through interface image analysis, extracting update information, and installing updates without requiring user intervention. This self-service mechanism resolves the contradiction by eliminating manual installation time while keeping application functions accessible to users.
Data Source
AI summary
A method for updating an application is provided. In the method, a first interface image generated during a period that a first instance of the application is running is obtained. The first instance of the application is running on an application trial platform. The application trial platform is communicatively couplable to a server of the application. A plurality of attributes associated with a control contained in the first interface image are extracted. Based on the plurality of attributes, it is determined whether the first interface image indicates that an update of the application is released by the server. In response to determining that the first interface image indicates that the update of the application is released by the server, the first instance of the application is updated on the application trial platform.