External UI Change Detection via Image Analysis
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Solution Overview
Problem
Conventional electronic devices struggle to efficiently recognize changes in the user interface (UI) provided by external devices connected through input/output interfaces, requiring users to manually check for updates, which is time-consuming and limited to connected devices only, preventing universal UI updates.
Innovation Solution
An electronic apparatus with an input/output interface, memory, and processor that trains the UI of external devices by analyzing images received through the interface, identifies UI changes, and re-trains the UI information, allowing for offline detection and adaptation of UI updates without internet connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional recognition methods are used to identify external devices, then device connection is easily recognized, but UI changes by the same external device are not easily recognized
Solution Approach 1:
The system performs preliminary training to establish a baseline UI model before actual UI change detection occurs. This preliminary action creates a reference framework that enables subsequent automatic detection of UI changes without requiring complex real-time analysis mechanisms.
Solution Approach 2:
The system creates a copied representation of the UI (UI model) that can be stored and compared against current UI states. This copying approach allows the system to detect changes by comparing the current UI against the stored model, simplifying the detection process while maintaining high accuracy.
2Loss of information
If users manually check for UI updates by visiting service provider websites, then UI change information can be obtained, but considerable effort and time are required
Solution Approach 1:
The system performs self-service by automatically detecting UI changes through image analysis and model comparison without requiring user intervention. The electronic apparatus independently identifies when UI updates occur and retrieves necessary information, eliminating the need for users to manually visit websites or check for updates.
Solution Approach 2:
The system implements feedback mechanisms where the detected UI changes are continuously compared against the stored model, and update information is automatically retrieved and applied. This closed-loop feedback system ensures timely detection and application of UI updates without user involvement.
3Adaptability or versatility
If UI updates are applied only to electronic apparatuses connected via Internet, then online devices receive updates, but changes cannot be applied to all electronic apparatuses
Solution Approach 1:
The system achieves universality by implementing UI change detection and model training functionality that works offline without requiring Internet connectivity. The electronic apparatus can independently detect UI changes, train new models, and apply updates locally, making the system applicable to all devices regardless of their network status.
Solution Approach 2:
The system performs preliminary training to create a comprehensive UI model that can serve as a reference for future comparisons. This preliminary action ensures that even offline devices have the necessary baseline information to detect and adapt to UI changes, expanding the scope of devices that can receive updates.
Data Source
AI summary
An electronic apparatus and a controlling method thereof are provided. The electronic apparatus includes a processor configured to train a UI provided by an external device through an input/output interface and store information on the UI provided by the external device in a memory, based on an image being received from the external device through the input/output interface, identify whether a UI is included in the received image, based on a UI being included in the received image, compare the UI included in the received image with the UI provided by the external device stored in the memory and identify whether the UI provided by the external device is changed, and based on identification that the UI provided by the external device being changed, retrain the UI included in the received image and store information on the UI included in the received image in the memory.