Context-Aware Screenshot Capture Reducing File Size
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Solution Overview
Problem
Current screenshot capture methods often capture irrelevant information, leading to increased file size, network throughput, and costs, as well as the need for users to take multiple screenshots and manually crop them, due to the inability to intelligently understand user needs and capture only relevant content.
Innovation Solution
A method that collects context data from user interactions, IoT, and social media to identify relevant information on a display screen, captures only the relevant parts, and appends additional relevant information from other sources, while optionally performing auto zoom-out to fit the content into a single screenshot.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional screenshot capture methods are used to capture the entire display screen, then all visible information is captured, but irrelevant information is included leading to increased file size and storage costs
Solution Approach 1:
The patent extracts and captures only the relevant portion of the display screen that contains the requested information, rather than capturing the entire screen. The system identifies the specific application window or region containing the relevant data and captures only that portion, eliminating irrelevant content and reducing file size while maintaining information completeness.
2Loss of information
If multiple screenshots are captured to ensure all relevant information is included, then information completeness improves, but user effort and time increase
Solution Approach 1:
The system performs self-service by automatically identifying and capturing the relevant information portion without requiring user intervention to take multiple screenshots or manually crop images. The patent uses context data and application analysis to autonomously determine what information is relevant and captures it in a single operation, eliminating the need for users to repeatedly capture and assemble multiple screenshots.
3Measurement precision
If context data collection and analysis are performed to identify relevant information, then screenshot relevance improves, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional system that simultaneously performs context data collection, application window identification, relevant information detection, and screenshot capture. The system integrates multiple functions into a unified process that analyzes context data (such as user activity, application state, and information relevance) to automatically determine what to capture, achieving high accuracy without proportionally increasing complexity through integrated design.
4Quantity of substance
If only the active application window is captured, then file size is reduced, but additional relevant information from other windows is missed
Solution Approach 1:
The patent applies local quality by capturing different portions of the display screen based on their relevance to the requested information. Rather than uniformly capturing the entire screen or only the active window, the system identifies specific regions (such as the active application window and additional relevant windows) and captures only those localized areas containing relevant information, optimizing both file size and information completeness.
Data Source
AI summary
Generating a composite screenshot including contextually relevant screenshots and displayed information. The composite screenshot includes one or more screenshots captured from a display screen of a requesting user. Contextual relevance is determined according to collected user communications data such as IoT interactions, social media posts, and chat session transcripts.