Dynamic Screen Timeout and Auto-Scrolling for Mobile Reading
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Solution Overview
Problem
Portable electronic devices with touch-sensitive displays require frequent user interactions for scrolling and managing content, which disrupts the reading experience and can lead to battery inefficiency due to automatic screen timeouts and notifications.
Innovation Solution
A method and system that use machine learning regression models to predict reading parameters such as complete screen reading time, scroll distance, and data reading time, enabling automated control of operations like dynamic screen timeout, auto-scrolling, and notification management based on user behavior, reducing the need for physical interactions and optimizing battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If automatic screen timeout is implemented to save battery, then energy consumption is reduced, but reading experience deteriorates due to frequent screen interruptions
Solution Approach 1:
The system predicts the user's reading duration in advance using machine learning models that analyze reading parameters such as scrolling frequency, reading speed, and content type. Based on this prediction, the screen timeout is proactively adjusted before the reading session ends, ensuring the screen remains active throughout the predicted reading period while saving battery when not in use.
Solution Approach 2:
The screen timeout setting is transformed from a static fixed value to a dynamic parameter that automatically adjusts based on real-time detection of reading behavior. The system continuously monitors scrolling patterns and reading parameters, then dynamically extends or reduces the timeout period to match the user's actual reading duration, optimizing both battery life and reading experience.
2Ease of operation
If manual scrolling is used to navigate content, then user control over reading pace is maintained, but reading experience deteriorates due to frequent touch interactions and interruptions
Solution Approach 1:
The system performs automatic scrolling without requiring user intervention. Machine learning models predict the optimal scroll timing and distance based on detected reading parameters such as current scroll position, scrolling speed, and content density. The display automatically advances content at predicted intervals, allowing the reading process to serve itself without repeated manual touches.
Solution Approach 2:
The system continuously monitors user scrolling behavior and uses this feedback to refine automatic scrolling predictions. By analyzing the relationship between scroll distance, scrolling frequency, and reading pace, the system adjusts future scroll actions to better match user preferences, maintaining reading continuity while preserving user control through adaptive behavior.
3Loss of information
If notifications are enabled to provide information, then information delivery is improved, but reading experience deteriorates due to screen interruptions and battery consumption
Solution Approach 1:
The system predicts when the user will naturally pause or finish reading based on analyzed reading parameters such as reading speed, content type, and historical pause patterns. Notifications are proactively scheduled to appear during these predicted pause moments rather than interrupting active reading, ensuring information delivery without disrupting reading flow.
Solution Approach 2:
Notification delivery is transformed from a static scheduled or immediate system to a dynamic adaptive system that adjusts timing based on real-time reading state detection. The system continuously evaluates reading parameters and dynamically delays or advances notification presentation to align with natural reading pauses, optimizing both information delivery and reading experience.
Data Source
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AI summary
A method for managing operations on data presented on a display is presented. The method includes detecting data presented on the display of the electronic device; determining reading parameters associated with the data; performing a plurality of operations based on the reading parameters, wherein the reading parameters comprises at least one of a complete screen reading time taken by a user to completely read the data presented on the display of the electronic device, a partial screen reading time taken by the user to read at least one portion of the data, a scroll distance per one scrolling action on the display, or a data reading time which is a time taken to completely read the data presented on the display.