Dynamic Biometric Pattern Selection for Mobile Terminals
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Solution Overview
Problem
Current mobile terminals rely on single biometric recognition patterns for operations like unlocking and security authentication, leading to high power consumption and reduced battery life when multiple biometric patterns are used simultaneously.
Innovation Solution
A method for a mobile terminal to query and enable a target biometric recognition pattern based on historical usage data and specific conditions, such as gesture information or unlocking requests, to optimize power usage by selecting the most frequently and accurately used biometric pattern.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple biometric recognition patterns are enabled simultaneously, then recognition versatility is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts which biometric recognition patterns are enabled based on real-time conditions such as usage frequency, recognition accuracy, and user behavior patterns. The processor continuously monitors these parameters and selectively activates only the necessary biometric patterns, transforming the static multi-pattern system into a dynamic one that adapts to actual needs, thereby maintaining versatility while reducing unnecessary power consumption.
Solution Approach 2:
The system changes operational parameters by adjusting the enablement state of different biometric recognition patterns based on monitored performance metrics. When usage frequency and recognition accuracy indicate that certain patterns are rarely used or ineffective, the system modifies the parameter of pattern enablement to reduce the number of active patterns, thus lowering power consumption while preserving essential recognition capabilities.
2Reliability
If multiple biometric recognition patterns are enabled simultaneously, then recognition accuracy is improved, but battery life is reduced
Solution Approach 1:
The system dynamically determines which biometric patterns to enable by monitoring usage frequency and recognition accuracy in real-time. This dynamic adjustment ensures that only the most effective patterns are active, maintaining high recognition accuracy while avoiding the continuous power drain of keeping all patterns enabled, thereby extending battery life.
Solution Approach 2:
The system performs self-optimization by automatically monitoring its own performance metrics (usage frequency, recognition accuracy) and adjusting the enablement of biometric patterns accordingly. This self-service mechanism allows the system to maintain optimal recognition accuracy without manual intervention while automatically reducing power consumption to preserve battery life.
3Extent of automation
If the system queries and selects biometric patterns based on historical usage data, then operational intelligence is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-collecting and analyzing historical usage data and recognition accuracy metrics before making decisions about pattern enablement. This preliminary data gathering and analysis creates a knowledge base that simplifies subsequent decision-making, allowing the processor to quickly determine which patterns to enable based on pre-analyzed trends rather than complex real-time calculations.
Solution Approach 2:
The system implements feedback loops where usage frequency and recognition accuracy are continuously monitored and fed back to the processor. This feedback mechanism enables the system to learn from past performance and automatically adjust pattern enablement decisions, increasing operational intelligence while managing complexity through structured feedback processing rather than uncontrolled system expansion.
Data Source
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AI summary
A method for enabling a biometric recognition pattern and related products are provided, and the method includes the follows. A mapping relationship between a first condition and a target biometric recognition pattern is queried when detecting that a terminal device satisfies the first condition. The target biometric recognition pattern is one or more of at least one biometric recognition pattern with which the terminal device is operable. The target biometric recognition pattern is determined based on the mapping relationship. The target biometric recognition pattern is enabled.