Wearable Device Sound-Based Operation Mode Adaptation
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Solution Overview
Problem
Wearable devices lack effective methods to automatically adjust their operation modes based on surrounding sounds and user inputs, leading to inefficient power consumption and noise management.
Innovation Solution
A wearable device that uses AI technology to receive surrounding sounds, determine operation modes such as conversation, announcement, or power control modes, and perform corresponding preset operations, including noise cancellation, volume adjustment, and power management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the wearable device continuously monitors surrounding sounds to determine operation modes, then the adaptability and user experience are improved, but the power consumption increases
Solution Approach 1:
The wearable device automatically determines operation modes by analyzing surrounding sounds without requiring manual user input. The processor autonomously identifies voice signatures, announcements, and conversation patterns, then switches modes accordingly, enabling the device to serve itself in adapting to user needs while conserving energy.
Solution Approach 2:
Instead of continuous monitoring, the device employs periodic sound analysis to determine operation modes. The processor analyzes surrounding sounds at intervals, identifying key acoustic patterns (voice signatures, announcements) only when needed, thereby reducing overall power consumption while maintaining effective adaptability.
2Object-affected harmful factors
If the wearable device implements multiple operation modes with noise cancellation and voice amplification, then the noise management and user experience are improved, but the device complexity increases
Solution Approach 1:
The wearable device integrates multiple functions including noise cancellation, voice amplification, and operation mode determination within a single unified system. The processor handles diverse acoustic scenarios (conversations, announcements, quiet environments) using a common framework, reducing overall device complexity despite the multiple capabilities.
Solution Approach 2:
The device manages different acoustic environments by changing operational parameters rather than adding separate hardware systems. The processor adjusts noise cancellation intensity, voice amplification levels, and audio output parameters based on the determined operation mode, achieving effective noise management through parameter optimization.
3Measurement precision
If the wearable device uses AI technology to analyze voice signatures and determine operation modes, then the measurement precision and automatic operation are improved, but the processing time and energy consumption increase
Solution Approach 1:
The device performs preliminary analysis of acoustic patterns to identify potential operation modes before full processing is required. Voice signatures and announcement patterns are detected and classified in advance, allowing the processor to quickly switch modes without extensive real-time computation, thereby reducing processing time while maintaining detection accuracy.
Data Source
AI summary
A wearable device and a method of operating the wearable device are provided. The wearable device includes: a memory configured to store one or more instructions; and at least one processor configured to execute the one or more instructions to: receive, as an input, a surrounding sound of surroundings of the wearable device: determine an operation mode from among a plurality of operation modes, based on the received input; and perform a preset operation according to the determined operation mode.