Smart Device Scene Recognition for Automatic Audio Adjustment
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Solution Overview
Problem
Smart devices lack dynamic adjustment capabilities based on environment scenes, requiring manual user intervention for optimal performance, leading to suboptimal user experience.
Innovation Solution
An environment scene recognition and decision-making system for smart devices that includes an acquisition module, data processing module, environment scene recognition module, and decision-making module to automatically adjust audio configuration parameters based on recognized environment scenes using finite state machine or classification network models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustment of audio parameters is required for different environment scenes, then device complexity is reduced, but adaptability to different scenes deteriorates
Solution Approach 1:
The system performs self-adjustment by automatically detecting environment scenes through sensor data (microphone, accelerometer, gyroscope) and independently modifying audio parameters without user intervention. The control module autonomously selects and applies appropriate audio configurations based on scene recognition, enabling the device to serve itself rather than requiring manual user adjustment.
Solution Approach 2:
The system dynamically changes audio parameters such as equalization settings, volume, and noise reduction levels based on detected environment scenes. Different parameter sets are applied for different scenes (e.g., music playing vs. voice communication), allowing the device to adapt its audio characteristics to match the current environmental context automatically.
2Ease of operation
If default parameters are used for all scenes, then device complexity is minimized, but user experience deteriorates due to suboptimal audio performance
Solution Approach 1:
The system transitions from static default parameters to dynamic parameter adjustment based on real-time scene detection. Audio parameters are continuously adapted according to the detected environment (indoor, outdoor, noisy, quiet), allowing the device to optimize performance for each specific scene rather than relying on fixed defaults that work poorly across diverse contexts.
Solution Approach 2:
The system incorporates feedback loops where sensor data from the environment is continuously monitored, scene recognition is performed, and audio parameters are adjusted accordingly. This closed-loop control ensures that the audio system responds to environmental changes and maintains optimal performance based on real-time conditions rather than relying on predetermined defaults.
3Adaptability or versatility
If automatic scene recognition is implemented, then adaptability to different scenes is improved, but device complexity increases
Solution Approach 1:
The system uses multi-functional sensor integration where the microphone, accelerometer, and gyroscope serve multiple purposes: environment scene detection, audio quality monitoring, and motion recognition. This universal approach allows a single sensor array to support various audio adjustment functions without requiring separate dedicated systems for each function, thereby reducing overall complexity while maintaining high adaptability.
Data Source
AI summary
Provided is an environment scene recognition and decision-making system and method based on a smart device. The system includes: an acquisition module disposed in the smart device to acquire environment data; a data processing module connected to the acquisition module to process the environment data to obtain environment scene features; an environment scene recognition module connected to the data processing module to recognize the environment scene features to obtain corresponding environment scenes; and a decision-making module connected to the environment scene recognition module to call a preset configuration strategy according to the environment scenes to automatically adjust audio configuration parameters of the smart device. Through the above methods, different environment scene may be recognized and the corresponding audio configuration parameters of the smart device may be adapted in different environment scenes, which may effectively improve the user experience.