Smart Device Wake-Up Using Multi-Frequency Tone Detection

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Solution Overview

Problem

Existing wake up technologies for smart devices face challenges in achieving accurate and low-power consumption operations, with methods like sound-activated lights causing false awakenings and complex AI voice wake up technologies increasing power consumption.

Innovation Solution

A method using multi-frequency tones for wake up information, determined by frame energy and feature frequency analysis, to accurately awaken smart devices with reduced processing complexity and energy consumption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by stationary object

If simple sound-activated wake up technology is used, then power consumption is reduced, but false waking up occurs frequently

Engineering Contradiction:
Improvepower consumptionVSAvoidfalse waking up ratio
Core Design Contradiction:
Use of energy by stationary objectVSReliability

Solution Approach 1:

The wake-up detection process is segmented into multiple stages: initial sound trigger detection, followed by multi-frequency tone pattern recognition, and finally frame energy information verification. This segmentation allows the device to maintain low power consumption during idle states while ensuring reliable wake-up activation through progressive verification steps that prevent false triggering.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system performs preliminary actions by pre-configuring multi-frequency tone patterns and frame energy thresholds before actual wake-up detection. The device prepares detection parameters and frequency analysis templates in advance, enabling rapid and accurate wake-up recognition when activated, while maintaining standby mode with minimal power consumption during normal operation.

Inventive Principle:
Principle #10Preliminary action

2Measurement precision

If complex AI voice wake up technology is used, then wake up accuracy is improved, but power consumption increases

Engineering Contradiction:
Improvewake up recognition accuracyVSAvoidpower consumption
Core Design Contradiction:
Measurement precisionVSUse of energy by stationary object

Solution Approach 1:

The invention extracts only the essential frequency characteristics and frame energy information from complex voice signals, eliminating the need for full AI voice recognition processing. By focusing specifically on multi-frequency tone patterns and energy thresholds, the system achieves sufficient wake-up accuracy without the high computational overhead and power consumption of complete AI voice processing.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The system uses simple frequency analysis and energy detection algorithms instead of complex AI models, employing computationally lightweight methods that consume minimal power. These simplified detection mechanisms provide adequate wake-up recognition accuracy for the specific application scenario, avoiding the energy-intensive processing of full AI voice recognition systems.

Inventive Principle:
Principle #27Cheap short-living objects (Disposable)

3Adaptability or versatility

If complex AI voice recognition is used, then wake up functionality is enhanced, but processing complexity increases

Engineering Contradiction:
Improvewake up functionalityVSAvoidprocessing complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The invention replaces complex AI software-based voice recognition with a more straightforward signal processing approach using frequency domain analysis and energy detection. By substituting mechanical/signal processing methods for complex computational AI systems, the device achieves wake-up functionality with reduced processing complexity and lower computational resource requirements.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Ensures accurate wake up while minimizing power consumption and processing complexity, applicable to various smart devices and scenarios.

Implementation Method 1

performs a frequency domain transformation on each frame of data of each single-frequency tone, so as to obtain frame energy information of each single-frequency tone

Methodology Applied
Scientific EffectFrequency domain transformation:

Data Source

PatentEP3929723B1Method and apparatus for waking up smart device, smart device and medium
Publication Date: 2026.01.07 BEIJING XIAOMI MOBILE SOFTWARE CO LTD
  • EP3929723B1 patent drawingFigure 1~2
  • EP3929723B1 patent drawingFigure 3~4
  • EP3929723B1 patent drawingFigure 5

AI summary

A method for waking up a smart device includes receiving (S110, S210, S510, S610, S710, S810, S910) sound information; determining (S120, S720, S830, S920) whether the sound information includes a multi-frequency tone; and when the sound information includes the multi-frequency tone, waking (S130, S530) up a preset function of the smart device based on the multi-frequency tone. A device for waking up a smart device as well as a smart device incorporating the device includes processing elements for performing the method. A non-transitory computer-readable storage medium stores computer instructions to cause processing elements to perform the method for waking up a smart device.