Cooktop Audio Detection for Accurate Cooking Event Response
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Solution Overview
Problem
Existing cooktop systems face challenges in accurately detecting cooking events due to false positives from motion sensors and temperature sensors, leading to issues like overcooking, splattering, and potential fires from inattentiveness.
Innovation Solution
A method and system using acoustic sensors to collect and compare audio signals at a cooktop against a database of cooking event sounds to identify specific cooking events, allowing for intelligent responses such as adjusting heat or alerting the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If motion sensors are used to detect cooking events, then detection capability is provided, but false positives occur due to human motion or rising steam
Solution Approach 1:
The patent replaces motion sensors (mechanical detection system) with acoustic sensors that detect cooking events through sound waves. The acoustic sensor captures audio signals from cooking events like boiling, sizzling, and frying, converting them into electrical signals for processing. This substitution eliminates false positives caused by human motion or steam while maintaining reliable detection of actual cooking events through acoustic characteristics.
2Measurement precision
If temperature sensors are used to detect cooking events, then temperature monitoring is provided, but accuracy and granularity are insufficient in generally heated environments
Solution Approach 1:
The patent substitutes temperature sensors with acoustic sensors for cooking event detection. Instead of measuring temperature changes that are ambiguous in generally heated environments, the system listens for distinctive acoustic signatures of cooking events. This provides superior measurement precision and reliability by detecting the unique sound patterns of boiling, sizzling, and frying events regardless of ambient temperature conditions.
Solution Approach 2:
The patent applies the principle of detecting changes in acoustic characteristics (analogous to color changes) to identify cooking events. The system analyzes changes in audio signal properties such as frequency, amplitude, and temporal patterns to distinguish different cooking events. This enables precise detection of cooking event transitions based on acoustic feature changes rather than temperature changes.
3Reliability
If acoustic sensors are used to detect cooking events, then detection accuracy is improved, but device complexity increases due to audio signal processing requirements
Solution Approach 1:
The patent segments the audio signal processing into distinct functional modules: an acoustic sensor captures raw audio, a processor analyzes acoustic characteristics (frequency, amplitude, temporal patterns), and a control system executes appropriate responses. This segmentation manages device complexity by organizing the processing pipeline into manageable, specialized components that can be optimized independently while maintaining high detection reliability.
Solution Approach 2:
The patent manages complexity by focusing analysis on specific acoustic parameters (frequency, amplitude, temporal characteristics) rather than processing the entire audio signal spectrum. By transforming the audio signal into these key parameters and comparing them against known cooking event signatures, the system achieves reliable detection with controlled processing complexity.
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
Enhances cooking event detection accuracy by distinguishing between different cooking sounds, reducing the risk of overcooking and fires, and providing a more attentive cooking experience.
Implementation Method 1
receiving, from one or more acoustic sensors positioned at a cooktop of the cooktop appliance, an audio signal
Data Source
AI summary
Cooktop appliances and methods of operation for intelligent response to cooktop audio are provided. One example cooktop appliance includes microphones for capturing an audio signal at the cooktop. A controller can compare the audio signal to a plurality of cooking event sounds representative of different cooking events. If the audio signal is matched to one of the cooking event sounds, operations responsive to the particular identified cooking event can be performed.