Cooking Device Doneness Recognition for Real-Time Parameter Control
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Solution Overview
Problem
Existing cooking devices lack intelligence in controlling cooking parameters, leading to frequent overcooking or undercooking due to reliance on user adjustments based on visual observations, resulting in poor cooking results and user experience.
Innovation Solution
A control method for cooking devices that employs preset doneness recognition models to monitor and adjust cooking parameters in real-time, ensuring food is cooked to the desired doneness by recognizing food images and controlling cooking duration and temperature dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If mechanical heating with fixed parameters is used, then the cooking device is simple to operate, but the cooking precision is poor leading to overcooking or undercooking
Solution Approach 1:
The patent implements a feedback mechanism where the cooking device captures images of the food during cooking, recognizes the cooking state through image analysis, and dynamically adjusts cooking parameters based on the recognized state. This closed-loop feedback system enables precise control of cooking doneness without requiring complex manual intervention from the user.
Solution Approach 2:
The cooking device performs automatic image recognition and self-adjusts cooking parameters without user intervention. The system independently monitors the cooking process, identifies when the food reaches the desired doneness state, and automatically terminates or adjusts cooking, making the device self-regulating and eliminating the need for user expertise in timing and temperature control.
2Reliability
If user manually adjusts cooking parameters based on visual observation, then the device operation is simple, but the cooking reliability is poor due to delayed intervention
Solution Approach 1:
The system continuously monitors the cooking process through image capture and real-time recognition of cooking states. This automated feedback mechanism reliably detects when the food reaches the desired doneness and immediately triggers appropriate control actions, eliminating the delays and human error associated with manual observation and adjustment.
Solution Approach 2:
The patent replaces manual visual observation and mechanical adjustment with automated optical recognition and electronic control. Image recognition algorithms automatically analyze food appearance and texture changes, substituting human sensory judgment with machine vision, thereby improving reliability and enabling true automatic control.
3Manufacturing precision
If static image recognition algorithm is used, then the implementation is simple, but the cooking control precision is insufficient leading to high failure rate
Solution Approach 1:
The patent transitions from static image recognition to dynamic multi-stage recognition. Instead of a single fixed algorithm, the system employs multiple recognition models corresponding to different cooking stages and doneness levels. The recognition process dynamically adapts to the changing cooking state, selecting appropriate models and adjusting parameters based on the current stage of cooking, thereby significantly improving recognition precision.
Solution Approach 2:
The cooking process is segmented into multiple stages with different recognition models for each stage. The system divides the complex cooking process into manageable segments, applying specialized recognition algorithms to each segment based on characteristic changes at different doneness levels. This segmentation allows for more precise control and recognition without requiring a single overly complex algorithm.
Data Source
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AI summary
A cooking device and a control method and a control system thereof are provided. According to the control method, a cooking state of a food at a preset time point in a cooking process is recognized through a preset doneness recognition model, and a manner of controlling operation of the cooking device is determined in combination with a relationship between an actual cooking duration of the food at the preset time point and a preset cooking duration. Through this implementation, a correlation between a dynamic change of the food in the cooking process and doneness of the food is established based on the dynamic change during the cooking and impact of the dynamic change on the doneness, and then the cooking device can be controlled in real time based on the cooking state in the cooking process, thereby optimizing a cooking result and improving user experience.