Intelligent identification cooking system for oven
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Solution Overview
Problem
Traditional ovens require users to manually assess various parameters such as type, size, thickness, fattiness, and temperature of steak-type food for accurate cooking, leading to potential overcooking or undercooking due to human error, especially with varying raw materials.
Innovation Solution
An intelligent identification cooking system utilizing computer vision and identification technology, combined with temperature sensing, to automatically analyze steak parameters and adjust cooking settings, comprising an image acquisition system, image analysis and processing system, and temperature measurement and monitoring system, which outputs a calibrated cooking program for precise cooking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually assess steak parameters (type, size, thickness, fattiness, temperature) to set cooking conditions, then the oven can be operated with simple controls, but the cooking precision and consistency deteriorate due to human error and subjective judgment
Solution Approach 1:
The patent replaces the manual mechanical assessment system with an automated optical detection system. A camera captures images of the steak, and image processing algorithms automatically analyze parameters such as thickness, color, and surface characteristics. This substitution eliminates human subjective judgment while maintaining simple user operation through automatic recognition and cooking parameter recommendation.
Solution Approach 2:
The system enables the oven to perform self-assessment of steak parameters through integrated imaging sensors and processing capabilities. The oven automatically detects steak characteristics, determines appropriate cooking parameters, and executes the cooking process without requiring user expertise. This self-service approach improves both operational simplicity and cooking precision simultaneously.
2Device complexity
If the oven uses fixed cooking programs without ingredient identification, then the device complexity is reduced, but the adaptability to different steak types and qualities deteriorates
Solution Approach 1:
The patent integrates multiple functions into a single cooking system: the imaging system serves both as a detection device for ingredient identification and as a control input device for determining cooking parameters. The system can handle various steak types, thicknesses, and quality levels through a unified algorithmic approach, eliminating the need for multiple specialized programs while maintaining broad adaptability.
Solution Approach 2:
The system dynamically adjusts cooking parameters based on detected steak characteristics. By analyzing image data to determine thickness, color, and surface properties, the system automatically modifies temperature, time, and heating zone parameters to suit different steak types and desired doneness levels. This parameter adaptation occurs within a single flexible program structure rather than requiring fixed separate programs for each scenario.
3Measurement precision
If computer vision and identification technology are implemented to automatically analyze steak parameters, then the measurement precision and cooking consistency are improved, but the device complexity and cost increase
Solution Approach 1:
The patent uses optical copying through camera imaging to create a digital representation of the steak's physical characteristics. This optical copy is then processed through image analysis algorithms to extract thickness, color, and surface information without requiring direct physical contact or complex sensing devices. The copying approach achieves high measurement precision while avoiding the complexity of multiple specialized sensors.
Solution Approach 2:
The imaging system serves as an intermediary between the steak and the control system. Rather than directly measuring physical parameters with complex sensors, the system captures optical information that mediates the extraction of cooking-relevant parameters through image processing. This intermediary approach simplifies the overall system architecture while maintaining measurement accuracy.
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
The system effectively identifies steak parameters, eliminating manual estimation errors and ensuring consistent, high-quality cooking results with one-button operation, reducing complexity and cost while enhancing applicability.
Implementation Method 1
the image acquisition system is mainly formed by a camera and a light source, the camera is used to collect image information
Implementation Method 2
The temperature measurement and monitoring system mainly comprises an infrared temperature sensor and a thermocouple temperature sensor, which are respectively used to measure and monitor a food surface temperature and an oven cavity temperature
Implementation Method 3
The temperature measurement and monitoring system mainly comprises an infrared temperature sensor and a thermocouple temperature sensor
Data Source
AI summary
An intelligent identification cooking system of an oven including an image acquisition system, an image analysis and processing system, and a temperature measurement and monitoring system. The image acquisition system is connected to the image analysis and processing system and an intelligent menu control system is connected to the image analysis and processing system and the temperature measurement and monitoring system respectively. Through computer vision and identification technology and temperature sensing technology, parameters such as the type, thickness, size, fattiness and temperature are identified and automatically matched and calibrated to a cooking menu. A control program is output to a control terminal and executed.