Tailored food preparation with an oven
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Solution Overview
Problem
Conventional cooking methods require manual adjustment of multiple operation parameters, making it difficult for users to consistently achieve desired food output conditions, especially for inexperienced cooks, and lack a systematic approach to incorporate user feedback for improving cooking results.
Innovation Solution
A method and system that collect user feedback during and after cooking sessions to update operation instructions dynamically, using a connected cooking apparatus with sensors and a computing system to tailor cooking sessions to user preferences by adjusting parameters such as temperature and time based on subjective feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of multiple operation parameters is required, then cooking flexibility is maintained, but ease of operation deteriorates and manufacturing precision deteriorates
Solution Approach 1:
The system automatically adjusts multiple cooking parameters (temperature, time, convection fan speed, heating element power) based on user feedback and historical data, transforming manual parameter adjustment into automated parameter optimization. This resolves the contradiction by maintaining cooking precision through systematic parameter control while improving ease of operation through automation.
Solution Approach 2:
The system collects user feedback about cooking results and uses this feedback to dynamically update operation instructions for future cooking sessions. This feedback loop enables the system to learn from past performance and automatically refine parameter settings, achieving both high precision and ease of use without requiring manual intervention.
2Adaptability or versatility
If manual adjustment of multiple operation parameters is required, then cooking flexibility is maintained, but device complexity deteriorates
Solution Approach 1:
The system performs self-optimization by automatically collecting user feedback, analyzing cooking results, and updating its own operation instructions without requiring external intervention or complex user configuration. This self-service capability maintains cooking adaptability across different dishes and preferences while managing system complexity through automated learning rather than manual programming.
Solution Approach 2:
The system handles multiple cooking functions (convection, fan-assisted, conventional, roast, bake, broil) and adapts to various user preferences through a unified feedback-driven framework. This universal approach maintains versatility across different cooking modes while managing complexity through a single adaptive control system rather than separate control mechanisms for each function.
3Manufacturing precision
If user feedback is collected and used to update operation instructions dynamically, then manufacturing precision improves, but device complexity improves
Solution Approach 1:
The system implements a feedback mechanism where user responses about cooking results are collected and used to update operation instructions for future sessions. This feedback loop systematically improves cooking precision by learning from actual outcomes while managing complexity through automated data collection and analysis rather than requiring complex manual calibration systems.
Solution Approach 2:
The system pre-processes and stores operation instructions and cooking parameters before actual cooking sessions, organizing data in a manner that enables quick retrieval and adaptation. This preliminary organization of information reduces the complexity of real-time decision-making while maintaining high precision through pre-analyzed optimal parameter sets.
Data Source
AI summary
A method for operating a connected oven based on subjective user feedback, wherein the connected oven includes a set of in-cavity sensors configured to monitor the foodstuff throughout a cooking session; the method comprising: executing a cooking session according to an initial set of operation instructions to achieve a target food output condition; collecting subjective feedback values from the user for the resulting food output condition of the foodstuff after the cooking session; and updating the initial set of operation instructions based on the feedback values from the user.