System and method for estimating foodstuff completion time
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Solution Overview
Problem
Current food preparation methods often result in nonideal cooking outcomes such as overcooking or undercooking due to the inability to accurately estimate the time required for food to reach a desired temperature, especially with noisy data and changes in cooking conditions.
Innovation Solution
A system and method that uses temperature curves and state estimation techniques, such as a Kalman filter, to accurately estimate the time to completion of cooking by measuring and filtering temperature data from foodstuffs, correcting for noisy readings and adapting to changes in cooking conditions, and providing real-time updates to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional fixed-time cooking methods are used, then the cooking process is simple to operate, but the food preparation quality deteriorates due to overcooking or undercooking
Solution Approach 1:
The system continuously monitors foodstuff temperature during cooking and uses this feedback to dynamically adjust the estimated time to completion. The state estimator processes temperature readings in real-time and updates the completion time estimate, allowing the system to adapt to actual cooking conditions rather than relying on fixed timers.
Solution Approach 2:
The patent replaces traditional mechanical timing mechanisms with a computational system that uses temperature sensors, state estimation algorithms (such as Kalman filter), and dynamic modeling to determine cooking completion. This substitution enables precise control based on actual foodstuff state rather than predetermined time schedules.
2Measurement precision
If temperature measurements are taken frequently to improve accuracy, then the estimation precision improves, but the processing power and storage requirements increase
Solution Approach 1:
The system uses a state estimator that processes temperature measurements efficiently by maintaining a dynamic model of the cooking process. Rather than requiring exhaustive processing of all possible data points, the estimator uses a simplified mathematical model (such as a first-order thermal model) that provides accurate predictions with minimal computational overhead. The system processes only the necessary temperature readings to update the completion time estimate.
3Adaptability or versatility
If the system adapts to different food types and cooking conditions, then the versatility improves, but the device complexity increases
Solution Approach 1:
The patent implements a universal state estimation framework that can handle different food types and cooking conditions through a single integrated system. The dynamic model and state estimator are designed to work with various thermal characteristics by adjusting parameters such as thermal mass and heat transfer coefficients, rather than requiring separate systems for different food types. The system automatically adapts to changing conditions through continuous state estimation.
Solution Approach 2:
The system uses a dynamic model that continuously updates the foodstuff temperature prediction based on actual measurements and changing cooking conditions. The state estimator adjusts model parameters in real-time to account for variations in food type, size, shape, and cooking method, enabling the system to adapt to different scenarios without requiring manual reconfiguration.
4Reliability
If real-time temperature monitoring is implemented, then the reliability of completion estimation improves, but the measurement system complexity increases
Solution Approach 1:
The patent introduces a state estimator as an intermediary between the temperature sensor and the completion time calculation. This intermediary processes the raw temperature measurements, filters noise, and generates a reliable completion time estimate even when individual measurements are noisy or inconsistent. The state estimator acts as a buffer that translates complex sensor data into a simple, reliable prediction.
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 ensures accurate and timely estimation of food completion, adapting to various food types and cooking conditions, reducing the risk of overcooking or undercooking while requiring minimal processing power and storage capacity.
Implementation Method 1
A system and method that uses temperature curves and state estimation techniques, such as a Kalman filter, to accurately estimate the time to completion of cooking by measuring and filtering temperature data from foodstuffs
Data Source
AI summary
A system and method for estimating a time to foodstuff completion can include receiving a measured foodstuff parameter, determining a current foodstuff state based on: a previous foodstuff state and the measured foodstuff parameter, selecting a foodstuff parameter curve based on the current foodstuff state, determining an estimated time to completion using the foodstuff parameter curve.