Nutritional Value Prediction via Power Supply Sensing
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Solution Overview
Problem
Optimizing nutrient intake is complex due to individual variations, requiring personalized approaches based on factors like gender, health status, and eating habits, and existing systems lack efficient methods for predicting nutritional values during food processing.
Innovation Solution
A nutritional value prediction system that uses a 'smart-plug' to determine processing characteristics of kitchen appliances by sensing power supply parameters, allowing for accurate prediction of nutritional values based on food identity and processing conditions, eliminating the need for post-processing measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If post-processing measurement is used to determine nutritional value, then measurement accuracy can be ensured, but user convenience deteriorates and time consumption increases
Solution Approach 1:
The system performs preliminary action by predicting nutritional value during the food processing operation itself, rather than measuring after processing. The predictor uses processing characteristics (temperature, time, appliance type) to calculate nutritional value in real-time, eliminating the need for post-processing measurement and weighing operations.
2Measurement precision
If post-processing weighing and measurement is performed, then accurate nutritional value can be obtained, but time consumption and operational complexity increase
Solution Approach 1:
The system replaces mechanical measurement systems (scales, post-processing analysis equipment) with a computational prediction system. The predictor calculates nutritional value based on processing characteristics data, substituting physical measurement with mathematical modeling to reduce time and operational steps.
3Measurement precision
If detailed food quantity measurement is performed, then prediction accuracy improves, but device complexity and ease of operation worsen
Solution Approach 1:
The system applies self-service by automatically obtaining food quantity data through the appliance's own sensors and processing characteristics, without requiring external measurement devices or manual input. The appliance itself provides the data needed for prediction, eliminating the need for separate weighing equipment.
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
Enables intuitive and accurate monitoring of nutritional intake by predicting nutritional values of processed food, considering factors like calorie, vitamin, and mineral content, improving user convenience and accuracy in assessing dietary intake.
Implementation Method 1
a parameter sensor adapted to detect a parameter of a power supply provided to the kitchen appliance
Data Source
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AI summary
The invention provides a nutritional value prediction system. A nutritional value of processed food is predicted based on an identity of food to be processed and processing characteristics of a kitchen appliance used to process the food to be processed. Processing characteristics of the kitchen appliance are determined based on a sensed parameter of a power supply of the kitchen appliance.