Spectral Camera Food Selection System for Freshness Matching
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Solution Overview
Problem
Existing methods for selecting food products, especially in online supermarkets, struggle to accurately match user desires for food freshness and quality, leading to suboptimal selection and potential waste.
Innovation Solution
A food selection method that utilizes spectral cameras to obtain spectra of foods, compares this information with user desire attributes, and selects foods that best match the user's preferences, including freshness, ripeness, and cooking methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional selection methods are used in online supermarkets, then the selection process is simple, but the accuracy of matching user desires for food freshness and quality is poor
Solution Approach 1:
The patent replaces traditional visual inspection and manual selection methods with spectral camera technology. The spectral camera captures spectral information about food properties (color, texture, freshness indicators) and automatically compares this data with user preference profiles to make selections, substituting mechanical/visual inspection with optical measurement and automated data processing.
Solution Approach 2:
The patent introduces spectral information as an intermediary between the food product and user preferences. The spectral camera measures physical properties of the food, this spectral data is processed and compared with user desire information, and the system selects foods based on this intermediate comparison, thereby improving matching accuracy without direct human intervention.
2Measurement precision
If spectral camera measurement is implemented, then food selection accuracy improves, but measurement and processing time increases
Solution Approach 1:
The patent performs preliminary measurement of spectral information for all available foods and pre-comparison with user preference profiles before the actual selection moment. This allows the system to have ready-made assessment data, reducing real-time measurement and processing time when a selection is actually needed.
Solution Approach 2:
The patent creates a digital spectral profile copy of each food item's properties and stores it for rapid retrieval and comparison. Instead of physically measuring each food during selection, the system retrieves and compares pre-acquired spectral data copies, significantly reducing measurement time while maintaining accuracy.
3Manufacturing precision
If comprehensive spectral analysis is performed on all food attributes, then selection precision improves, but system complexity and processing requirements increase
Solution Approach 1:
The patent extracts only the specific spectral characteristics that are relevant to food quality assessment and user preferences (such as color, texture, moisture content indicators) rather than performing comprehensive analysis of all possible food attributes. This selective extraction maintains selection precision while reducing processing complexity.
Solution Approach 2:
The patent applies different levels of spectral analysis to different food attributes based on their importance to user preferences. Critical quality attributes receive detailed spectral measurement and analysis, while less important attributes receive simplified processing, optimizing the balance between selection precision and system complexity.
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
This method enables the accurate selection of foods that meet user desires, reducing waste and improving customer satisfaction by ensuring foods are selected at optimal freshness and quality.
Implementation Method 1
obtaining one or more spectra corresponding to each of one or more foods, the one or more spectra being a result of measurement of each of the one or more foods using a spectral camera
Data Source
AI summary
A food selection method includes obtaining one or more spectra corresponding to each of one or more foods, the one or more spectra being a result of measurement of each of the one or more foods using a spectral camera, comparing desire information indicating an attribute of a food desired by a user and a state of each of the one or more foods based on the one or more spectra, and selecting a food that suits the user's desire on a basis of a result of the comparing.