Beverage Appliance Pod Recognition Using Segmented Code Analysis
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Solution Overview
Problem
Existing beverage systems lack efficient methods for authenticating and identifying beverage pods, which can lead to the use of counterfeit or expired pods, potentially affecting the quality and safety of the beverages produced.
Innovation Solution
The system incorporates a camera and processor that analyze a code on the beverage pod, specifically decoding a barcode section, analyzing a design section for authentication, and optionally reading a date section. This process involves storing bits of information about the code without storing the entire image, allowing for efficient memory usage and cost-effective implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire code image is stored in memory for analysis, then authentication accuracy is improved, but memory cost and device complexity increase
Solution Approach 1:
The system extracts only the essential features from the code image (barcode section, design section, date section) rather than storing the entire image. The camera captures the code and the processor analyzes specific sections to extract authentication information, eliminating the need to store the complete high-resolution image in memory.
Solution Approach 2:
The code is divided into distinct sections (barcode section, design section, date section) that are analyzed separately. Each section contains specific information needed for authentication, allowing the system to process and store only the relevant data from each segment rather than the entire code image.
2Measurement precision
If a high-resolution camera is used to capture the code, then code recognition accuracy is improved, but device cost and processing time increase
Solution Approach 1:
The system uses a standard-resolution camera to capture the code image, then extracts only the necessary information from specific sections (barcode, design, date) rather than processing the entire high-resolution image. This extraction approach maintains recognition accuracy while significantly reducing processing time and computational requirements.
Solution Approach 2:
The system performs partial analysis by focusing only on the essential sections of the code (barcode section, design section, date section) rather than analyzing the entire image in detail. This partial action approach achieves sufficient authentication accuracy without the excessive processing time that would result from analyzing the complete high-resolution image.
Data Source
AI summary
Described herein is an appliance for making a beverage that can include a pod receiver, a camera oriented to capture an image of a code depicted on the pod, a processor and memory in communication with the processor where the processor includes programmed instructions that cause the processor to analyze a design section of the code.