Drinking Vessel Shape Recommendation to Accentuate Coffee Flavor Notes
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Solution Overview
Problem
The complex process of roasting and brewing coffee results in diverse flavor profiles, making it challenging to consistently experience and identify specific flavor notes, as individual perceptions are influenced by physiology, memories, and the shape of the drinking vessel, which existing technologies fail to effectively address.
Innovation Solution
A system and method that recommends specific coffee cups with suggestive indicia to enhance the experience of particular flavor notes, using a computerized recommendation engine and database to match coffee with cup designs that accentuate desired flavor notes, and includes sensors and interactive features to collect and analyze user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a standard drinking vessel is used, then the beverage can be consumed, but the flavor notes cannot be consistently experienced or identified
Solution Approach 1:
The drinking vessel incorporates specific local geometric features (such as rim curvature, body contours, and surface textures) that are strategically designed to influence flavor perception. These localized structural qualities modify the drinking experience without requiring complete redesign of the entire vessel system.
Solution Approach 2:
The invention varies geometric parameters of the drinking vessel (angles, curves, dimensions) to create different flavor experiences. By adjusting these physical parameters, the system can accentuate specific flavor notes in coffee, transforming a standard vessel into a flavor-optimizing tool.
2Reliability
If the shape of the drinking vessel is modified to accentuate flavor notes, then flavor perception is enhanced, but the objective measurement of flavor becomes more difficult
Solution Approach 1:
The system incorporates feedback mechanisms where user experiences with specific vessel shapes and flavor notes are collected and stored. This feedback loop allows the system to learn and refine recommendations, improving reliability of flavor experiences while managing the subjective measurement challenge through aggregated data analysis.
Solution Approach 2:
The system provides preliminary guidance to users about which flavor notes to expect with specific vessel shapes before they actually taste the coffee. This preparatory action frames the user's perception and helps them focus on detecting specific flavor notes, making the subjective experience more measurable and reliable.
3Reliability
If suggestive indicia are added to the drinking vessel, then user perception of flavor notes is enhanced through psychological association, but the manufacturing complexity increases
Solution Approach 1:
The suggestive indicia are integrated directly into the drinking vessel design, merging the functional vessel with the communicative element. This combination eliminates the need for separate components and simplifies manufacturing by incorporating the indicia as part of the vessel's basic structure or surface treatment.
Solution Approach 2:
The suggestive indicia use simple, cost-effective visual elements (colors, simple graphics, text) that can be applied through standard manufacturing processes. These indicia are designed to be durable yet simple enough for mass production, avoiding complex or expensive manufacturing techniques.
Data Source
AI summary
The present disclosure provides systems, methods and machine readable programs. In some implementations, the systems, methods and machine readable programs can be used for selecting coffee cups or mugs of particular shapes with the objective of accentuating particular flavor notes in coffee as experienced by a user. In further implementations, the systems, methods and machine readable programs can be used for recommending an infusible extract based on a drinking vessel.