Customizable Liquid Blending System with Algorithmic Recipe Refinement
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Solution Overview
Problem
Current liquid systems for consumable beverages, such as wine blending, are inefficient in selecting user preferences and incorporating feedback, leading to inaccurate blends and overwhelming winemakers with complex processes.
Innovation Solution
A customizable liquid blending and dispensing system that uses a user interface to select and blend liquids based on coordinate locations, with an algorithm determining the blend recipe, and incorporates user feedback to refine subsequent blends, stored in a database for future dispensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional liquid blending systems are used with manual selection processes, then the system is simple to operate, but the beverage selection efficiency is low and user preferences cannot be accurately identified
Solution Approach 1:
The patent replaces manual mechanical selection processes with an automated computer-based system that uses algorithms to analyze user feedback and determine optimal blend recipes. The processor automatically calculates blend proportions based on coordinate inputs from the whiteboard interface, eliminating tedious manual blending processes while improving selection efficiency.
Solution Approach 2:
The system enables users to directly interact with the blending process through the whiteboard interface, where they can visually select and manipulate liquid components. The algorithm then autonomously processes this input to generate recipes, creating a self-service mechanism that empowers users while maintaining system automation.
2Adaptability or versatility
If extensive liquid options are provided to meet consumer demands, then product variety is high, but consumer selection becomes overwhelming and inefficient
Solution Approach 1:
The system incorporates user feedback loops where consumer preferences are continuously captured through the whiteboard interface and fed back into the algorithm. This allows the system to learn and adapt to individual user preferences, making selection easier while maintaining extensive liquid variety. The feedback mechanism transforms the overwhelming choice into a personalized, guided experience.
Solution Approach 2:
The whiteboard interface serves multiple functions: it displays available liquids, captures user preferences through coordinate inputs, visualizes blend compositions, and provides feedback to the algorithm. This multi-functional interface simplifies the selection process while supporting extensive liquid variety through a single unified system.
3Productivity
If manual blending processes are used for each beverage preparation, then the system is simple, but the blending frequency and productivity are limited
Solution Approach 1:
The system performs preliminary actions by pre-calculating optimal blend recipes based on user preferences stored in the database. When a user requests a beverage, the system can quickly retrieve and execute pre-determined recipes, enabling high blending frequency without requiring complex real-time calculations for each preparation.
Solution Approach 2:
The patent replaces manual blending operations with an automated liquid dispensing system controlled by the processor. The system automatically measures and combines liquids according to the algorithm-determined recipes, eliminating manual blending tasks and enabling rapid, high-frequency beverage preparation.
4Measurement precision
If expert advice is relied upon for beverage selection, then selection accuracy may be high, but the system cannot capture individual user preferences and feedback
Solution Approach 1:
The system implements continuous feedback collection through the whiteboard interface, capturing individual user preferences and responses to different liquid blends. This feedback is stored in the database and used to refine future recommendations, enabling the system to accurately identify and adapt to each user's unique preferences rather than relying on generic expert advice.
Solution Approach 2:
Users directly interact with the system through the whiteboard interface, making their own selections and providing direct feedback on their preferences. This self-service approach empowers users to define their own preferences accurately while the system adapts to their individual tastes, replacing the need for external expert intervention.
Data Source
AI summary
One or more aspects of the present disclosure provide improved liquid systems, as well as improved liquid system techniques. For example, a liquid system may include a liquid blending system and a liquid dispensing system that more efficiently meets the demands of consumers/users. Specifically, liquid blending and dispensing systems described herein may facilitate user blending of various liquids, accurate user identification of sensory characteristics associated with various liquid blends and liquid blend components, efficient handling of user feedback and refinement of subsequent liquid blends, etc. For instance, a liquid blending system may take user selection input and provide a liquid. The liquid system may store data describing the provided liquid in a database. Further, the liquid system may receive and analyze user input regarding the provided liquid and provide a subsequent liquid blend recipe based on the user input and the stored data describing the original blend.