Olfactory Data Sharing Terminal Using Machine Learning Preference Models
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Solution Overview
Problem
Current technologies lack an effective method for users to indirectly recognize their olfactory preferences without physically interacting with objects, limiting the ability to share and utilize olfactory data between the real and online worlds.
Innovation Solution
A method utilizing an olfactory sensor to generate and share olfactory data, where machine-learning algorithms, such as the user olfactory function fuser(x), determine user preferences by analyzing sensed odor data from standard fragrance samples and applying it to unknown objects, enabling preference determination and display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users physically test odor samples to recognize olfactory preferences, then measurement precision is improved, but device complexity and operation difficulty increase
Solution Approach 1:
The patent creates a digital copy of the olfactory sensing system through machine learning models. The physical olfactory sensor system is replicated as a computational model that can process odor data without requiring physical sampling or direct user interaction with odor sources, thereby maintaining measurement precision while reducing operational complexity
Solution Approach 2:
The patent replaces the mechanical/physical odor testing process with an information-processing system. Instead of requiring users to physically sample and evaluate odors, the system uses machine learning algorithms to analyze odor data and predict preferences, substituting physical interaction with computational analysis
2Measurement precision
If users physically test odor samples to recognize olfactory preferences, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary actions by pre-training machine learning models with extensive odor data and user preference information. This pre-processing allows the system to quickly determine user preferences for new odor samples without requiring time-consuming physical testing, as the computational model can instantly analyze and compare odor characteristics against stored knowledge
Solution Approach 2:
The patent substitutes the time-consuming physical odor testing process with rapid computational analysis. The machine learning system can process and evaluate odor data much faster than human users can physically sample and assess odors, significantly reducing the time required for preference determination
3Adaptability or versatility
If olfactory data is shared between real world and online world, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal olfactory data processing system that can operate in multiple contexts - both in the physical world (through physical sensors) and in the digital world (through data processing and sharing). The same core technology serves dual purposes: physical odor sensing and virtual data analysis, enabling the system to adapt to different environments without requiring separate specialized systems
Solution Approach 2:
The patent introduces an intermediary layer in the form of a cloud-based processing system that mediates between physical olfactory sensors and online applications. This intermediary handles the complexity of data transmission, processing, and sharing, allowing the physical sensing components to remain relatively simple while enabling sophisticated data sharing capabilities
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 users to indirectly recognize their olfactory preferences online, providing accurate information for selecting products like perfumes without smelling them, and allows for the prediction of preferences based on olfactory data, enhancing the shopping experience.
Implementation Method 1
information regarding absorption and desorption between odor molecules and polymer elements
Implementation Method 2
information regarding absorption and desorption between odor molecules and polymer elements
Data Source
AI summary
Provided is an olfactory data sharing terminal including a receiver configured to receive olfactory data obtained by sensing an odor of an object through an olfactory sensor; a preference determiner configured to determine whether a user prefers the received olfactory data, based on a user olfactory function fuser(x); and a display displaying a user preference for the received olfactory data.