Hash-Based Design Parameters for Scalable Personalization
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Solution Overview
Problem
Conventional methods for product personalization are time and cost-intensive, lack scalability, and do not provide a democratized platform for connecting customers with designers, and there is a need for immersive product selection experiences with unique and reproducible design ownership.
Innovation Solution
A system and method that utilizes a secure hash algorithm to convert user inputs into design parameters, generates personalized designs using generative algorithms, tokenizes them as non-fungible tokens (NFTs) in blockchain, and allows users to create customized generative algorithms, ensuring unique and reproducible designs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If exclusive designers are connected with customers to create personalized products, then product personalization quality is improved, but time and cost increase and scalability deteriorates
Solution Approach 1:
The patent uses generative algorithms to create digital replicas of design processes. Instead of connecting customers with human designers for each customization, the system copies the creative process through algorithmic generation, allowing unlimited scalability while maintaining personalization quality through deterministic output from seed inputs.
Solution Approach 2:
The patent replaces the mechanical system of human designer-customer interaction with an automated computational system. The generative design algorithm acts as a virtual designer that transforms customer inputs into personalized designs automatically, eliminating the need for human intervention while maintaining design quality.
2Productivity
If pre-defined modular components are used for product customization, then scalability is improved, but personalization scope is limited
Solution Approach 1:
The patent changes the parameters of generative algorithms through seed inputs derived from customer data. By adjusting algorithm parameters based on customer preferences, purchase history, and behavioral patterns, the system achieves both scalability and extensive personalization scope without being limited to pre-defined modules.
Solution Approach 2:
The patent introduces dynamic personalization where the generative algorithm adapts its behavior based on real-time customer inputs and preferences. The system evolves from static pre-defined modules to dynamic algorithmic generation that can create unlimited design variations tailored to each customer's unique preferences.
3Ease of manufacture
If conventional design platforms are used, then design creation is simplified, but unique design ownership and verifiability are lost
Solution Approach 1:
The patent introduces blockchain as an intermediary layer between design generation and ownership verification. The blockchain verifies and records design ownership through cryptographic hashing, providing reliable proof of unique design creation while maintaining the simplicity of the design generation process through the generative algorithm interface.
Data Source
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AI summary
The disclosure relates generally to methods and systems for generating personalized designs based on a personalized input provided by a user. Conventional techniques for personalized designs lack a democratized design content platform to connect retailers, designers or digital artists or creative coders or generative artists and the customers. According to the present disclosure, the customer or a user provides personalized input. Further, the customer or the user is allowed to choose a generative design of interest by selecting a suitable generative design algorithm from a list of generative design algorithms. The personalized input provided by the customer is then transformed as a hash value which is used to determine a set of design parameters based on a set of design attributes, using a random number generation technique. Finally, the set of design parameters are then used to generate an exclusive personalized design.