Dynamic NFT Segmentation for Goal Visualization
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Solution Overview
Problem
Current technologies lack effective methods to visualize and achieve goals using non-fungible tokens (NFTs), which are unique digital designs recorded on a blockchain ledger, limiting user engagement and goal accomplishment.
Innovation Solution
A generative artificial intelligence (GenAI) model generates and modifies NFTs based on user interactions and account activity, allowing dynamic evolution of images and transfer of image segments on a blockchain ledger, enhancing user engagement and goal visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If NFTs are used to represent goals, then proof of ownership and unique digital design are achieved, but user engagement and goal accomplishment are limited due to lack of effective visualization methods
Solution Approach 1:
The NFT image is divided into multiple segments or regions, where each segment can be independently manipulated, transferred, or evolved. This segmentation allows users to interact with specific portions of the NFT rather than treating it as a monolithic asset, thereby enhancing engagement while maintaining ownership proof through blockchain
Solution Approach 2:
The NFT is designed to be dynamic rather than static. The image can evolve, transform, or change based on user actions, goal progress, or external triggers. This dynamic nature makes the NFT more engaging and interactive while still maintaining its unique digital identity and ownership verification on the blockchain
2Device complexity
If static NFT images are used, then simple ownership representation is achieved, but user engagement and interactive goal tracking are limited
Solution Approach 1:
The patent transforms static NFT images into dynamic, evolving visual representations. The NFT can change its appearance, add new elements, or modify existing features based on user progress toward goals, account activity, or other triggers. This dynamic evolution maintains relatively simple underlying structure while dramatically improving user engagement through visual feedback
3Device complexity
If complete NFT transfer is required, then simple transaction processing is achieved, but partial progress recognition and selective reward distribution are limited
Solution Approach 1:
The patent enables segmentation of NFT transfer by allowing specific portions or segments of the NFT image to be transferred independently from the complete NFT. This allows for partial transfer capability where users can reward or recognize specific achievements by transferring only relevant portions of the NFT, rather than requiring transfer of the entire asset
Solution Approach 2:
Different segments of the NFT can have different properties, transferability rules, or meanings. This local quality approach allows specific regions of the NFT to be configured for different purposes - some segments may be freely transferable, others may require approval, and others may represent different types of rewards or achievements
Data Source
AI summary
An example operation may include one or more of generating a dynamically-modifiable image comprising a plurality of pieces of interconnected content via an image generating model and displaying the dynamically-modifiable image via a user interface of a software application, installing a smart contract that includes an identifier of an owner of the dynamically-modifiable image on a blockchain ledger, detecting removal of a piece of content from among the plurality of pieces of interconnected content based on user inputs via the user interface, detecting addition of the removed piece of content to a different dynamically-modifiable image of a different user, and in response to the detected addition, executing an electronic payment transaction to transfer value from the owner of the dynamically-modifiable image to the different user based on the smart contract installed on the blockchain ledger.