Blockchain Token Matching for Commodity Tender Execution
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Solution Overview
Problem
Existing systems face challenges in efficiently managing and tracking unique and interchangeable commodities on a large scale, particularly in transactions involving non-fungible tokens and fungible tokens, while also leveraging real-time analytics and user profiles for optimal trading recommendations.
Innovation Solution
A method and system for creating item and request tokens on a blockchain platform, matching these tokens based on attributes, and generating trades using a blockchain engine to facilitate secure and efficient transactions through smart contracts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional trading platforms are used to manage large commodity transactions, then existing infrastructure can be utilized, but managing the status and information of commodities becomes challenging due to the uniqueness of non-fungible items and interchangeable nature of fungible tokens
Solution Approach 1:
The patent creates digital token representations (copies) of physical commodities on the blockchain. Each commodity or batch of commodities is represented by a token that contains all relevant attributes and status information. This copying approach allows the system to handle both unique non-fungible items and interchangeable fungible items uniformly through their token representations, simplifying management while maintaining versatility.
Solution Approach 2:
The patent implements a universal token-based framework that can represent both non-fungible and fungible commodities within the same system. The token structure is designed to accommodate various commodity types and trading scenarios, enabling a single platform to handle diverse transaction types without requiring separate management systems for different commodity categories.
2Reliability
If vast trading data is collected for analysis, then trade recommendations can be improved, but the difficulty of analyzing and processing the data increases
Solution Approach 1:
The patent extracts only the essential attributes and information needed for trading decisions from the vast amount of available data. By focusing on key token attributes rather than processing all possible data points, the system maintains high recommendation quality while reducing analysis complexity. The blockchain structure naturally organizes data into extractable, relevant fields.
3Productivity
If manual processes are used for matching items and offers, then flexibility in negotiation is maintained, but the efficiency and speed of trade execution decreases
Solution Approach 1:
The patent implements automated matching mechanisms where the system itself performs the matching of item tokens with offer tokens based on predefined criteria. The smart contracts automatically execute trades when matching conditions are met, eliminating the need for manual intervention while maintaining operational simplicity. Parties can set their preferences and let the system handle the matching process autonomously.
Solution Approach 2:
The system provides real-time feedback on matching status and trade execution through the blockchain network. All participants can monitor the status of their offers and items, and the automated system adjusts matching based on current market conditions and participant preferences, combining speed with operational transparency.
Data Source
AI summary
A computer implemented method for managing tokens on a blockchain platform. The method uses a number of processor units to receive a first set of attributes associated with a number of items and a second set of attributes associated with a number of offers to purchase the number of items. The number of processor units creates an item token on the blockchain platform for each item from the number of items based on the first set of attributes to form a number of item tokens. The number of processor units create a request token on the blockchain platform for each offer to purchase based on the second set of attributes to form a number of request tokens. The number of processor units create a number of matching tokens and a number of trades based on the matching tokens.