Transaction Reconciliation via Object Recognition Signatures
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Solution Overview
Problem
Existing transaction systems lack the ability to reconcile transactions among multiple provider or user accounts and fail to account for derived object attributes, limiting their functionality in complex transaction scenarios.
Innovation Solution
A transaction system comprising a recognition engine, a transaction engine, and device engagement engines that derive digital representations of real-world objects, associate attributes with recognition signatures, and use reconciliation matrices to map these signatures to multiple accounts, enabling transactions and account reconciliations across multiple providers or users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single-provider transaction system is used, then the system is simple to operate, but it cannot reconcile transactions among multiple provider or user accounts
Solution Approach 1:
The system segments the transaction reconciliation process into distinct functional modules: a recognition engine that identifies objects and derives attributes, a transaction engine that processes multiple accounts, and device engagement engines that interface with users. This segmentation allows the complex multi-account reconciliation functionality to be implemented while maintaining manageable system architecture and operational simplicity.
2Productivity
If existing transaction systems are used, then manual processing is required, but this reduces transaction processing efficiency
Solution Approach 1:
The system implements self-service automation where the recognition engine automatically identifies objects, derives relevant attributes, and the transaction engine automatically reconciles transactions across multiple accounts without requiring manual intervention. This self-service capability dramatically improves transaction processing efficiency while the system maintains ease of operation through automated workflows that eliminate manual processing steps.
3Adaptability or versatility
If object recognition is implemented, then derived object attributes can be used for transactions, but this increases system complexity
Solution Approach 1:
The recognition engine is designed as a universal component that can identify various types of objects and derive multiple kinds of attributes applicable to different transaction scenarios. This multi-functional engine handles diverse object recognition tasks and attribute derivations through a single unified system, enabling the use of derived object attributes across multiple transaction types without proportionally increasing system complexity.
Data Source
AI summary
Methods and systems of enabling location-based transactions of virtual goods are disclosed. At least one location attribute is derived from a digital representation of a real-world scene captured at least in part by a mobile device. The location attribute is used as a basis to identify at least one virtual game good offered by at least one merchant. A reconciliation matrix related to the at least one virtual game good and the at least one merchant is identified, wherein the reconciliation matrix comprises a provisioned template from the at least one merchant. A transaction with respect to the at least one virtual game good between at least one merchant account of the at least one merchant is enabled according to the reconciliation matrix based on a merchant identifier and at least one user account associated with the mobile device.