Adaptive Learning System for Transaction Processing Latency
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Solution Overview
Problem
Existing systems handling transactions face inefficiencies due to large numbers of fields and increasing complexities, leading to latency issues and potential token deficiencies, which can cause transaction declines and require manual intervention.
Innovation Solution
An adaptive learning system with a product configuration engine that consolidates transaction attributes, unifies structures, and proactively manages token issuance by analyzing depletion rates to prevent deficiencies, eliminating the need for human intervention and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of fields and records are increased to handle transaction complexities, then the system can accommodate more transaction attributes and entities, but system inefficiency and latency increase
Solution Approach 1:
The patent segments the monolithic transaction processing system into a distributed network of edge devices and central servers. Edge devices perform local processing of transaction fields and records, while only essential data is transmitted to central servers. This segmentation allows the system to handle complex transaction attributes distributed across multiple nodes, improving both adaptability and processing efficiency by avoiding centralized bottlenecks.
2Reliability
If more fields are clustered with transactions to capture all attributes, then comprehensive transaction tracking is achieved, but system inefficiency increases due to data volume
Solution Approach 1:
The patent extracts and separates essential transaction attributes from the complete set of fields. Edge devices identify and extract only the critical fields needed for immediate processing and validation, leaving non-essential fields to be handled separately or cached locally. This extraction reduces the data volume transmitted and processed centrally while maintaining reliable tracking of essential transaction attributes.
3Reliability
If manual intervention is implemented to handle token deficiencies and transaction declines, then transaction accuracy can be improved, but latency and operational complexity increase
Solution Approach 1:
The patent implements self-service mechanisms where edge devices autonomously detect token deficiencies and handle transaction declines without requiring manual intervention. The system automatically retrieves additional tokens from distributed pools, validates transaction parameters locally, and resolves common errors at the edge. This self-service capability maintains high transaction accuracy while eliminating the latency associated with manual processing.
4Speed
If distributed edge devices are deployed to process transactions locally, then processing speed and user experience are improved, but system complexity and token management challenges increase
Solution Approach 1:
The patent implements a universal token pool architecture where distributed edge devices share access to common token pools through standardized protocols. Each edge device can independently access and utilize tokens from any pool in the network, eliminating the need for separate token management systems at each location. This universal approach simplifies distributed system management while maintaining fast local processing capabilities.
Data Source
AI summary
The adaptive learning systems described herein may include machine-learning engines, product configuration engines, and/or various other components configured to improve the efficiency of processing transactions. The systems described herein may detect and/or predict declined transactions, token deficiencies, insufficient system capacities, and/or other system anomalies. As such, the system may perform operations to generate additional tokens associated with assets, provision various bin ranges, and/or share reserve capacities, and/or other operations. Thus, the system may improve system efficiencies, ensure reliability and operability across the system, and optimize the operations for successfully processing transactions.