Optimal Resource Routing via Contextual Data Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems fail to optimally select resource channels based on contextual and historical data, neglecting real-time and future resource needs, and do not effectively balance the interests of payors and resource processors.
Innovation Solution
A system utilizing contextual data analysis and historical usage data to determine optimal resource channels by analyzing patterns and models associated with resource delivery events, considering factors like efficiency, cost, and security, and communicating these findings to both resource providers and processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional resource channel selection systems are used, then resource delivery can be completed, but the system fails to optimize resource channel selection based on contextual and historical data, resulting in suboptimal efficiency and cost-effectiveness
Solution Approach 1:
The system performs preliminary analysis of contextual information and historical usage data before resource delivery to pre-determine optimal resource channels. The optimal resource channel determination module analyzes patterns and models associated with the resource and historical channel data in advance, enabling real-time recommendations without adding complexity to the actual delivery process.
Solution Approach 2:
The system enables resource presenters and processors to automatically receive optimal resource channel recommendations without manual intervention. The determination module autonomously analyzes data and provides recommendations, allowing the system to serve itself in optimizing resource channel selection while maintaining simplicity for users.
2Loss of time
If real-time optimal resource channel recommendations are provided, then resource delivery efficiency improves, but the system must process and analyze multiple data sources in real-time, increasing computational requirements
Solution Approach 1:
The system performs preliminary analysis of historical usage channel data and contextual information before real-time resource delivery decisions are needed. By pre-processing and storing patterns and models associated with resources and channels, the system reduces the computational burden during real-time operations, enabling fast recommendations without excessive energy consumption.
Solution Approach 2:
The system replaces complex real-time computational analysis with pre-computed patterns and models derived from historical data. Instead of performing heavy data processing during real-time resource delivery, the system uses stored analytical results to provide rapid recommendations, significantly reducing computational energy requirements while maintaining real-time responsiveness.
3Reliability
If the system balances the interests of both payors and resource processors, then overall system effectiveness improves, but the system must simultaneously consider multiple conflicting objectives, increasing decision-making complexity
Solution Approach 1:
The optimal resource channel determination module serves multiple functions simultaneously: it analyzes contextual information, processes historical usage data, identifies patterns and models, and generates recommendations that balance the interests of both resource presenters and processors. This multi-functional approach consolidates multiple decision-making processes into a single unified system, reducing overall complexity while improving reliability through comprehensive analysis.
Data Source
AI summary
Systems, apparatus are defined that provide for determining optimal resource channels for delivering resources using contextual and prior usage data analysis. As such, the present invention is able to determine and communicate to the resource presenter the optimal resource channel, in which optimal is defined as being most beneficial to the resource presenter and/or resource processor. In this regard, the present invention takes into account the efficiency (i.e., time to process), cost, security, usage, and other benefits associated with the resource presenter and/or resource processor in determining which resource channel is optimal for any given resource delivery event.