Single Hub Data Aggregation for Heterogeneous Message Structures
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Solution Overview
Problem
Collecting entities face challenges in aggregating data from multiple entities with different message structures, leading to inefficiencies and scalability issues due to the need for multiple hubs and manual data transfer processes.
Innovation Solution
A single hub system that receives and processes messages from multiple entities, regardless of their message structure, by parsing and extracting actionable information, allowing for agnostic analysis and action based on the message structure, thereby eliminating the need for multiple hubs and simplifying data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple hubs are used to handle different message structures from different entities, then each entity can have dedicated message structure support, but the system complexity and cost increase
Solution Approach 1:
The patent implements a universal hub that can handle multiple message structures from different entities through a single point of entry. The hub includes message structure identification logic that automatically detects and parses various message formats (XML, JSON, CSV, etc.) without requiring separate dedicated hubs for each entity or message type. This multi-functional approach allows one hub to perform the work of multiple specialized hubs, reducing system complexity while maintaining adaptability.
Solution Approach 2:
The patent introduces an intermediary message structure identification and parsing layer between the receiving hub and the data processing system. This intermediary layer acts as a mediator that translates various message structures into a standardized internal format, allowing the hub to maintain agnostic behavior toward different message formats while ensuring consistent data processing downstream.
2Reliability
If manual data transfer processes are used between entities and collecting entities, then data accuracy can be verified, but the productivity and efficiency decrease
Solution Approach 1:
The patent implements self-service mechanisms where the message structure identification and parsing processes occur automatically without manual intervention. The hub automatically identifies message structures, selects appropriate parsing logic, extracts data elements, and validates data integrity through automated type checking and format verification. This automation maintains reliability through systematic validation while dramatically improving productivity by eliminating manual data transfer processes.
Solution Approach 2:
The patent incorporates feedback mechanisms in the automated data transfer process, where the system validates received messages against expected formats and structures, and automatically requests retransmission or correction when validation fails. This feedback loop ensures data accuracy is maintained while the overall process remains automated and efficient.
3Adaptability or versatility
If expensive hardware or software updates are required for new message structures, then message structure support can be added, but the adaptability and ease of operation worsen
Solution Approach 1:
The patent implements a dynamic message structure handling system where the hub can adapt to new message formats through software-based message structure identification and parsing logic rather than requiring hardware changes. The system dynamically selects and loads appropriate parsing routines based on the identified message structure type, allowing new formats to be supported through software updates alone, significantly reducing implementation costs and improving ease of manufacture.
Solution Approach 2:
The patent changes the approach from hardware-specific message structure handling to software-configurable parameter-based processing. The hub uses configurable parameters and metadata to identify and process different message structures, allowing new formats to be supported by updating software parameters and parsing logic rather than requiring expensive hardware or software updates.
4Quantity of substance
If data is aggregated from multiple entities with different message structures, then comprehensive data collection is achieved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent segments the message structure analysis process into distinct modular components: message structure identification, parsing logic selection, data element extraction, and validation. Each component handles a specific aspect of the analysis, making the overall complex process manageable and maintainable. The segmentation allows the system to handle diverse message structures through a consistent modular approach rather than requiring monolithic complex analysis logic.
Data Source
AI summary
One embodiment provides a hub of a collecting device that receives messages from entities. The messages are formatted in a message structure that is dependent upon an entity sending the message. The hub analyzes each of the received messages by identifying, from the message structure, information corresponding to an interest of the collecting entity, and discarding information of the message not of interest to the collecting entity. The analysis is agnostic with respect to the entity sending the message and the message structure of the message. The hub performs an action based upon the information corresponding to an interest of the collecting entity.