Animal Data Aggregation for Faster Outbreak Decisions

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing systems struggle to efficiently manage and coordinate the vast amount of raw information during animal disease outbreaks, leading to inefficient and ineffective decision-making processes.

Innovation Solution

A system and method for monitoring and analyzing animal-related data, which includes a processor and memory to identify parameters, aggregate data from various sources, correlate it against a baseline, and analyze the data to assess animal management, while ensuring secure and compartmentalized data sharing based on user type and emergency needs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If data is aggregated from multiple sources during animal disease outbreaks, then information completeness is improved, but data management complexity increases

Engineering Contradiction:

Improveinformation completenessVSAvoiddata management complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system segments data from multiple sources into distinct categories and channels, organizing raw information from news reports, official updates, spreadsheets, maps, photos and documents into structured segments that can be managed independently while maintaining overall information completeness

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary data coordination layer that mediates between multiple data sources and decision-makers, standardizing and coordinating information flow without requiring decision-makers to directly manage the complexity of raw data from numerous sources

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If comprehensive data is provided to decision-makers during outbreaks, then decision quality is improved, but information processing time increases

Engineering Contradiction:

Improvedecision qualityVSAvoidinformation processing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary data aggregation, coordination and organization before presenting information to decision-makers, so that when data is provided during outbreaks, it is already processed and ready for immediate use, reducing information processing time while maintaining decision quality

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms that provide timely updates and coordinated information to decision-makers, allowing them to receive comprehensive data without excessive processing delays through efficient information flow management

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If data sharing is expanded among stakeholders, then collaboration is improved, but data security risks increase

Engineering Contradiction:

ImprovecollaborationVSAvoiddata security risks

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The system applies different data sharing permissions and security levels to different stakeholders based on their specific roles and needs, allowing expanded collaboration among authorized users while maintaining data security through localized access control rather than uniform data sharing

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS12430355B2Method and data service for converting and outputting animal related data

Publication Date: 2025.09.30 THE GOVERNMENT OF THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SEC OF HOMELAND SECURITY

AI summary

A system and computerized method for monitoring and analyzing animal related data. In one embodiment, the system includes a processor and memory operable to identify a parameter related to animal management for species in a biological environment, aggregate animal related data from different sources about the parameter of the species, identify a baseline for the parameter, correlate the animal related data against the baseline to obtain correlated data, and analyze said correlated data to assess said animal management.