AWARE System for Global Event Detection and Semantic Analysis
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Solution Overview
Problem
Existing systems for detecting and tracking socially disruptive events, such as disease outbreaks and civil unrest, are limited in their ability to efficiently process and communicate event-related information across global scales, lacking comprehensive and timely analysis and reporting capabilities.
Innovation Solution
The AWARE (Argus Workflow Analysis Reporting Environment) system enhances event detection and tracking by incorporating semantic coding, social media and video ingestion, and advanced visualization technologies, allowing for structured data generation and scalable reporting to support diverse user needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing systems for detecting and tracking socially disruptive events are used, then basic event detection capability is provided, but the ability to efficiently process and communicate event-related information across global scales is limited
Solution Approach 1:
The system is divided into multiple specialized subsystems: information collection subsystem for gathering data from diverse sources, information storage and archive subsystem for organized storage, information tagging subsystem for semantic coding and classification, information analysis subsystem for processing and identifying patterns, and information communications subsystem for dissemination. This segmentation allows each subsystem to handle specific tasks efficiently, improving overall productivity while managing complexity through modular design.
Solution Approach 2:
The patent introduces an information analysis subsystem as an intermediary between the collection and communication subsystems. This intermediary layer processes raw information, applies semantic coding, identifies patterns, and prepares structured data for communication. The intermediary handles the complex processing tasks, allowing the collection and communication subsystems to remain relatively simple while achieving high processing efficiency.
2Reliability
If comprehensive event detection capabilities are implemented, then timely analysis and reporting is improved, but processing time and resource requirements increase
Solution Approach 1:
The system performs preliminary actions by collecting and storing information from multiple sources continuously, applying semantic coding and tagging in advance, and maintaining organized archives of event data. This preliminary processing ensures that when events need to be analyzed and reported, the system can quickly retrieve and process pre-prepared information, improving timeliness without increasing real-time processing time.
Solution Approach 2:
The information collection and processing operations run continuously rather than being triggered only when events occur. The system continuously gathers data from information sources, updates semantic codes and tags, and maintains current archives. This continuous operation eliminates startup delays and ensures the system is always ready to detect and report events immediately, improving reliability without adding processing time when events actually occur.
3Productivity
If automated data extraction and dissemination is implemented, then analyst productivity is enhanced and reporting time is reduced, but system complexity and automation requirements increase
Solution Approach 1:
The system performs self-service by automatically collecting information from sources, applying semantic coding and tagging rules, analyzing data patterns, and disseminating reports without requiring manual analyst intervention for each task. The automated processes handle routine operations, allowing analysts to focus on higher-value activities such as interpreting results and making decisions. This self-service automation significantly enhances analyst productivity while the modular architecture manages the complexity of automated operations.
Data Source
AI summary
A system and method involves detecting operational social disruptive events on a global scale, modeling data in conjunction with linguistics analysis to establish responsive actions, and generating visualization and executing models for communicating information.