Automated Tactical Information Collection and Correlation System
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Solution Overview
Problem
The manual analysis of vast amounts of tactical information from unmanned aerial vehicles (UAVs) is time-consuming and resource-intensive, as analysts must sift through hours of video footage to find relevant intelligence, leading to inefficiencies in data collection and correlation.
Innovation Solution
An automated method and system for collecting and correlating tactical information, which involves identifying entities in imagery using a processor, creating relationships between imagery and entities, and storing these relationships in a database, allowing for real-time geo-referencing and automated capture of intelligence based on predefined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of tactical information is used, then analysts can review and interpret data, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The system performs preliminary automated processing of tactical information by identifying entities in imagery, creating relationships between entities and imagery, and organizing data in databases before analyst review. This preliminary action filters and structures data so analysts receive pre-processed information ready for interpretation, reducing their time burden while maintaining accuracy.
Solution Approach 2:
An automated information processing system acts as an intermediary between raw tactical data and human analysts. The system includes components for receiving imagery and telemetry data, identifying entities, creating relationships, and presenting correlated information. This intermediary performs time-consuming processing tasks automatically while preserving analytical accuracy through structured relationship creation.
2Productivity
If automated entity identification is implemented, then data processing speed increases, but system complexity increases
Solution Approach 1:
The automated system is divided into distinct functional modules: an entity identification component that detects entities in imagery, a relationship creation component that links entities to imagery using telemetry data, and a database component that stores structured relationships. This segmentation allows each module to perform its function independently, improving processing speed while managing complexity through modular design.
Solution Approach 2:
Manual mechanical analysis processes are replaced with automated computational systems. The system uses computer vision algorithms for entity identification, automated relationship matching based on telemetry data, and database automation for storage and retrieval. This substitution dramatically increases processing speed while the modular software architecture manages system complexity.
3Loss of information
If all imagery is captured and stored, then complete information is available, but storage requirements and data management become overwhelming
Solution Approach 1:
The system extracts only the essential and relevant information from captured imagery by identifying specific entities and creating relationships between them and the imagery using telemetry data. Rather than storing and analyzing all imagery data, the system extracts key entity information and stores structured relationships in a database, maintaining information completeness for tactical analysis while dramatically reducing data volume.
Solution Approach 2:
The system performs preliminary filtering and organization of imagery data by automatically identifying entities and creating structured relationships before long-term storage. This preliminary action categorizes data into manageable structured formats with defined relationships, making the data more usable and reducing the burden of managing raw imagery volumes while preserving all necessary tactical information.
Data Source
AI summary
A method, and corresponding system, apparatus, and computer program product for automated collection and correlation for tactical information includes identifying an entity in imagery based on a field of view of the imagery using a processor, creating a relationship between the imagery and the entity, and storing the relationship in a database.