Dynamic Operational Hierarchy for Real-Time Military Unit Tracking
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Solution Overview
Problem
Current methods for analyzing military exercises struggle to accurately assess the performance of individual units and personnel due to the ad-hoc and fast-paced nature of operational changes during large-scale deployments, leading to outdated performance evaluations.
Innovation Solution
A method that updates the operational hierarchy in real-time using unit element tracking data and a trained classification algorithm, allowing for dynamic task adjustments and resource sharing, thereby generating more accurate performance scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a pre-determined operational hierarchy is used for performance analysis, then the analysis structure is simple and stable, but it becomes outdated and inaccurate when operational changes occur during exercises
Solution Approach 1:
The patent implements a dynamic operational hierarchy that automatically updates during exercises based on real-time tracking data. The system transitions from a static pre-determined hierarchy to a dynamic structure that adapts to operational changes, ensuring performance assessments remain accurate throughout the exercise duration.
Solution Approach 2:
The system continuously monitors unit element tracking data and uses this feedback to automatically update the operational hierarchy. The feedback loop compares actual positions and movements against the expected hierarchy, triggering automatic updates when deviations are detected, thus maintaining accuracy without manual intervention.
2Measurement precision
If tracking data is gathered at the individual level, then fine-grained performance analysis becomes possible, but the quantity and complexity of data becomes overwhelming
Solution Approach 1:
The patent segments the large volume of individual tracking data into meaningful units by automatically grouping individuals into units based on their hierarchical relationships. This segmentation reduces data complexity by organizing granular individual data into structured unit-level patterns that are easier to analyze and interpret.
Solution Approach 2:
The operational hierarchy acts as an intermediary layer between individual tracking data and performance analysis. It mediates the complex individual-level data by providing a structured framework that automatically organizes and contextualizes the data, making it manageable for analysis without losing the fine-grained detail.
3Measurement precision
If manual updates to operational hierarchy are performed to reflect changing tasks, then accuracy can be maintained, but the process cannot keep pace with fast-moving operational changes
Solution Approach 1:
The system performs self-service by automatically detecting operational changes through tracking data and updating the operational hierarchy without human intervention. The algorithm autonomously identifies when units deviate from their assigned tasks or form new groupings, and automatically recalibrates the hierarchy to reflect current operations, maintaining both accuracy and speed.
Solution Approach 2:
The patent replaces the manual mechanical process of hierarchy updates with an automated computational system. Instead of operators manually reviewing and updating hierarchy documents, a computer-based algorithm continuously processes tracking data and automatically generates updated hierarchies, dramatically increasing update speed while maintaining accuracy.
Data Source
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AI summary
There is provided a method of tracking a plurality of military units during a battlefield exercise. The method comprising receiving an operational hierarchy, said operational hierarchy: (a) associating each unit of the plurality of military units with one or more respective tasks, and (b) associating each unit with one or more respective unit elements. For one or more time periods of the battlefield exercise, receiving respective unit element tracking data for each element. For the one or more time periods, updating the operational hierarchy by applying a trained classification algorithm to the respective unit element tracking data to generate an updated operational hierarchy for said time period. The step of updating comprises, modifying one or more of the associations between each unit and one or more respective unit elements or one or more respective tasks.