Dynamic Control Area Visualization for Real-Time Forward Line Updates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for visualizing control areas, such as the forward lines of groups, are manual and inefficient, particularly in handling large-scale, real-time data updates.
Innovation Solution
A system and method for dynamically visualizing control areas using real-time or near real-time data processing to automatically update forward lines of groups, incorporating data from various sources and providing live updates without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used for visualizing control areas, then simplicity of implementation is maintained, but productivity and real-time responsiveness deteriorate
Solution Approach 1:
The patent replaces manual mechanical visualization methods with an automated computer-based system that processes object data, determines control areas and forward lines algorithmically, and generates visualizations automatically. This substitution of manual operations with automated computational processes resolves the contradiction by achieving real-time productivity while managing complexity through software automation.
2Productivity
If automated real-time data processing is implemented, then productivity and responsiveness improve, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically receiving object data, identifying objects associated with groups, determining control areas and forward lines, and generating visualizations without requiring manual intervention at each step. This automation achieves high productivity while the complexity is contained within the self-service processing architecture.
Solution Approach 2:
The system implements feedback mechanisms where the visualization output can trigger notifications or alerts that feed back into the processing loop, enabling continuous monitoring and automatic adjustments. This feedback loop enhances productivity by maintaining real-time awareness while the structured feedback architecture manages system complexity.
3Measurement precision
If comprehensive object data from multiple sources is processed, then measurement precision and reliability improve, but device complexity and data processing requirements worsen
Solution Approach 1:
The patent segments the complex task of control area visualization into distinct operational steps: receiving object data from multiple sources, identifying objects associated with specific groups, determining control areas for each group, determining forward lines, and generating visualizations. This segmentation of the data processing workflow improves measurement precision by systematically handling each aspect while managing overall complexity through structured decomposition.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
System and method for control area visualization according to certain embodiments. For example, a method includes: receiving object data from a plurality of data sources; identifying a plurality of first objects associated with a first group based at least in part on the object data, each first object of the plurality of first objects being associated with a geospatial location and a buffer area; determining a first control area associated with the first group based at least in part on the geospatial location and the buffer area of each first object of the plurality of first objects; and causing a presentation of the first control area on a display.