Multidimensional Network Visualization for Signal Diagnosis
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Solution Overview
Problem
Current methods for diagnosing and troubleshooting energy emissions and computing architecture issues are cumbersome and inefficient, as they rely on manual evaluations and require extensive equipment, making it difficult to visualize invisible signals and radiation emissions in real-time.
Innovation Solution
An environmental visualization system that uses augmented reality to generate a multidimensional layout of network nodes and signals, allowing users to visualize communication networks and energy spectra through distinct visual, tactile, or audible properties, enabling real-time or recorded playback for improved troubleshooting and diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If traditional manual evaluation methods are used to diagnose energy emissions and computing architecture issues, then equipment requirements and process complexity increase, but visualization capability and diagnostic efficiency remain insufficient
Solution Approach 1:
The patent replaces traditional mechanical measurement equipment and manual evaluation processes with a computational system that uses software-based signal processing and visualization. The system captures signals through standard interfaces, processes them through algorithms, and generates visual representations, eliminating the need for complex specialized hardware while improving visualization capability.
Solution Approach 2:
The patent introduces a computational environment as an intermediary between the physical system generating signals and the human observer. This intermediary captures, processes, and transforms raw signals into visualized representations that reveal patterns and issues not directly observable, thereby improving detection capability without requiring direct physical measurement equipment.
2Measurement precision
If comprehensive equipment arrays are deployed to detect radiation emissions, then measurement capability improves, but time consumption and operational complexity increase
Solution Approach 1:
The patent merges multiple detection functions into a single integrated computational system. Instead of using separate specialized equipment for different types of measurements, the system combines signal capture, processing, analysis, and visualization into one unified platform, maintaining measurement precision while reducing the time and complexity associated with coordinating multiple devices.
Solution Approach 2:
The patent performs preliminary signal processing and pattern recognition automatically as signals are captured, rather than requiring post-processing analysis. The system pre-computes visualized representations and identifies potential issues in real-time, reducing the time required for diagnostic analysis while maintaining detection accuracy.
3Loss of information
If manual tracing and monitoring methods are used to understand data flow in computing architectures, then system understanding may be achieved, but operational complexity and cognitive workload increase
Solution Approach 1:
The patent uses visualized representations with distinct visual properties (such as color coding, intensity variations, and graphical indicators) to represent different aspects of data flow and system states. This visual encoding transforms abstract data flow information into intuitive visual patterns that are easily interpreted, improving understanding while reducing cognitive workload and operational complexity.
Solution Approach 2:
The patent transforms one-dimensional data flow information into multi-dimensional visualized representations that display temporal, spatial, and hierarchical relationships simultaneously. By adding visual dimensions to the data presentation, the system enables comprehensive system understanding without requiring manual tracing through complex architectural layers.
Data Source
AI summary
An environmental visualization system is provided for visualization of a computing architecture. The environmental visualization system may include a front-end system configured to receive signals communicated and carrying messages between source and destination network nodes separate and distinct from the system in a communication network composed of a plurality of network nodes within an environment of a user, interpret the messages to identify the source and destination network nodes, and generate data input for the signals that indicates the source and destination network nodes. The environmental visualization system may also include a computing architecture system configured to generate from the data input, a multidimensional layout that depicts the communication network, including the source and destination network nodes and signals communicated therebetween, in which the front-end system may be configured to output the multidimensional layout for display by a display device.