Navigable Graph for Sensed Feature Signal Segments
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Solution Overview
Problem
Current computing systems lack efficient methods for organizing and navigating sensed features of physical entities over time, limiting their ability to perform complex queries and focus on relevant data in the physical world.
Innovation Solution
A computer-navigable graph is created to associate sensed features with signal segments, allowing for organized navigation and rapid rendering of evidence supporting these features, enabling sophisticated querying and computation on physical entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sensed features are organized in a navigable graph structure with associated signal segments, then query efficiency and data retrieval speed improve, but system complexity and data organization overhead increase
Solution Approach 1:
The patent segments sensed data into discrete signal segments and organizes them into a graph structure where each node represents a sensed feature and edges represent temporal or causal relationships. This segmentation allows efficient navigation to specific features and their supporting signal segments, improving query efficiency while managing complexity through structured organization.
Solution Approach 2:
The patent introduces a graphical navigation dimension to the data organization system, transforming linear data storage into a multi-dimensional graph structure. This allows navigation through sensed features and signal segments along multiple pathways (temporal, causal, hierarchical), significantly improving query efficiency by enabling direct access to relevant data without linear scanning.
2Loss of information
If all sensed signal segments are stored and retained for navigation, then complete evidence availability improves, but storage requirements and data management complexity increase
Solution Approach 1:
The patent extracts and retains only the essential signal segments that directly support sensed features, rather than storing complete raw signal data. By identifying and extracting the specific portions of signals that evidence particular sensed features, the system maintains complete evidence availability for navigation while significantly reducing overall data volume and storage requirements.
Solution Approach 2:
The patent applies different quality levels of data retention to different parts of the data structure. Signal segments associated with important or frequently queried sensed features are retained in higher detail, while less critical data may be summarized or stored at lower resolution. This local quality approach ensures evidence availability for critical features while managing total data volume.
Data Source
AI summary
The managing of sensed signals used to sense features of physical entities over time. A computer-navigable graph of sensed features is generated. For each sensed feature, a signal segment that was used to sense that feature is computer-associated with the sensed feature. Later, the graph of sensed features may be navigated to that features. The resulting signal segment(s) may then be access allowing for rendering of the signal evidence that resulted in the sensed feature. Accordingly, the principles described herein allow for sophisticated and organized navigation to sensed features of physical entities in the physical world, and allow for rapid rendering of the signals that evidence that sensed features.