Auto-id Data Visualization Using Hierarchical Nested Shapes
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Solution Overview
Problem
Auto-id systems generate vast amounts of data that are difficult to present meaningfully due to the large number of readers accessing identifiers with associated information that changes over time, leading to challenges in data visualization.
Innovation Solution
The method involves storing tag identifications and their associated locations and attributes, generating a hierarchy based on these, and displaying the data as nested shapes, with options for filtering, aggregation, and time-based visualization using a treemap format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If auto-id systems collect data from a large number of readers and identifiers, then data completeness and information granularity are improved, but data volume and complexity increase making visualization difficult
Solution Approach 1:
The patent segments the vast auto-id data into hierarchical groups and categories, organizing identifiers into nested structures that can be visually represented. This segmentation allows the system to manage and visualize large volumes of data by breaking them into manageable hierarchical units, resolving the contradiction between data completeness and visualization complexity
Solution Approach 2:
The patent introduces hierarchical dimensioning to the data structure, organizing auto-id information into multiple levels (e.g., parent categories, subcategories, individual identifiers). This dimensional transformation enables the visualization system to represent complex multi-dimensional data relationships in a structured manner, addressing the challenge of visualizing large data volumes
2Duration of action of stationary object
If data is collected over extended periods, then temporal coverage and historical analysis capability are improved, but data set size grows making processing and display more difficult
Solution Approach 1:
The patent applies preliminary aggregation and filtering operations to temporal data before visualization, organizing time-series auto-id data into hierarchical structures in advance. This preliminary processing reduces the computational burden during display while preserving the full temporal coverage, resolving the contradiction between extended time coverage and data set size
Solution Approach 2:
The patent implements dynamic data sampling and aggregation strategies that adapt to temporal patterns, allowing the system to maintain comprehensive temporal coverage while optimizing data representation. The hierarchical structure dynamically adjusts how historical data is presented, balancing completeness with manageable data volumes for display
Data Source
AI summary
Embodiments of the present invention improve visualization of information associated with auto-ids (tag IDs). In one embodiment, the present invention includes a method of processing auto-identification data comprising storing a plurality of tag identifications, storing a plurality of locations, wherein each tag identification is associated with at least one location, storing information having a plurality of attributes, wherein each tag identification is associated with one or more of said attributes, generating a hierarchy based on at least one location or at least one attribute associated with the plurality of tag identifications, and displaying at least a portion of the information and at least a portion of the locations associated with each tag identification as nested shapes corresponding to the hierarchy.