Trend Dynamic Sensor Imaging for Multi-Source Data Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data visualization techniques fail to effectively analyze large quantities of data from multiple sources with different scales in real-time, making it difficult for users to discern trends and anomalies in physical processes like semiconductor manufacturing.
Innovation Solution
A trend dynamic sensor imaging (DSI) system that preprocesses data to a common scale and displays it using a color gradient on a grid, allowing users to visualize and detect anomalies across multiple data sets from various sources, such as sensors in semiconductor manufacturing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from multiple sources with different scales are visualized using traditional techniques, then data completeness is improved, but data visualization effectiveness deteriorates
Solution Approach 1:
The patent segments the visualization process into distinct stages: data reception from multiple sources, preprocessing to normalize scales, and display on a grid interface. This segmentation allows each stage to handle specific tasks efficiently, maintaining data completeness while improving visualization effectiveness through systematic processing.
Solution Approach 2:
The patent transforms multi-dimensional data from different scales into a unified two-dimensional grid display with color-coded values. By mapping diverse data sources onto a common visual dimension (the grid), the system enables effective comparison and analysis while preserving all data points.
2Loss of information
If multiple data sets are displayed in a single view, then information density is improved, but detection precision deteriorates
Solution Approach 1:
The patent applies local quality by using color gradients to encode data values within each grid cell. Different color intensities represent different data magnitudes, allowing users to quickly identify anomalies (outliers) through visual contrast while maintaining high information density across the entire display.
Solution Approach 2:
The system uses color changes to represent data variations across multiple sources. By mapping data values to color intensities or hues, the patent enables simultaneous display of numerous data sets with preserved detection precision, as color provides an intuitive visual cue for identifying deviations from normal ranges.
3Adaptability or versatility
If data preprocessing is performed to normalize scales, then data comparability is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary normalization of data scales during the preprocessing stage before display. By standardizing data from multiple sources upfront, the system enables direct comparability across all data sets without requiring real-time calculations, thus improving data comparability while minimizing processing time delays during actual analysis.
Data Source
AI summary
A method and system for trend dynamic sensor imaging is described herein. The method includes receiving, from a plurality of sensors, a plurality of data sets, and comparing the plurality of data sets to reference data to generate, for each of the plurality of sensors, one or more corresponding comparison values. The method further includes transforming, using the one or more corresponding comparison values for each of the plurality of sensors, the plurality of data sets to have a common scale regardless of corresponding physical processes, and causing anomalies in one or more physical processes to be displayed via a client device by plotting the transformed plurality of data sets according to the common scale.