Automatic Visualization Configuration for Industrial Data Attributes
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Solution Overview
Problem
In industrial control systems, it is challenging to efficiently visualize and display data with varying attributes in a manner that is both user-friendly and adaptable to different devices and environments, as existing systems often lack the ability to dynamically modify data appearance based on attributes such as source, channels, and user preferences.
Innovation Solution
A system comprising an input component that receives data, an analyzer that determines visualization attributes, and a configuration method that formats and displays data based on these attributes, using a common data object shell definition and tiered levels of human machine interface (HMI) visualization attributes, allowing for automatic visualization configuration and display in industrial environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data is displayed with fixed formatting rules, then system complexity is reduced, but adaptability to different devices and environments deteriorates
Solution Approach 1:
The system dynamically adjusts data formatting and visualization based on device characteristics, user preferences, and environmental context. Instead of fixed rules, the system modifies display properties in real-time to optimize for different screens, resolutions, and user needs, resolving the contradiction between system simplicity and adaptability.
Solution Approach 2:
The system changes multiple parameters including font size, color schemes, layout configurations, and data density based on the target device and user preferences. By adjusting these parameters dynamically, the system maintains adaptability across diverse environments without requiring completely different formatting rule sets for each device type.
2Ease of operation
If automatic visualization configuration is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system performs self-configuration by automatically analyzing device characteristics, user preferences, and data attributes to generate appropriate visualization settings without user intervention. This self-service capability improves ease of operation while the automation intelligence is contained within the system, minimizing the perceived complexity for users.
Solution Approach 2:
The system pre-establishes formatting rules and visualization templates based on common device types and user preferences. When a new device or context is encountered, the system matches it against pre-configured templates and makes automatic adjustments, reducing the complexity of real-time decision-making while maintaining adaptability.
3Adaptability or versatility
If data is formatted based on multiple attributes, then adaptability is improved, but processing time increases
Solution Approach 1:
The system pre-processes and caches formatting decisions based on common attribute combinations encountered in different devices and contexts. By preparing these formatting rules in advance and storing them for reuse, the system reduces the processing time required when encountering similar data visualization scenarios, while still maintaining the ability to handle multiple attributes and adapt to new situations.
Data Source
AI summary
The invention provides systems and methods that format data based at least in part upon attributes associated with such data. Data attributes can be related to a number of various factors in a data driven architecture such as the source of the data, the data subscriber and the path employed to convey the data from the source to the subscriber. In addition, data formatting can employ various levels of complexity and data presentation can vary dependent on various factors such as display device and user to which the data is presented. For example, the format of the data can refer to the size, shape, color, and graphics associated therewith.