Context-Based Data Prioritization for Industrial Automation
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Solution Overview
Problem
Existing systems fail to effectively present data to users in industrial environments, often overwhelming or hindering them due to inappropriate amounts or formats of data, which can obstruct task performance and relevance.
Innovation Solution
A system and method that categorize sensory datasets from industrial automation systems, determine context information, and prioritize data presentation based on user inputs and environmental conditions, using extended reality devices to provide output data in intuitive and relevant formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all sensory datasets are presented to the user, then complete information is provided, but the user experiences cognitive overload and task performance deteriorates
Solution Approach 1:
The system segments sensory datasets into multiple categories (e.g., visual, auditory, haptic, operational parameters) and processes each category separately based on its priority level. This segmentation allows the system to manage information complexity by dividing the complete dataset into manageable, prioritized groups that can be selectively presented to the user without overwhelming them.
Solution Approach 2:
The system applies local quality by providing different levels of information detail to different user contexts. High-priority categories receive detailed presentation while lower-priority categories receive summarized or omitted information, tailored to the specific task and environmental conditions. This ensures each user receives appropriately filtered information based on their immediate needs.
2Loss of information
If data is presented in detailed formats, then information completeness is improved, but user comprehension and task efficiency deteriorate
Solution Approach 1:
The system implements partial action by selectively presenting only the necessary level of data detail required for each task context. Rather than providing complete detailed information for all categories, the system provides partial information for lower-priority categories while maintaining full detail for high-priority categories, optimizing the balance between information completeness and task efficiency.
3Loss of information
If context-based prioritization is implemented, then relevant information is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary action by pre-establishing priority frameworks and context models before actual data presentation occurs. Category priorities, contextual parameters, and presentation formats are pre-configured and stored, allowing the system to quickly retrieve and apply appropriate filtering rules during operation without requiring complex real-time decision-making, thus managing complexity effectively.
Data Source
AI summary
A tangible, non-transitory, computer-readable medium includes instructions. The instructions, when executed by processing circuitry, are configured to cause the processing circuitry to receive a plurality of sensory datasets associated with an industrial automation system from a plurality of sensors, categorize each sensory dataset of the plurality of sensory datasets into one or more sensory dataset categories of a plurality of sensory dataset categories, determine context information associated with the plurality of sensory datasets, the context information being representative of an environmental condition associated with an extended reality device, the industrial automation system, or both, determine a priority of each sensor dataset category of the plurality of sensory dataset categories based on the context information, determine output representative data to be presented by the extended reality device based on the plurality of sensory datasets and the priority, and instruct the extended reality device to present the output representative data.