Streamed Sensor Data Processing With Dynamic Mode Switching
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Solution Overview
Problem
Current control systems for industrial automation processes are inefficient in processing sensor data in real-time, leading to delayed monitoring and control actions, as they rely on batch processing that requires significant computational resources and memory.
Innovation Solution
Implementing smart sensor devices with processing capabilities that employ learning algorithms to identify operational states and anomalies, allowing them to toggle between different operational modes for efficient data processing, reducing the need for external processing and enhancing real-time monitoring and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If batch processing is used for sensor data, then comprehensive analysis can be performed, but processing time and resource consumption increase significantly
Solution Approach 1:
The patent segments sensor data processing into two distinct modes: real-time processing for immediate anomaly detection and batch processing for comprehensive analysis. The controller dynamically switches between these modes based on operational conditions, allowing the system to perform quick assessments when needed while maintaining the option for detailed analysis during batch operations.
Solution Approach 2:
The system implements dynamic processing mode switching where the controller can transition between real-time and batch processing modes based on operational requirements. This dynamic adaptation allows the system to optimize processing speed during critical periods while maintaining analytical thoroughness when time permits.
2Measurement precision
If batch processing is used for sensor data, then comprehensive analysis can be performed, but computational resource requirements increase
Solution Approach 1:
The patent segments processing tasks by separating real-time monitoring functions from comprehensive batch analysis. The controller handles real-time processing with lower computational demands, while batch processing is scheduled during periods when resource availability is higher, thus optimizing overall resource utilization.
Solution Approach 2:
The system employs periodic batch processing where comprehensive analysis is performed at scheduled intervals rather than continuously. This periodic approach reduces peak computational resource requirements while still providing thorough analysis capabilities when needed.
3Speed
If real-time processing is implemented, then faster anomaly detection is achieved, but system complexity increases
Solution Approach 1:
The patent introduces a controller as an intermediary that manages processing mode transitions between real-time and batch modes. This intermediary component coordinates the switching logic and ensures smooth transitions, preventing the need for complex dual-processing architectures while maintaining real-time capabilities.
4Speed
If more processing power is allocated to sensor data analysis, then faster monitoring is achieved, but sensor device lifespan decreases
Solution Approach 1:
The system dynamically adjusts processing intensity based on operational needs. During normal operation, real-time processing operates at lower intensity to conserve sensor resources, while batch processing handles comprehensive analysis. This dynamic adjustment extends sensor lifespan while maintaining necessary monitoring speeds.
Solution Approach 2:
The patent applies partial processing in real-time mode, performing only essential anomaly detection functions at reduced processing intensity. Full comprehensive analysis is reserved for scheduled batch processing, allowing the system to maintain monitoring speed for critical functions while preserving sensor device lifespan through reduced overall processing load.
Data Source
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AI summary
A system may include sensor device comprising a sensor configured to measure sensor data indicating an operational parameter of industrial automation equipment associated with an industrial automation process. The system may also include communication circuitry configured to transmit the sensor data Additionally, the system includes a processor configured to receive the sensor data. Further, the system includes a non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause the processor to perform operations including identifying an operational state of the industrial automation equipment based on the sensor data. The operations may also include determining a discrepancy between the sensor data and the operational state. Further, the operations may include modifying an operation of the processor from a first operational mode to a second operational mode of a plurality of operational based on the comparison.