Adaptive Sensor Pattern Recognition for Industrial Data Collection
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Solution Overview
Problem
Industrial environments face challenges in data collection and utilization due to complex sensor configurations, variable network conditions, and the need for real-time data management, which limits the effectiveness of monitoring and optimization in heavy industrial settings.
Innovation Solution
The implementation of a system that includes continuous ultrasonic monitoring, on-device sensor fusion, self-organizing data marketplaces, and AI training based on industry-specific feedback, along with augmented reality and virtual reality interfaces for improved data collection and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous monitoring of multiple sensor parameters is implemented, then detection capability and reliability are improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the data collection process by implementing adaptive sampling rates for different sensor parameters based on their importance and variability. Critical parameters are sampled continuously at high rates, while less critical parameters use lower sampling rates, reducing overall system complexity while maintaining detection reliability.
Solution Approach 2:
The system dynamically adjusts sensor sampling rates and activation states based on real-time process conditions, equipment state, and detected anomalies. This dynamic configuration allows the system to maintain high reliability during critical operations while reducing complexity during normal operations.
2Productivity
If real-time data processing and analysis are implemented, then responsiveness and productivity are improved, but computational resource requirements and energy consumption increase
Solution Approach 1:
The patent implements partial real-time processing by prioritizing analysis of critical parameters and anomaly detection over comprehensive analysis of all sensor data. The system processes only the most relevant data subsets in real-time, while less critical data is processed asynchronously or in batches, reducing computational energy consumption while maintaining productivity for critical functions.
3Adaptability or versatility
If adaptive sensor configuration is implemented, then adaptability to changing conditions is improved, but system complexity and control difficulty increase
Solution Approach 1:
The system uses feedback mechanisms where sensor data quality, process conditions, and equipment state information continuously inform adaptive configuration decisions. This feedback loop enables the system to automatically adjust sensor activation and sampling rates in response to changing conditions, improving adaptability while keeping control complexity manageable through rule-based decision logic.
4Loss of information
If comprehensive sensor data collection is implemented, then information completeness is improved, but data management burden and storage requirements increase
Solution Approach 1:
The patent extracts and prioritizes only the most relevant sensor data for real-time analysis and decision-making. By filtering out redundant or low-value data streams and focusing computational resources on critical parameters, the system maintains information completeness for essential functions while significantly reducing the data management burden and storage requirements.
Data Source
AI summary
The present disclosure describes a system for data collection in an industrial environment. The system can include an industrial system comprising a plurality of components each operatively coupled to a sensor, a sensor communication circuit to interpret the sensor data values in response to a sensed parameter group, a pattern recognition circuit to determine a recognized pattern value in response to a least a portion of the sensor data values, and a sensor learning circuit to update the sensed parameter group in response to the recognized pattern value, wherein the sensor communication circuit also adjusts the interpreting of the plurality of sensor data values in response to the updated sensed parameter group.