Digital Twin Data Collection Using Virtual Sensing and Sensor Tuning
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Solution Overview
Problem
Existing digital twin systems face challenges due to limitations in physical sensors, such as power and lifetime constraints, sampling frequency, precision, signal-to-noise ratio, and mismatch with the measured object, leading to unreliable operations and inability to meet dynamic data input requirements.
Innovation Solution
A system and method that includes a virtual sensing module to generate supplementary data and adjust physical sensor settings dynamically to match the input requirements of the digital model, using a processor arrangement to determine necessary input information and optimize data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical sensors operate at maximum capacity to provide sufficient data for digital twin, then measurement precision is improved, but sensor lifespan deteriorates and reliability worsens due to maximum capacity operation and malfunctions
Solution Approach 1:
The patent creates virtual copies of physical sensor data through digital twins. The virtual sensor module generates synthetic sensor readings that replicate the behavior and output of physical sensors, allowing the digital twin to operate with virtual data copies rather than continuously demanding maximum capacity from physical sensors, thereby reducing wear and improving reliability
Solution Approach 2:
The system dynamically adjusts sampling rates and data collection parameters based on the digital twin's current needs. Instead of continuously operating at maximum capacity, physical sensors adjust their operational parameters (sampling frequency, data resolution) to match the actual requirements of the digital twin model, reducing unnecessary stress on sensors while maintaining required precision
2Productivity
If physical sensors increase sampling rate to provide sufficient data for real-time digital twin operations, then productivity is improved, but use of energy worsens and sensor lifespan deteriorates
Solution Approach 1:
The system implements dynamic adjustment of sensor sampling rates based on the digital twin's real-time requirements. The virtual sensor module and configuration system continuously monitor what data the digital twin needs and adjust physical sensor sampling rates accordingly, increasing productivity only when necessary while minimizing energy consumption during periods when the digital twin can operate with lower data rates or virtual data
Solution Approach 2:
The patent dynamically changes operational parameters including sampling rates, resolution, and data collection frequency to match the digital twin's current needs. This allows the system to achieve high productivity when required while consuming minimal energy during normal operation, and extends sensor lifespan by avoiding continuous high-stress operation
3Reliability
If physical sensors continuously monitor patient data for real-time digital twin updates, then reliability of digital twin operations is improved, but sensor discomfort worsens and sensor lifespan deteriorates
Solution Approach 1:
The virtual sensor module generates virtual copies of patient sensor data that can be used to update the digital twin without requiring continuous physical sensor attachment. This allows the digital twin to maintain reliable operations using virtual data representations, reducing the need for continuous physical sensor contact with the patient and thereby reducing discomfort
Solution Approach 2:
Instead of continuous monitoring, the system implements periodic data collection where physical sensors activate only when needed to update the digital twin or virtual sensor module. This intermittent operation maintains digital twin reliability by providing periodic refreshes of patient data while significantly reducing sensor-patient contact time and associated discomfort
4Measurement precision
If digital twin requires specific input data types that physical sensors cannot provide, then adaptability worsens, but measurement precision is compromised
Solution Approach 1:
The virtual sensor module creates virtual data copies and transformations that convert physical sensor readings into the specific data types required by the digital twin. This virtual data transformation layer enables the system to provide precise input data in the required formats without being limited by the native output types of physical sensors, thereby maintaining measurement precision while improving adaptability
Solution Approach 2:
The virtual sensor module acts as an intermediary between physical sensors and the digital twin. It receives data from physical sensors, processes and transforms it into the required data types, and provides it to the digital twin. This intermediary layer resolves the incompatibility between physical sensor output types and digital twin input requirements while maintaining data precision
Data Source
AI summary
A system (10) for configuring data collection for provision to a digital twin for generating a desired set of output information (e.g. physiological or anatomical parameter estimations) from the digital twin. The system is configured to detect available sources (56) of physical sensor data (58) pertaining to a patient, and to compare these with determined input data requirements of a digital twin (32) of the patient for computing a particular defined set of required output information. Depending on the result, a virtual sensing module (28) can be used to generate supplementary ‘virtual’ sensor data to compensate for any insufficiencies in the available physical sensor data or augment the physical sensor data, and the system can re-configure operating settings of the available physical sensors (56) to optimally meet the input data requirements of the digital model.