Multi-Sensor Data Recording for Reproducible Storage Reduction
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Solution Overview
Problem
Existing data recording systems face challenges in efficiently managing and reducing the volume of measurement data from multiple sensors while ensuring that critical data for reproducing target sensor measurements is not inadvertently deleted, leading to potential loss of predictive capabilities.
Innovation Solution
A data recording apparatus and method that acquires measurement data from multiple sensors, predicts data using measurement data from other sensors, decides a set of sensors capable of reproducing the data within a predetermined allowable range, and selectively records data from included sensors, prioritizing data that ensures reproducibility and reducing unnecessary data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If measurement data from all sensors is recorded, then data completeness is improved, but storage capacity requirements increase
Solution Approach 1:
The patent extracts and removes redundant measurement data from the recording system. By using prediction models to identify which sensor data can be accurately reconstructed from other sensors, the system selectively excludes redundant data from storage while maintaining the ability to reproduce complete measurement sets within allowable error ranges.
Solution Approach 2:
The patent changes the parameter of data representation by storing prediction model parameters and metadata instead of all raw sensor data. This allows the system to reproduce measurement data through computational transformation of stored parameters rather than storing every original measurement, significantly reducing storage requirements while maintaining data utility.
2Quantity of substance
If measurement data from fewer sensors is recorded, then storage capacity is reduced, but data reproducibility deteriorates
Solution Approach 1:
The patent performs preliminary analysis to identify redundant sensors and establishes prediction models before actual data recording. By pre-determining which sensors can be excluded based on their reconstructability from other sensors, the system ensures data reproducibility is maintained while minimizing storage requirements from the outset.
Solution Approach 2:
The patent implements feedback mechanisms where prediction accuracy is continuously evaluated against actual measurement data. This feedback loop allows the system to adjust which sensors are excluded from recording, ensuring that data reproducibility remains within allowable error ranges while optimizing storage capacity utilization.
3Productivity
If redundant measurement data is deleted, then storage efficiency is improved, but predictive capability is lost
Solution Approach 1:
The patent creates computational copies of redundant sensor data through prediction models. Instead of storing actual redundant measurements, the system stores the capability to generate these measurements computationally from non-redundant sensor data, preserving predictive capability while improving storage efficiency.
Solution Approach 2:
The patent makes the stored prediction models multi-functional, enabling them to serve both as data compression mechanisms and as predictive tools. The same models that enable storage efficiency by identifying redundant data also provide predictive capability for estimating missing or future measurements, eliminating the trade-off between storage efficiency and predictive capability.
Data Source
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AI summary
Provided is a data recording apparatus including: a data acquisition unit configured to acquire measurement data obtained by measuring a measurement target from a plurality of sensors; a data prediction unit configured to predict measurement data acquired from at least any one sensor of the plurality of sensors by using measurement data acquired from another sensor among the plurality of sensors; a decision unit configured to decide a set of sensors capable of reproducing the measurement data acquired from the plurality of sensors within a predetermined allowable range by using the acquired measurement data and the predicted measurement data; a data selection unit configured to select measurement data acquired from a sensor included in the set in preference to measurement data acquired from a sensor not included in the set; and a data recording unit configured to record the selected measurement data.