Sensor Data Fusion Using Entropy-Based Validation and Linking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing sensor data fusion systems fail to create actionable data by correlating and fusing heterogeneous, partially heterogeneous, or homogeneous data sources in real-time, leading to excessive computational and storage requirements, and lack of sensor accuracy assurance.
Innovation Solution
A system and method for sensor data fusion that includes a computer processor with curation, link, fusion, inference, and validation engines to curate and mathematically link sensor data before storage, creating a unique dataset with enhanced accuracy and reduced computational and storage demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data from multiple sources is fused without mathematical validation, then data fusion can be performed quickly, but the accuracy and reliability of the fused data cannot be ensured
Solution Approach 1:
The system performs preliminary mathematical validation and correlation analysis on sensor data before fusing it with other data sources. By pre-validating the mathematical relationships and accuracy of individual sensor outputs, the system ensures that only reliable data is fused, maintaining high measurement precision while avoiding the need for complex post-fusion validation processes.
Solution Approach 2:
The patent introduces mathematical validation mechanisms as intermediary processes between raw sensor data and fused output. These validation layers act as mediators that assess the reliability and accuracy of sensor data through mathematical correlations, allowing the system to maintain simplicity in the overall architecture while ensuring high accuracy through structured intermediate verification steps.
2Loss of information
If all sensor data is stored before processing, then complete data is available for analysis, but storage requirements become excessive
Solution Approach 1:
The system extracts and processes only the essential and validated portions of sensor data rather than storing complete raw datasets. By identifying and retaining only the critical information that passes mathematical validation, the system maintains data completeness for analysis while dramatically reducing the quantity of data that needs to be stored.
Solution Approach 2:
The patent performs preliminary processing and validation of sensor data before storage, filtering out redundant or invalid information in advance. This preliminary action ensures that only necessary, validated data is retained for future analysis, preventing information loss while minimizing storage requirements by eliminating unnecessary data upfront.
3Productivity
If heterogeneous sensor data is fused without mathematical linking, then fusion can be performed rapidly, but the correlation and reliability of fused data cannot be validated
Solution Approach 1:
The system performs preliminary mathematical linking and correlation validation on heterogeneous sensor data before the fusion process. By pre-establishing the mathematical relationships and reliability metrics of different sensor sources, the system can quickly fuse validated data while maintaining high reliability, as the validation work is completed in advance rather than during the fusion operation itself.
Data Source
AI summary
Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.