Sensor Data Fusion Using Curation and Linking Before Storage
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Solution Overview
Problem
Existing sensor data fusion systems fail to create actionable data by correlating and fusing sensor data before storage, leading to excessive computational and storage requirements, and lack real-time data processing capabilities, especially for heterogeneous and partially heterogeneous data sources.
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, creating a unique dataset in near real-time, reducing computational and storage demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensor data is stored and processed after collection, then data completeness is improved, but computational requirements and storage demands increase excessively
Solution Approach 1:
The patent applies preliminary action by performing data curation, mathematical linking, and fusion operations on sensor data immediately upon receipt, before the data is stored. The curation engine curates incoming sensor data, the link engine mathematically links curated data, and the fusion engine fuses linked data to create fused sensor data - all before storage occurs. This eliminates the need to process and analyze entire raw datasets later, significantly reducing computational requirements while maintaining data completeness.
2Loss of information
If all sensor data is stored for later analysis, then data availability is improved, but storage requirements increase excessively
Solution Approach 1:
The system performs preliminary fusion of sensor data before storage, transforming multiple sources of raw sensor data into a single dataset of fused sensor data. This consolidation dramatically reduces the volume of data that needs to be stored while preserving all essential information. The fused sensor data contains correlated and integrated information from multiple sensor sources, making the stored data more valuable and compact simultaneously.
3Speed
If sensor data fusion is performed in real-time, then processing speed is improved, but computational complexity increases
Solution Approach 1:
The patent segments the sensor data fusion process into distinct functional modules: a curation engine that curates incoming sensor data, a link engine that mathematically links curated data, and a fusion engine that fuses linked data. This segmentation allows each module to perform its specific function efficiently and independently, reducing overall computational complexity while enabling real-time processing. The modular architecture makes the complex fusion task manageable and scalable.
4Adaptability or versatility
If heterogeneous sensor data is fused, then data versatility is improved, but processing difficulty increases
Solution Approach 1:
The patent creates a universal processing framework that handles heterogeneous sensor data through standardized operations. The curation engine curates data from diverse sensor sources using common criteria, the link engine applies mathematical linking operations that work across different data types, and the fusion engine fuses linked data regardless of origin. This universal approach enables the system to process heterogeneous sensor data (images, audio, text, etc.) with the same machinery, improving versatility while managing processing difficulty through standardization.
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.