Sensor Data Fusion with Pre-Storage Curation and Linking

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

VSEngineering Contradiction Analysis

1Loss of information

If sensor data is stored and processed after collection, then data availability is improved, but computational requirements and storage needs increase excessively

Engineering Contradiction:

Improvedata availabilityVSAvoidcomputational requirements

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system performs data curation, mathematical linking, and fusion operations before storing sensor data. The curation engine prepares data by categorizing it into properties and sub-properties, the link engine establishes mathematical relationships between data points, and the fusion engine combines correlated data points into new datasets. This preliminary processing ensures data is ready for immediate use when needed, eliminating the need for excessive post-collection computational resources and storage capacity.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If heterogeneous sensor data sources are fused without pre-processing, then data comprehensiveness is improved, but processing complexity and energy consumption increase

Engineering Contradiction:

Improvedata comprehensivenessVSAvoidenergy consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The system performs data curation, mathematical linking, and fusion operations before storing sensor data. The curation engine prepares data by categorizing it into properties and sub-properties, the link engine establishes mathematical relationships between data points, and the fusion engine combines correlated data points into new datasets. This preliminary processing ensures data is ready for immediate use when needed, eliminating the need for excessive post-collection computational resources and storage capacity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system transforms heterogeneous sensor data into a standardized format with defined properties and sub-properties. By changing the parameter representation of diverse sensor inputs into a common structured framework, the system enables efficient processing and fusion of heterogeneous data sources while reducing energy consumption during operation.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If all sensor data is stored for future analysis, then data accessibility is improved, but storage requirements increase

Engineering Contradiction:

Improvedata accessibilityVSAvoidstorage requirements

Core Design Contradiction:

Loss of informationVSQuantity of substance

Solution Approach 1:

The system performs data curation, mathematical linking, and fusion operations before storing sensor data. The curation engine prepares data by categorizing it into properties and sub-properties, the link engine establishes mathematical relationships between data points, and the fusion engine combines correlated data points into new datasets. This preliminary processing ensures data is ready for immediate use when needed, eliminating the need for excessive post-collection computational resources and storage capacity.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12541575B2Systems and methods of sensor data fusion

Publication Date: 2026.02.03 DIGITAL GLOBAL SYSTEMS INC

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.