Vehicle Data Normalization Layer for Real-Time Multi-Source Integration

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Solution Overview

Problem

Existing vehicle data systems struggle to efficiently collect, process, and interpret disparate, non-standardized data from various sources for efficient vehicle operation and cost savings.

Innovation Solution

A method and system that combines disparate, non-standardized vehicle data into a central repository, normalizes it in real-time to pre-defined formats, and makes it available for consumption through APIs, utilizing an edge computing device for on-board processing and a communications manager for authorized applications.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If disparate non-standardized vehicle data is collected from multiple sources, then data quantity and coverage are improved, but data complexity and processing difficulty increase

Engineering Contradiction:

Improvedata quantityVSAvoiddata processing complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary component (data normalization service/API layer) that sits between the diverse data sources and the applications. This intermediary standardizes and harmonizes the disparate data formats, protocols, and structures from multiple vehicle sources into a unified format, reducing processing complexity while maintaining comprehensive data collection.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments the data processing function into distinct modular components: data collection modules for different sources, normalization modules for standardizing formats, and access modules for applications. This segmentation allows each component to handle specific data types independently, reducing overall system complexity while processing diverse data.

Inventive Principle:

Principle #1Segmentation

2Productivity

If real-time data normalization is implemented, then data usability and operational efficiency are improved, but processing time and computational resources increase

Engineering Contradiction:

Improveoperational efficiencyVSAvoidprocessing time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary data normalization and validation at the point of data ingestion, before the data enters the main processing pipeline. By pre-standardizing data formats and validating structures upfront, the system reduces the computational burden during real-time operations, improving efficiency without significant time loss.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The data normalization service operates autonomously, automatically detecting data types, selecting appropriate normalization rules, and transforming data without manual intervention. This self-service capability reduces the need for complex real-time processing decisions, improving operational efficiency while maintaining acceptable processing times.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If centralized data repository is created, then data accessibility and integration are improved, but system complexity and data security requirements increase

Engineering Contradiction:

Improvedata accessibilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The centralized repository is designed with universal access protocols and standardized data schemas that serve multiple applications and data sources. This multi-functional design allows different applications to access and utilize data in consistent formats, improving accessibility while reducing the need for application-specific data handling complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Quantity of substance

If multiple data sources are integrated, then data comprehensiveness is improved, but data heterogeneity and standardization challenges increase

Engineering Contradiction:

Improvedata comprehensivenessVSAvoiddata standardization quality

Core Design Contradiction:

Quantity of substanceVSLoss of information

Solution Approach 1:

The system applies parameter transformation rules that convert diverse data parameters from different sources into standardized parameters. By systematically changing data parameters (formats, units, structures) according to predefined rules, the system maintains comprehensive data from multiple sources while ensuring consistent standardization quality across all integrated data.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260040373A1Method And System For Generating Standardized Format Data From Disparate, Non-Standardized Vehicle Data

Publication Date: 2026.02.05 PLATFORM SCIENCE INC

AI summary

A system (1100) and method (1200) for generating vehicle data and surrounding contextual data into a standardized form by combining disparate, non-standardized onboard vehicle data into a central repository which is updated in real-time, that normalizes that data from non-standard to pre-defined formats, and then makes the pre-defined data available for consumption to authorized applications and users in raw form, or as outputs to a data product comprising data from multiple onboard signal generating sources through APIs. The system (1100) comprises an assigning authority engine (1105), a mobile device (110) for a vehicle (1000), a connected vehicle device (135) comprising on-vehicle data for the vehicle (1000), and an off vehicle source selected from a database (1125), a cloud source (1180), or a physical structure (1140).