Automotive Data Feature Bundling for Connected Vehicle Consent Management
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Solution Overview
Problem
Managing access to automotive data sources for connected vehicles is challenging due to unclear sensor requirements and consent management issues, making it difficult to match data sources with consumers effectively.
Innovation Solution
Implementing data features bundling, where a list of attributes is grouped into subsets based on specific use cases, allowing clients to receive tailored bundles of data features that meet their business requirements, simplifying consent processes and improving data utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sensor-by-sensor data access approach is used, then data consumers can access individual sensors, but it becomes difficult to manage consent requirements and match data sources with consumers effectively
Solution Approach 1:
The patent combines multiple individual sensor data features into bundled data sets that correspond to specific use cases. Instead of managing consent and access for each sensor separately, the system merges related sensors into predefined bundles (e.g., location bundle, vehicle status bundle), thereby reducing consent management complexity while maintaining data accessibility.
Solution Approach 2:
The patent segments the overall data catalog into organized bundles based on use cases and data types. Each bundle contains specific data features grouped by their functional relationship, making it easier for consumers to select and manage access to relevant data sets rather than individual sensors.
2Adaptability or versatility
If individual sensor access is provided, then consumers can select specific sensors, but it is difficult to determine what access is needed and in what format to optimize data use
Solution Approach 1:
The system performs preliminary organization of data features into use case-specific bundles before consumers access them. Each bundle is pre-configured with the appropriate data features and formats needed for specific applications (e.g., insurance, navigation, fleet management), eliminating the need for consumers to determine sensor requirements and formats independently.
Solution Approach 2:
The bundled data sets are designed to be universally applicable to multiple consumers and use cases. Each bundle contains data features that can serve various purposes (e.g., location data can be used for navigation, tracking, or insurance), providing adaptability while maintaining clear format specifications.
3Productivity
If sensor-by-sensor matching is implemented, then precise data access is possible, but it becomes difficult to enforce policies and bill consumers per sensor
Solution Approach 1:
The system merges billing and policy enforcement operations from the sensor level to the bundle level. Instead of tracking and billing for each individual sensor access, the system manages policies and billing for entire data bundles, significantly improving matching efficiency while reducing operational complexity.
4Quantity of substance
If comprehensive data access is provided, then consumers can access all available data, but it becomes difficult to manage consent requirements for various data sources
Solution Approach 1:
The system segments comprehensive data access into organized bundles based on use cases and data types. Each bundle represents a logical group of data features with associated consent requirements, allowing consumers to access comprehensive data while managing consent at the bundle level rather than for each individual data source.
Data Source
AI summary
A system and a method for bundling data features relating to connected vehicles, in accordance with respective use cases are provided herein. The method may include the following steps: obtaining a plurality of data features relating to connected vehicles originated from a plurality of data sources; maintaining a use cases database, holding a plurality of use cases, each affiliated with a respective blend of said data features; receiving one or more requests from clients for data features, each request associated with respective business requirements; and providing said clients with a respective one of said bundles according to the respective business requirements and responsive to the requests and based on the use cases database.