In-Vehicle Data Routing by Occupant Profile and Data Type
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Solution Overview
Problem
Current transportation systems lack efficient methods for data management and distribution within vehicles, particularly in determining and prioritizing data to be forwarded to occupants based on their type and characteristics, which can lead to suboptimal user experiences and service delivery.
Innovation Solution
A method and system where a vehicle determines data to be forwarded to associated devices based on the type of data and characteristics of occupants, using a processor and memory to prioritize and distribute data portions accordingly, leveraging blockchain technology for secure and decentralized data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is forwarded to all devices without selection, then all devices receive data, but data distribution efficiency deteriorates and unnecessary data consumption increases
Solution Approach 1:
The patent segments data into different types (e.g., safety-critical data, entertainment data, update data) and distributes different segments to different devices based on their characteristics and needs. This selective segmentation improves distribution efficiency by avoiding unnecessary data transmission to each device.
Solution Approach 2:
The patent applies local quality by tailoring data distribution to specific device characteristics and occupant profiles. Each device receives data with quality and type optimized for its specific function and the occupant's preferences, reducing overall data consumption while maintaining effectiveness.
2Ease of operation
If data distribution is customized based on occupant characteristics, then user experience improves, but system complexity increases
Solution Approach 1:
The system implements self-service by automatically analyzing occupant characteristics, device capabilities, and data types to make distribution decisions without manual intervention. This automation improves user experience while managing complexity through algorithmic decision-making rather than manual configuration.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting data distribution parameters (such as data type, volume, timing) based on occupant characteristics and device states. This allows customized user experience through parameter optimization rather than structural complexity.
3Loss of information
If all data types are transmitted to all devices, then data availability is maximized, but data security and privacy protection deteriorate
Solution Approach 1:
The patent segments data by sensitivity and type, ensuring that only necessary data segments are transmitted to specific devices. This segmentation maintains data availability for authorized devices while reducing privacy risks by limiting exposure of sensitive information.
Solution Approach 2:
The system introduces an intermediary layer (the transport's data management system) that mediates between data sources and devices. This intermediary enforces security policies, filters data based on device authorization, and protects privacy while maintaining data availability for legitimate recipients.
Data Source
AI summary
An example operation includes one or more of determining, by a transport, data to be forwarded to one or more devices associated with each of one or more occupants based on a type of the data and characteristics of the one or more occupants, and forwarding, by the transport, one or more portions of the data based on the determining.