Vehicle Proposal Server Using User Attributes and Environmental Data
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Solution Overview
Problem
Existing vehicle proposal systems fail to precisely match the needs of users, lacking integration of user attributes and environmental information for tailored suggestions.
Innovation Solution
A server apparatus that communicates with in-vehicle systems to derive proposals based on user attributes and environmental data, using scenario information to enhance proposal relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a server apparatus integrates user attribute information and environmental information to derive personalized proposals, then the precision of matching user needs is improved, but the complexity of the system increases
Solution Approach 1:
The system segments information processing into distinct modules: user attribute information management, environmental information acquisition, scenario information storage, and proposal derivation. Each module handles specific data types and functions independently, reducing overall system complexity while enabling precise matching through integrated processing.
Solution Approach 2:
The server apparatus acts as an intermediary between the in-vehicle apparatus and the user, collecting and processing various information types (user attributes, environmental data, scenario information) to generate personalized proposals. This intermediary role centralizes complex processing logic in the server, simplifying the in-vehicle apparatus while maintaining high matching precision.
2Measurement precision
If the server apparatus stores and processes multiple types of information (user attributes, environmental data, scenario information), then the personalization accuracy of proposals is improved, but the information processing load increases
Solution Approach 1:
The system performs preliminary actions by pre-storing user attribute information, environmental information, and scenario information in the server apparatus before proposal generation. This pre-processing and organization of data reduces the computational load during actual proposal derivation, as the server can efficiently query and combine pre-structured information rather than processing raw data in real-time.
Data Source
AI summary
A server apparatus includes a communication interface configured to make communication, a memory configured to store scenario information defining a proposal scenario to a user of a vehicle, and a controller configured to derive, using the scenario information, a proposal to the user based on attribute information indicating an attribute of the user and environmental information, and cause an in-vehicle apparatus of the vehicle to output or execute the proposal by transmitting, to the in-vehicle apparatus, proposal information indicating the proposal.