Anonymized Vehicle Visit Tendency Analysis
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Solution Overview
Problem
Current technologies lack the capability to effectively acquire and analyze information indicating visit spot tendencies for different vehicle types without identifying individual users or vehicles, limiting the ability to provide targeted services based on user preferences and vehicle attributes.
Innovation Solution
An information processing apparatus and method that acquires and processes vehicle information from various sources, including in-vehicle devices, cameras, and social networking services, to determine visit spot tendencies for each vehicle classification by totaling records based on attributes such as vehicle type, body style, and spot characteristics, without identifying individual users or vehicles, allowing for flexible data extraction and output formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vehicle information is collected to analyze visit spot tendencies, then the ability to provide targeted services is improved, but user privacy protection is compromised
Solution Approach 1:
The patent extracts and removes personally identifiable information (vehicle identification numbers, user names, contact information) from the collected data before analysis. Only anonymized attributes such as vehicle type, body style, and visit spot characteristics are retained, enabling service personalization without compromising user privacy.
Solution Approach 2:
The patent introduces an intermediary processing layer that anonymizes data between collection and analysis. This intermediary step transforms identifiable vehicle information into categorized attributes (e.g., converting specific vehicle models into vehicle type categories), allowing tendency analysis while protecting individual user identity.
2Measurement precision
If detailed vehicle information is collected from multiple sources, then the accuracy of visit spot tendency analysis is improved, but the complexity of data processing increases
Solution Approach 1:
The patent segments the data processing into distinct modules: data collection from multiple sources (in-vehicle devices, cameras, SNS), data cleaning and validation, anonymization processing, attribute extraction, and tendency analysis. Each module handles specific tasks independently, reducing overall system complexity while maintaining high analysis accuracy.
Solution Approach 2:
The patent transforms raw vehicle information into standardized parameters and categories (vehicle type, body style, visit spot characteristics) with defined value ranges. This parameter standardization enables accurate cross-source data integration and simplifies subsequent analysis operations.
Data Source
AI summary
The present disclosure includes an object to acquire information indicating a tendency on a visit spot for each vehicle sort.The present disclosure provides an information processing apparatus including a controller configured to execute: acquiring first information about a plurality of vehicles, the first information including vehicle information about a vehicle, the first information not being capable of identifying an individual user or an individual vehicle but reflecting at least part of attributes or preferences of a user associated with the vehicle, and spot information about a visit spot of the vehicle; and acquiring tendency information indicating a tendency on the visit spot of the vehicle for each vehicle classification based on the vehicle information, from the first information about the plurality of vehicles.