Vehicle Data Collection for Geomarketing Incentives
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Solution Overview
Problem
Current systems for obtaining and utilizing vehicle-related data lack effective methods to incentivize users for sharing this data, limiting the development of location-based services and marketing applications.
Innovation Solution
A geomarketing system that equips vehicles with data collection devices to gather and transmit vehicle-related data, which is analyzed by a geomarketing server to determine location and mobility status, offering rewards to users for sharing this data, such as bonuses credited to a bonus account, and providing personalized marketing services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If vehicle data is collected and transmitted to servers for marketing analysis, then the quality and quantity of location-based services improve, but user privacy and data security risks increase
Solution Approach 1:
The patent extracts and processes only specific marketing-relevant data elements (location, vehicle type, usage patterns) while excluding sensitive personal information. The server receives and analyzes only the necessary data subsets required for geomarketing purposes, separating useful marketing intelligence from sensitive user data.
Solution Approach 2:
The patent applies different data processing qualities to different data types. Location data is processed with high precision for service accuracy, while personally identifiable information is either excluded or processed with lower quality/aggregate levels. This local differentiation optimizes marketing value while minimizing privacy exposure.
2Quantity of substance
If users are incentivized with bonuses for sharing vehicle data, then data collection volume increases, but system complexity and cost increase
Solution Approach 1:
The patent implements a feedback mechanism where users receive bonus rewards based on their data sharing participation. The system monitors data contribution levels and automatically credits bonuses to user accounts, creating a self-regulating incentive loop that encourages continued data sharing without requiring complex manual intervention.
Solution Approach 2:
The bonus system operates autonomously through automated tracking and crediting mechanisms. Users automatically receive rewards for their data contributions without requiring manual approval or complex administrative processes, reducing system operational complexity while maintaining incentive effectiveness.
3Adaptability or versatility
If comprehensive vehicle data is collected for marketing purposes, then service personalization improves, but data transmission and processing costs increase
Solution Approach 1:
The patent segments vehicle data into distinct categories (location information, vehicle characteristics, usage patterns, mobility status) and processes each segment according to its specific marketing utility. This segmentation allows selective transmission and processing of only the most valuable data elements, reducing overall data handling costs while maintaining personalization capability.
Solution Approach 2:
The patent collects and processes more data than strictly necessary for basic marketing, including detailed mobility status and temporal patterns. This excessive data collection enables highly personalized services and predictive analytics, with the added value outweighing the increased transmission and processing costs through improved targeting efficiency.
Data Source
AI summary
A mobility status of a vehicle is estimated based on received data from a data collection device associated with a vehicle. The received data includes a first data set collected at a first point of time and a second data set collected at a second point of time. The mobility status of the vehicle is estimated based on a difference between values or a status change of at least one common parameter of the first data set and the second data set and based on the time difference between the first point of time and the second point of time. The estimated mobility status of the vehicle is stored at multiple points of time in a vehicle-specific mobility status database.