Dynamic Location Mapping System with Anonymity Protection
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Solution Overview
Problem
Current electronic location-based mapping systems fail to provide users with the ratio of males to females in a particular location, lack access to paid advertisements, and do not ensure user anonymity, making it difficult for individuals to find ideal locations based on demographic characteristics.
Innovation Solution
A dynamic location-based mapping system and method that uses a server with a processor to determine and display the count of males and females in blocks, protecting user anonymity while allowing access to local advertisements, enabling users to view population estimates and filter by interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current location-based mapping systems display user locations, then users can see where others are located, but user anonymity is compromised and demographic information cannot be protected
Solution Approach 1:
The system segments user location data by dividing the geographic area into blocks and aggregating user counts within each block rather than displaying individual user positions. This segmentation protects user anonymity while still providing useful location-based information about crowd density and demographics.
Solution Approach 2:
The system creates anonymized copies of user location data by replacing actual user identifiers with aggregated block-level statistics. Instead of showing real user positions, the system displays copied information in the form of user counts and demographic ratios for each block, maintaining utility while protecting privacy.
2Measurement precision
If the system displays detailed location information of individuals, then users can identify specific locations of other users, but this compromises user privacy and anonymity
Solution Approach 1:
The system divides the continuous geographic space into discrete blocks and aggregates user data at the block level. This segmentation reduces location precision from individual-level to block-level, thereby protecting user privacy while maintaining sufficient information for understanding crowd distribution and demographics.
Solution Approach 2:
The system changes the parameter of location information from precise individual coordinates to aggregated block-level statistics. By transforming the data representation from exact positions to statistical summaries (user counts, demographic ratios), the system maintains analytical value while eliminating privacy risks.
3Ease of operation
If the system aggregates large numbers of users into blocks, then user anonymity is protected, but the ability to locate specific clusters of people becomes difficult
Solution Approach 1:
The system segments the geographic area into a hierarchical structure of blocks, allowing users to navigate from larger to smaller blocks. This segmentation enables detection of clusters by comparing user counts across different block levels, maintaining anonymity while providing cluster location capability through the block hierarchy.
Solution Approach 2:
The system adds a hierarchical dimension to the block structure, allowing navigation and analysis at multiple levels of granularity. Users can detect clusters by examining user distribution across hierarchical levels, transforming the problem from two-dimensional precise location to multi-dimensional block hierarchy analysis.
Data Source
AI summary
A system for providing a geographic location based information having a server which comprises a transceiver which is operated to receive a request for the geographic location based information of the plurality of people and a processor to locate, to determine a count, to represent the count as a pair of counters in a plurality of blocks and update the count at each counter. A user interface is configured to display the plurality of blocks with the pair of counters. The cloud server dynamically stores/updates user settings and interests of all network devices, stores advertisers static locations and updates ads based off users inputs and populates stored information on universal map shared by all users and also receives request to filter user's map by a Label and determines all users in viewing window of map that have that Label saved in their profiles and then sends results to the user.