Particle Swarm Geolocation for Mobile Call Segments
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Solution Overview
Problem
Existing geolocation systems for mobile devices during calls are insufficiently accurate, especially when the device is moving, as they do not effectively utilize location information from neighboring call segments, leading to disjointed and noncontinuous geographical paths.
Innovation Solution
The method employs particle swarm operations and a modified multi-swarm approach to determine geolocation areas and segment locations by generating candidate particles based on probability distributions and trend lines, incorporating information from multiple call segments to improve accuracy and correlation between segment locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional geolocation methods are used for mobile devices during calls, then the system complexity remains low, but the location accuracy deteriorates especially when the device is moving
Solution Approach 1:
The patent divides the call into multiple call segments and determines geolocation areas for each segment separately. This segmentation allows the system to process location information in manageable units while maintaining overall accuracy across the entire call duration, resolving the contradiction between accuracy and complexity.
Solution Approach 2:
The patent introduces a new dimension by generating multiple candidate particles with different possible locations and using particle swarm optimization to search the solution space. This dimensional approach transforms the single-point location estimation into a multi-point probability distribution, improving accuracy without proportionally increasing system complexity.
2Measurement precision
If particle swarm operations with multiple candidate particles are used, then location accuracy improves, but computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by generating candidate particles based on probability distributions derived from geolocation areas before executing the full particle swarm optimization. This preliminary filtering reduces the search space and computational complexity while maintaining location accuracy.
Solution Approach 2:
The patent uses a limited number of candidate particles (e.g., 10-100 particles) rather than exhaustively searching all possible locations. This partial action approach provides sufficient accuracy for mobile device tracking without the excessive computational burden of complete enumeration, resolving the contradiction between accuracy and computational complexity.
3Stability of the object's composition
If information from multiple call segments is integrated, then continuity of geographical path improves, but processing time increases
Solution Approach 1:
The patent merges geolocation areas from multiple call segments by generating candidate particles that span across segment boundaries and using particle swarm operations to find consistent locations. This merging approach ensures continuity of the geographical path while processing segments efficiently in parallel, resolving the contradiction between path continuity and processing time.
Data Source
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AI summary
A device may include one or more processors. The device may obtain call information relating to a call. The call information may comprise a plurality of call segments. The device may perform one or more particle swarm operations to obtain approximate locations of the mobile device during at least some of the plurality of call segments. The device may combine the approximate locations to identify a location of the mobile device during the call.