Geofence Correction Algorithm for Vehicle Tracking Systems
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Solution Overview
Problem
Existing vehicle tracking systems fail to accurately identify and manage conflicts between user-defined geofences and frequently visited locations, leading to inefficiencies in geofence management and data analysis.
Innovation Solution
A computer system that includes a processor and storage medium programmed to receive GPS event data, analyze vehicle stops, and automatically identify frequent stop locations, determine conflicts with user-defined geofences, and correct geofence boundaries through a geofence correction algorithm, providing a graphical interface for user interaction and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If geofences are manually defined by users, then geofence management flexibility is improved, but conflicts with frequently visited locations cannot be automatically detected
Solution Approach 1:
The system automatically analyzes GPS event data to identify frequent stop locations and detects conflicts with user-defined geofences without requiring manual intervention. The computer system performs self-service by autonomously identifying conflicts and providing corrections, eliminating the need for users to manually detect or report geofence conflicts.
Solution Approach 2:
The system provides feedback to users by displaying detected geofence conflicts on a graphical map interface and offering automated corrections. This feedback mechanism allows users to review and approve conflict resolutions, ensuring that the automated conflict detection aligns with user intentions while maintaining operational flexibility.
2Productivity
If automated geofence correction is implemented, then conflict resolution efficiency is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary analysis of GPS event data to identify frequent stop locations before conflicts arise. By pre-processing the data and establishing a database of frequent stops, the system prepares conflict detection rules in advance, enabling efficient automated conflict resolution when geofence conflicts are detected without requiring complex real-time analysis.
3Measurement precision
If GPS event data is extensively analyzed, then frequent stop location accuracy is improved, but data processing time increases
Solution Approach 1:
The system applies partial analysis by focusing GPS event data processing on identifying frequent stop locations rather than analyzing all possible aspects of vehicle movement data. By selectively processing only the relevant portions of GPS data needed for geofence conflict detection, the system achieves accurate frequent stop location identification while minimizing unnecessary data processing time.
Data Source
AI summary
A system and method and system flow for identifying and correcting geofences.