Network Geofencing with Uncertainty-Weighted Location Estimates
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Solution Overview
Problem
Current geofencing technologies face challenges in accurately locating user devices across diverse geographic scenarios, particularly indoors, due to limitations in location technology capabilities and high resource consumption, which can lead to battery depletion and increased costs.
Innovation Solution
A location tracking system that receives location estimates from user devices and determines uncertainty thresholds, causing multiple location requests when uncertainties exceed a defined threshold, and calculates weighted average locations using these estimates to improve accuracy while conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple location requests are provided to improve location accuracy, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system dynamically adjusts the frequency and number of location requests based on uncertainty thresholds. When location uncertainty exceeds the threshold, multiple location requests are triggered to improve accuracy. When uncertainty is within acceptable ranges, location requests are reduced or suspended, thereby optimizing battery consumption while maintaining required location precision
Solution Approach 2:
The geofencing system transitions from static continuous location tracking to dynamic conditional tracking. Location estimation frequency adapts based on real-time uncertainty measurements and threshold comparisons, enabling the system to intensify tracking only when necessary for accuracy while conserving energy during stable conditions
2Measurement precision
If advanced location technologies are deployed to improve location accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system automatically monitors location uncertainty and self-adjusts the location estimation frequency without requiring complex external control software. The uncertainty threshold mechanism enables the system to self-manage tracking intensity based on actual location stability, reducing the need for sophisticated software intervention
Solution Approach 2:
The system pre-defines uncertainty thresholds and decision rules for when to intensify or reduce location tracking. These predetermined parameters guide the adaptive behavior, eliminating the need for complex real-time decision algorithms and reducing software complexity
3Measurement precision
If continuous location tracking is performed to maintain geofencing accuracy, then measurement precision is improved, but loss of energy increases
Solution Approach 1:
Instead of continuous location tracking, the system implements periodic location estimation triggered by uncertainty threshold evaluations. Location requests are sent periodically only when uncertainty exceeds predefined thresholds, replacing continuous energy-intensive tracking with intelligent periodic sampling that maintains geofencing accuracy while reducing battery depletion
Data Source
AI summary
A device may receive multiple location estimates, with uncertainties, for the user device based on determining that the uncertainty is greater than or equal to the uncertainty threshold, and may store the location estimate, the multiple location estimates, and the uncertainties in a data structure. The device may identify a greatest uncertainty of the uncertainties, and may remove, from the data structure, location estimates and uncertainties associated with the greatest uncertainty to generate a set of location estimates and a set of uncertainties. The device may calculate a set of weights based on the set of uncertainties, and may calculate a set of weighted location estimates based on the set of weights and the set of location estimates. The device may calculate a weighted average location of the user device based on the set of weighted location estimates, and may provide the weighted average location to the user device.