Adaptive Stop Geofence Radius for Fleet Management
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Solution Overview
Problem
Current fleet management systems face inaccuracies in detecting arrival and departure times at stops due to overlapping geofence radii when stops are in close vicinity, leading to delayed and imprecise business inferences.
Innovation Solution
The implementation of an adaptive stop geofence radius system that dynamically adjusts the detection radius for each stop based on the distance to the nearest stop, ensuring non-overlapping geofences and accurate arrival and departure detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed geofence radius is used for all stops, then the detection system is simple to implement, but stops in close vicinity have overlapping geofences causing inaccurate arrival and departure detection
Solution Approach 1:
The patent applies dynamics by transitioning from a static fixed geofence radius to a dynamic adaptive radius that automatically adjusts based on the spatial relationship between stops. The system calculates the distance to the nearest stop and sets the radius proportionally, allowing geofences to dynamically adapt to varying stop densities along the route, thereby preventing overlaps in close vicinity stops while maintaining simplicity for spaced-out stops.
Solution Approach 2:
The patent implements parameter changes by modifying the geofence radius parameter based on the distance to the nearest stop. Instead of using a constant radius value, the system varies the radius parameter adaptively - smaller radii for closely spaced stops and larger radii for widely spaced stops, optimizing detection accuracy without requiring complex manual configuration.
2Reliability
If the geofence radius is increased to ensure detection, then arrival detection sensitivity improves, but geofence overlap with nearby stops increases causing false detections
Solution Approach 1:
The patent applies local quality by assigning different geofence radius values to different stops based on their local spatial context. Each stop receives a customized radius tailored to its specific distance from neighboring stops, rather than applying a uniform radius globally. This localized adaptation ensures reliable detection at each stop while preventing false detections from overlaps.
3Measurement precision
If manual geofence configuration is used, then detection accuracy can be optimized, but the system requires significant manual effort and time to set up
Solution Approach 1:
The patent implements self-service by enabling the system to automatically configure geofence radii without manual intervention. The system autonomously calculates distances between stops and determines appropriate radius values based on predefined proportional relationships, eliminating the need for manual geofence setup while maintaining optimized detection accuracy.
Solution Approach 2:
The patent applies preliminary action by pre-establishing the proportional relationship between stop distances and geofence radii. The system proactively calculates and configures appropriate radius values before the vehicle begins its journey, ensuring detection accuracy is optimized in advance without requiring time-consuming manual configuration during deployment.
Data Source
AI summary
Embodiments detect stops by an entity on a pre-planned trip that includes a plurality of stops. For each stop of the plurality of stops, embodiments determine a distance to a nearest stop and generate a geofence for each of the stops, each geofence having a radius having a size based on the distance. Embodiments detect the entity entering one of the geofences and, based on the detecting the entity entering one of the geofences, determine that the entity has stopped at a corresponding stop.