Context-Based Reverse Geocoding for Mobile Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Mobile devices face challenges in accurately determining their location within geofenced areas due to factors like satellite positioning errors, noise, and interference from natural and built environments, leading to uncertainties in geographic coordinates and associated data.
Innovation Solution
Implementing context-based reverse geocoding methods that utilize a mobile device's current location, including latitude and longitude coordinates, along with patterns of movement such as speed and direction, to select the appropriate geofence among multiple intersecting ones, thereby determining the precise location within a geofenced area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or triangulation methods are used to determine geographic coordinates, then location data can be obtained, but measurement precision deteriorates due to satellite positioning errors, noise, and environmental interference
Solution Approach 1:
The patent introduces geofence selection criteria as an intermediary layer between raw GPS coordinates and final location identification. Instead of directly using potentially inaccurate coordinates, the system compares coordinates against predefined geofence boundaries and selection criteria (such as which geofence the device is most likely in based on movement patterns), thereby mediating the harmful effect of coordinate inaccuracies.
Solution Approach 2:
The patent applies preliminary action by pre-defining multiple geofences with selection criteria before location determination is needed. These geofences are established in advance with known boundaries and characteristics, allowing the system to proactively match observed coordinates and movement patterns against predetermined options rather than attempting to resolve coordinates after the fact.
2Adaptability or versatility
If multiple geofences intersect the current location, then more location options are available, but difficulty of detecting and measuring increases due to uncertainty in selecting the correct geofence
Solution Approach 1:
The patent applies dynamics by using movement patterns (speed, direction, trajectory) as dynamic criteria for geofence selection. Instead of relying solely on static coordinate matching, the system incorporates the device's motion characteristics to dynamically determine which intersecting geofence is most likely correct, allowing the selection process to adapt to the device's behavior.
Solution Approach 2:
The patent changes parameters by introducing movement pattern parameters (speed, direction, acceleration) in addition to spatial coordinates. This multi-parameter approach transforms the geofence selection problem from a simple coordinate-matching task into a multi-dimensional analysis that uses multiple varying parameters to disambiguate between intersecting geofences.
3Measurement precision
If context-based reverse geocoding is implemented, then location determination accuracy improves, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent extracts the computationally intensive geofence selection and context analysis from the mobile device and performs it on remote server systems. The device only needs to transmit its coordinates and basic movement data, while the server handles the complex logic of comparing against multiple geofences, analyzing movement patterns, and determining the correct location, thereby extracting the complexity burden from the device.
Solution Approach 2:
The system applies self-service by having the server automatically perform geofence selection and location determination without requiring complex client-side processing. The server autonomously analyzes the transmitted data, applies the geofence selection criteria, and returns the determined location, allowing the system to serve itself rather than requiring the device to perform complex computations.
Data Source
AI summary
In general, in one aspect, a mobile device can perform reverse geocoding based on context, in addition to latitude and longitude coordinates. The reverse geocoding can be used to determine in which geofence among multiple geofences the mobile device is located. Thus, the mobile device can be associated with a street address, a postal code, a named land feature, or a commercial, cultural, or political entity associated with the geofence. The context can include a pattern of movement, as well as an accuracy of the latitude and longitude coordinates. Information in the context can be compared to selection criteria of the geofence. A geofence having selection criteria that match the context the best can be selected.