Offline Map Management via Predictive Location Segmentation
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Solution Overview
Problem
Users of mobile devices face challenges in managing offline map data, as it is unclear which maps to download and how to manage them effectively, especially when offline, and existing solutions do not proactively provide relevant maps based on user behavior or privacy concerns.
Innovation Solution
A computing device identifies relevant locations using location data and proactively requests offline map data from a server, allowing users to edit and manage downloaded maps, while preserving privacy by approximating location data and suggesting predefined maps for download, and periodically updating the maps to free up storage space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the device downloads map data for all possible locations, then the user can access maps offline anywhere, but the storage space is excessively consumed
Solution Approach 1:
The patent segments the map data by dividing it into discrete geographic regions or areas. Instead of downloading all map data at once, the system divides the global map into smaller manageable segments that can be downloaded and stored individually, allowing users to selectively download only the regions they need rather than consuming excessive storage space for all possible locations
Solution Approach 2:
The patent implements preliminary action by proactively predicting which map regions a user will need in the future based on their travel patterns, calendar events, and historical data. The system automatically downloads these predicted map regions in advance before the user actually needs them, ensuring offline availability while optimizing storage by only pre-downloading relevant areas
2Measurement precision
If the device requests exact location data from the server, then the map service can provide accurate offline maps, but user privacy is compromised
Solution Approach 1:
The patent introduces an intermediary mechanism where the device sends approximate or generalized location data to the server instead of exact coordinates. The server acts as a mediator that processes this anonymized location information to determine which map regions to provide, thereby maintaining location accuracy sufficient for map services while protecting user privacy by not exposing precise location details
Solution Approach 2:
The patent applies local quality by differentiating between the precision required for different purposes. For map rendering and navigation, high precision is maintained locally at the device level using the received map data. For communication with the server, lower precision approximate locations are used, creating different quality levels appropriate for each function - accurate maps offline without exposing precise location data online
3Reliability
If the device automatically downloads maps based on predicted locations, then offline map availability is improved, but the device complexity increases
Solution Approach 1:
The patent implements self-service by enabling the device to automatically predict future location needs and download corresponding map data without requiring user intervention. The system uses built-in sensors, calendar applications, and historical travel patterns to autonomously determine which maps to download, reducing the need for complex user configuration while improving offline readiness
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors actual user travel patterns and compares them with predictions. This feedback loop allows the system to learn from user behavior and improve its prediction accuracy over time, adjusting the complexity of the prediction algorithm based on actual usage patterns rather than maintaining maximum complexity regardless of need
4Quantity of substance
If the user manually selects and downloads each map, then storage space is optimized, but the ease of operation is reduced
Solution Approach 1:
The patent applies self-service by automatically managing map downloads based on predicted user needs. The system monitors user behavior, predicts future locations, and automatically downloads appropriate map data without requiring manual user selection. This maintains storage efficiency by downloading only needed maps while significantly improving ease of operation by eliminating the manual selection process entirely
Data Source
AI summary
In some implementations, a computing device can identify relevant locations using location data gathered by and/or entered into the device. In some implementations, the device can proactively request offline map data for the relevant locations. A server can identify offline map data responsive to the request and send at least a portion thereof to the device in response. In some implementations, the device can suggest downloading offline map data for the relevant locations to a user before requesting the data. The user may be able to edit the location and/or search for other locations to download. The device may provide features for managing downloaded offline map content automatically and/or in response to user input.