Predicted Location Geo-Context Delivery for Mobile Devices
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Solution Overview
Problem
Mobile device platforms face limitations in delivering geo-context information due to constraints such as computing resources, operating system permissions, battery capacity, network connectivity, and bandwidth, which hinder precise location tracking and targeted advertising.
Innovation Solution
Implementing a system that uses predicted user locations to deliver geo-context information by employing a protocol that identifies datasets associated with predicted locations, utilizing locally stored location information, and adapting location refresh rates and notification data to overcome platform limitations and maintain relevance even without continuous network connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous location tracking and network connectivity are maintained to deliver precise geo-context information, then location precision and advertising relevance are improved, but battery power and network bandwidth are consumed excessively
Solution Approach 1:
The system performs preliminary actions by storing location information and geo-context data locally on the mobile device before network connectivity is lost. This allows the device to continue delivering relevant geo-context notifications using stored data without requiring continuous network connectivity or excessive battery power for real-time updates.
Solution Approach 2:
The patent implements local quality by enabling the mobile device to independently process and deliver geo-context information using locally stored location data and cached geo-context information. This reduces dependency on continuous network connectivity and minimizes battery consumption associated with constant network communication and centralized processing.
2Device complexity
If operating system region limits are enforced to conserve system resources, then device complexity and resource usage are reduced, but geo-context information coverage and advertising targeting capability are limited
Solution Approach 1:
The patent resolves the region limit constraint by transitioning from a single-dimension approach (tracking only active regions within OS limits) to a multi-dimensional approach that combines stored location information with predicted future locations. This allows the system to deliver geo-context notifications for regions beyond the current OS-imposed limits while maintaining acceptable system resource usage.
3Reliability
If location data is stored locally to maintain operation during network interruptions, then reliability is improved, but device memory and data storage requirements increase
Solution Approach 1:
The system extracts and stores only the essential elements needed for reliable geo-context notification delivery during network interruptions. This includes storing location information and associated geo-context information locally, while excluding redundant or non-essential data, thereby maintaining operation continuity without excessive data storage requirements.
4Loss of information
If frequent location updates are performed to maintain accurate geo-context information, then information relevance is improved, but network bandwidth and data transmission are consumed excessively
Solution Approach 1:
The system performs preliminary actions by caching geo-context information and location data locally before network connectivity is lost. This allows the device to continue delivering relevant geo-context notifications using stored data without requiring frequent network updates, thereby maintaining information relevance while conserving network bandwidth.
Data Source
AI summary
A server communicates with a mobile device to deliver a mobile application to the mobile device. Software instructions of the mobile application are executed on the mobile device. Then, responsive to operations of the software instructions on the mobile device, the mobile device sends messages comprising location data such as GPS data or other location point attributes. The server receives the location data describing the location of the mobile device and performs logic and computations to determine predicted location points, which are in turn used to determine predicted regions or areas surrounding the predicted location points. The server selects geo-specific notifications (e.g., advertisements, coupons, etc.) based at least in part on the predicted region, and transmits the geo-specific notifications electronically through the network to the mobile device. The notifications are determined based on geo-specific predictions, geo-specific rules, geo-specific triggers, geo-specific user data, geo-specific promotional data, and/or geo-specific context data.