Semantic Location API for Context-Aware Mobile Services
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Solution Overview
Problem
Current mobile computing devices lack an efficient method to determine semantic location information, which is essential for providing meaningful and context-aware services, while also ensuring user privacy and reducing resource consumption.
Innovation Solution
An application programming interface (API) is developed to determine semantic location information, including whether a user is stationary or in transit, and to provide a hierarchy of semantically identifiable locations, using sensor data and historical information, while allowing user consent and reducing redundant location determinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If semantic location information is determined using traditional GPS or signal triangulation methods, then location data can be obtained, but the system cannot provide context-aware semantic information about user state (stationary vs in transit) and location hierarchy
Solution Approach 1:
The patent introduces an intermediary service layer between raw location data collection and application usage. This service determines semantic location information by analyzing sensor data patterns to distinguish between stationary and in-transit states, and resolves location hierarchies. The intermediary processes GPS coordinates, signal strength, and device sensor data to produce context-aware semantic location information without requiring applications to directly implement complex location analysis logic.
Solution Approach 2:
The location determination system is designed to serve multiple functions through a single unified service. It simultaneously provides geographic coordinates, determines user movement state (stationary vs in transit), resolves location hierarchies (city, state, country levels), and supplies this information to multiple applications. This multi-functional approach eliminates the need for separate location determination mechanisms in each application while maintaining context-awareness.
2Productivity
If location information is determined for each application independently, then each application receives tailored location data, but resource consumption increases due to redundant location calculations
Solution Approach 1:
The patent merges location determination functionality into a single shared service that serves all applications. Instead of each application independently querying location data and triggering separate determination processes, multiple applications access a common location determination service that maintains a single active determination process. This consolidation combines location data collection, semantic analysis, and hierarchy resolution into one unified operation, significantly reducing redundant calculations and resource consumption while maintaining efficient location information delivery to all applications.
3Reliability
If continuous location monitoring is implemented to provide real-time semantic information, then up-to-date location data is available, but user privacy concerns increase and resource consumption rises
Solution Approach 1:
The system implements partial monitoring by determining location information only when changes are detected in sensor data patterns or when applications explicitly request updates. Rather than continuous monitoring, the system uses event-driven triggers based on significant changes in location state (e.g., transition from stationary to in-transit, or movement between location hierarchy levels). This partial action approach maintains reliability for critical location changes while reducing overall resource consumption and minimizing continuous surveillance that would raise privacy concerns.
Data Source
AI summary
The present disclosure provides systems and methods for determining semantic location information. In particular, one or more computing devices can receive, from an application program executing on at least one of the one or more computing devices, an application programming interface (API) call requesting semantic information about a location of at least one of the one or more computing devices. Responsive to receiving the API call, the one or more computing devices can determine semantic information for the location and can return the semantic information for the location to the application program via the API. The semantic information for the location can comprise data semantically identifying the location and indicating whether a user associated with the one or more computing devices is stationary at the location or in transit from the location.