Activity Tracking Context via Location Segmentation
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Solution Overview
Problem
Current fitness tracking technologies primarily provide basic accumulation of activity data without context, failing to associate specific activities with locations, which limits users' ability to make informed health decisions based on their activity levels at different locations.
Innovation Solution
Systems and methods that segment time into identifiable locations, using activity and geo-location data to associate specific activities with contextual information, allowing users to view and interact with activity data on a device, including automatic location identification through mapping services and user feedback, and infer locations based on patterns and activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If basic activity data accumulation is provided, then data collection is simple, but contextual information about locations is lost
Solution Approach 1:
The patent segments activity data by geographic locations, dividing the continuous activity stream into location-specific segments. This allows contextual information to be preserved and analyzed separately for each location, resolving the contradiction between maintaining information and managing complexity through structured organization
Solution Approach 2:
The patent introduces mapping services and location databases as intermediary components between the activity tracker and the user. These intermediaries handle the complex tasks of geocoding, location matching, and contextual information retrieval, allowing the core tracking system to remain simple while still providing rich location context
2Loss of information
If activity data is collected without location association, then data processing is efficient, but user understanding of activity patterns is limited
Solution Approach 1:
The patent performs preliminary geocoding and location identification by converting coordinates to place names and addresses in advance. This preliminary action stores location context with activity data, eliminating the need for time-consuming real-time processing and preventing information loss about activity locations
Solution Approach 2:
The system uses automated mapping services and location databases to self-service the complex task of location association. The algorithm automatically matches coordinates with location data, performs geocoding, and associates activities with places without requiring manual user input, thus preserving location information while minimizing additional processing time
3Reliability
If detailed location analysis is provided, then health decision-making is improved, but data privacy concerns increase
Solution Approach 1:
The patent applies local quality by providing detailed location analysis only where necessary for health insights, rather than uniformly processing all location data. The system identifies and analyzes specific locations of health significance while maintaining privacy for other areas, allowing reliable health decisions without unnecessary privacy exposure
Data Source
AI summary
A method includes receiving activity of a monitoring device that is configured to be worn by a user having a user account. The activity includes an amount of movement of the monitoring device and occurs for a period of time. The method further includes receiving geo-location data for the monitoring device and processing the activity data and geo-location data received for the period of time. The operation of processing is performed to segment the period of time into at least two events. The method includes assigning an identifier to each event. The identifier has a default description for the geo-location data. The default description is selected from a plurality of descriptions based on the activity data obtained by the movement of the monitoring device for the geo-location data.