Activity Tracking System Using Location Segmentation for Contextual Insights
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Solution Overview
Problem
Current fitness tracking technologies primarily provide basic accumulation of activity data without contextual information, failing to segment activities by location and provide interactive, contextually relevant insights for users to make informed health decisions.
Innovation Solution
Systems and methods that segment time into identification of locations associated with user activities, using geo-location data and learning logic to infer activities and provide contextual information, allowing users to view and interact with activity data on a device, including automatic association of events with locations and user feedback for location identification.
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 and location-specific insights are lacking
Solution Approach 1:
The patent segments activity data by geographic location, dividing the continuous activity stream into location-specific segments. This allows contextual information to be associated with specific locations while maintaining manageable data structures. The system creates location-based partitions of activity data, enabling targeted analysis without overwhelming system complexity.
Solution Approach 2:
The patent introduces geographic location data as an intermediary that connects raw activity data with contextual information. Location coordinates serve as the mediator that links physical activity measurements with environmental context, enabling the system to provide location-specific insights without directly coupling all data sources.
2Ease of operation
If activity data is collected without location segmentation, then data processing is straightforward, but users cannot make informed health decisions based on contextual awareness
Solution Approach 1:
The patent applies local quality by providing different types of activity analysis for different locations. Instead of uniform treatment of all activity data, the system tailors the information presentation to specific geographic contexts, allowing users to understand activity patterns in the context of where they occurred, thereby supporting more informed health decisions.
3Loss of information
If comprehensive location and activity tracking is implemented, then contextual awareness is improved, but data processing complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-segmenting activity data according to geographic locations before detailed analysis. Location boundaries and contexts are established in advance, creating a structured framework that simplifies subsequent processing. This preliminary organization reduces the complexity of handling comprehensive tracking data.
Data Source
AI summary
A method includes determining a location of a first monitoring device used while performing an activity. The first monitoring device is worn by a first user. The method includes determining a location of a second monitoring device used while performing an activity. The second monitoring device is worn by a second user. The method further includes determining whether the locations of the first and second monitoring devices are within a range and whether the activities are similar. The method includes sending a prompt to the first monitoring device upon determining that the activities are similar and the locations are within the range. The prompt includes a request for permission from a first user account to allow a second user account to access information from the first user account regarding the activity performed using the first monitoring device.