Dynamic User Profile Determination via Multi-Sensor Fusion
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Solution Overview
Problem
Existing geofencing applications in mobile devices rely solely on proximity to a point of interest (POI) to infer user behavior, which may not accurately reflect the user's current context or interests.
Innovation Solution
A method and apparatus for a mobile device to determine a dynamic user profile based on sensed indicators, such as wireless signals, inertial movements, environmental measurements, and encoded data files, to infer a current user behavior context and adjust location-based service functions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If geofencing applications rely solely on proximity to a point of interest to infer user behavior, then the system complexity is low, but the measurement precision of user behavior context is insufficient
Solution Approach 1:
The patent combines multiple sensing capabilities (GPS location, accelerometer motion detection, ambient light sensor, proximity sensor) into a unified user profile determination system. By merging these diverse sensors and their data streams, the system achieves comprehensive user behavior context accuracy without requiring any single sensor to be overly complex
Solution Approach 2:
The mobile device utilizes its existing multi-functional sensors for their primary purposes while also employing them for user behavior context determination. The accelerometer serves both motion detection for calls and behavior profiling; the GPS serves navigation and location-based service optimization. This multi-functionality approach improves measurement precision without adding dedicated complex hardware
2Measurement precision
If multiple sensed indicators are collected and processed to determine dynamic user profile, then the user behavior context accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of sensor data by continuously monitoring and pre-processing signals from multiple sensors in the background. User profile transitions are determined by comparing pre-processed data against stored patterns, allowing rapid response when user behavior changes without requiring intensive real-time computation
Solution Approach 2:
The system selectively processes only the necessary subset of sensor data required for determining user profile transitions, rather than continuously analyzing all available sensed indicators. The processor determines transitions based on relevant patterns in the data, performing partial processing that suffices for the task without the overhead of comprehensive analysis
Data Source
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AI summary
Methods, apparatuses and articles of manufacture for use in a mobile device to determine whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators. The dynamic user profile may be indicative of one or more current inferable user behavior contexts for a user co-located with the mobile device. The mobile device may transition a dynamic user profile from a first state to a second state, in response to a determination that the dynamic user profile is to transition from the first state to the second state, and operatively affect one or more functions performed, at least in part, by the mobile device based, at least in part, on the transition of the dynamic user profile to the second state.