Sensor-Based Consent Detection for Privacy-Aware Identity Sharing
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Solution Overview
Problem
Facial recognition systems face challenges in balancing effective operation with user consent and control over personal information, particularly in real-time applications.
Innovation Solution
A dynamic consent mechanism that allows individuals to control the sharing of their personal information by detecting their consent state through behavior patterns, such as entering a predefined region or making eye contact, and only sharing extracted information once consent is given.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If facial recognition systems continuously extract and share personal information to maintain effective operation, then system functionality is improved, but user privacy and control are worsened
Solution Approach 1:
The patent implements dynamic consent management where the system continuously monitors user behavior patterns (eye contact, orientation, region entry) and adjusts information sharing status in real-time. The consent state is not static but dynamically updated based on current user actions, allowing the system to balance functionality with privacy by only sharing information when consent is actively detected.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring user behavior and using this information to adjust the consent state. The sharing function receives feedback from the consent state determination and modifies information sharing accordingly, creating a closed-loop system that responds to user preferences while maintaining operational effectiveness.
2Adaptability or versatility
If the system requests consent from every user before information extraction, then user control is improved, but system operation efficiency is worsened
Solution Approach 1:
The system allows users to self-express consent through natural behavior patterns such as eye contact, head orientation, and entering predefined regions. Instead of requiring explicit verbal or written consent, the system interprets user actions as consent indicators, making the consent process seamless and efficient while maintaining user control.
Solution Approach 2:
The system performs preliminary consent detection by monitoring user behavior patterns before proceeding with information sharing. The consent state is determined in advance based on detected behaviors, allowing the system to prepare for information extraction only when consent conditions are met, thus avoiding unnecessary processing delays.
3Measurement precision
If the system monitors behavior patterns continuously to detect consent, then consent detection accuracy is improved, but processing complexity is worsened
Solution Approach 1:
The patent divides the monitoring process into distinct functional modules: detection function for capturing sensor data, analysis function for interpreting behavior patterns, and determination function for deciding consent state. This segmentation allows each module to focus on specific tasks, improving detection accuracy while managing processing complexity through modular architecture.
Solution Approach 2:
The system applies different processing levels to different aspects of user behavior. Simple behaviors like region entry trigger immediate consent updates, while more complex behaviors like eye contact require additional analysis. This local quality approach optimizes processing resources by applying appropriate complexity only where needed.
Data Source
AI summary
There is provided a computer implemented method of extracting information about a person. Incoming sensor signals for monitoring people within a field of view of a sensor system are received and processed. In response to detecting a person located within a notification region, an output device outputs a notification to the detected person. Processing of the incoming sensor signals continues in order to monitor behaviour patterns of the person and determine from his behaviour patterns whether he is currently in a consenting or non-consenting state. An extraction function attempts to extract information about the person irrespective of his determined state. A sharing function determines whether or not to share an extracted piece of information about the person with a receiving entity in accordance with his determined state, the information not being shared unless and until it is subsequently determined that the person is in the consenting state.