Sensor-Based Consent Gating for Personal Data Sharing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Facial recognition systems lack a mechanism to balance effective operation with user control over personal information, particularly in real-time consent for information extraction and sharing.
Innovation Solution
A dynamic consent mechanism that allows individuals to control the sharing of their personal information by moving into a consent region or making a predefined gesture, ensuring information is only shared if consent is given.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional sensor systems are used to detect persons, then detection capability is provided, but the systems are expensive, complex, and consume high energy
Solution Approach 1:
The patent replaces complex electronic sensor systems with a simplified acoustic detection system using a microphone and signal processing algorithms. Instead of using expensive proximity sensors, ultrasonic detectors, or infrared cameras, the system uses acoustic signals emitted by human bodies (breathing, heartbeats, movement) to detect and identify persons, thereby reducing device complexity while maintaining detection capability
Solution Approach 2:
The system creates an acoustic signature copy of a person's unique breathing and heartbeat patterns to enable identification. By capturing and analyzing these acoustic characteristics, the system can identify individuals without requiring complex biometric sensors, thus simplifying the overall system architecture
2Reliability
If conventional sensor systems are used to detect persons, then detection capability is provided, but energy consumption is high
Solution Approach 1:
The patent replaces energy-intensive electronic sensor systems with a low-power acoustic detection approach. The microphone and digital signal processing require significantly less energy than conventional proximity sensors, ultrasonic detectors, or thermal imaging systems, enabling prolonged operation on battery power while maintaining reliable person detection
Solution Approach 2:
The system leverages naturally occurring acoustic signals from human bodies (breathing, heartbeat, movement) rather than requiring active transmission of energy to detect persons. This passive detection method eliminates the need for high-power active sensors, dramatically reducing energy consumption
3Measurement precision
If acoustic signals are processed to identify persons, then identification capability is improved, but signal processing complexity increases
Solution Approach 1:
The patent segments the acoustic signal processing into distinct functional modules: noise filtering, feature extraction (breathing rate, heartbeat detection), pattern recognition, and identification. This modular approach organizes the complex processing tasks into manageable stages, making the system more tractable and implementable while achieving high identification accuracy
Solution Approach 2:
The system transforms complex acoustic waveforms into simplified parametric representations such as breathing rate, heartbeat frequency, and acoustic signature patterns. By converting raw signal data into meaningful parameters, the system achieves accurate person identification without requiring extremely complex processing algorithms
Data Source
Figure 1
Figure 2
Figure 3
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.