Audio Sensor Collaboration for User Geo-Location and Health Tracking
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Solution Overview
Problem
Conventional home AI systems fail to distinguish between multiple users in a common environment, leading to limited personalization and requiring explicit user interaction for health monitoring, which is inconvenient and unnatural, especially in device-dependent systems.
Innovation Solution
A device-independent AI environment using collaborative audio sensors for geo-location and tracking of multiple users, allowing for continuous health condition monitoring without explicit user interaction, by classifying audio events and triangulating user locations for personalized AI interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional home AI systems process commands without voice analysis, then system simplicity is maintained, but the ability to distinguish between multiple users is lost
Solution Approach 1:
The patent introduces voice analysis as an intermediary mechanism between the user and the AI system. By analyzing voice characteristics, the system can identify which user is speaking without requiring explicit login or device interaction, thus resolving the contradiction between maintaining system simplicity and preserving user identification capability.
2Measurement precision
If users must explicitly identify themselves in conventional systems, then user identification accuracy is improved, but ease of operation deteriorates due to constant identification requirements
Solution Approach 1:
The system performs automatic user identification through voice analysis without requiring users to actively participate in the identification process. The AI system independently analyzes voice characteristics and determines user identity, eliminating the need for users to constantly log in or identify themselves, thus improving ease of operation while maintaining identification accuracy.
3Reliability
If health monitoring requires user interaction with wearable devices, then monitoring reliability is improved, but device dependency and user burden increase
Solution Approach 1:
The patent replaces the mechanical/wearable device-based health monitoring system with an acoustic field-based system. Instead of requiring users to wear sensors or interact with devices, the system uses audio sensors to detect health-related sounds (coughing, sneezing, breathing patterns) and environmental sensors to monitor conditions, thereby eliminating device dependency while maintaining monitoring reliability.
4Measurement precision
If location services rely on GPS coordinates of carried devices, then location accuracy is improved, but ease of operation deteriorates as users must carry devices
Solution Approach 1:
The system replaces GPS-based location tracking with acoustic triangulation. Audio sensors distributed throughout the environment detect sound waves from user devices or voices and use triangulation algorithms to determine user location, eliminating the need for users to carry GPS devices while maintaining location accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables natural AI interactions without the need for users to carry devices, providing real-time health monitoring and feedback, enhancing user experience by accurately tracking and responding to health conditions across different locations.
Implementation Method 1
audio sensors of the two or more of the plurality of geographically-dispersed AI sensors
Implementation Method 2
collaborative audio sensors for geo-location and tracking of multiple users
Data Source
AI summary
Audio sensors collaborate for geo-location and tracking of health conditions for multiple users. Different users can be independently geo-located and tracked within the AI environment. Location is determined from two or more AI clients of known locations that detect an event such as a human voice command to connect a call with a specific user. Responsive to classification of a health event of concern, in view of the estimated location, a command for an AI action, such as contacting a hospital server or adapting to monitor a suspected health condition, is received for a response to the health event at the AI clients that detected the health event, or others.