Radar Activity Recognition for Privacy-Safe Fall Detection
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Solution Overview
Problem
Conventional methods for monitoring human activities, such as using cameras or wearable devices, are unreliable and intrusive, often failing to accurately detect falls or other life activities in a home environment due to user compliance issues and privacy concerns.
Innovation Solution
A system utilizing a radar emitter and receiver with multi-core processors and artificial intelligence processes to process UWB and FMCW signals, employing a plurality of antenna arrays to detect and analyze radar reflections, determine activities, and trigger notifications, while minimizing wearability and intrusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cameras or wearable devices are used for monitoring human activities, then activity detection capability is improved, but user compliance and privacy protection deteriorate
Solution Approach 1:
The patent replaces mechanical/wearable sensing devices with radar-based electromagnetic sensing. The radar system uses electromagnetic waves to detect human activities, movements, and falls without requiring physical contact or wearables on the user's body. This substitution eliminates compliance issues while maintaining detection accuracy through advanced signal processing and AI algorithms that analyze radar reflections to identify specific activity patterns.
Solution Approach 2:
The patent introduces radar technology as an intermediary between the monitoring system and the user. Instead of direct observation through cameras or contact through wearables, the radar system indirectly senses user activities by detecting changes in electromagnetic wave reflections. This intermediary approach preserves user privacy and comfort while enabling accurate activity monitoring through sophisticated signal analysis of the intermediate radar echoes.
2Measurement precision
If cameras or wearable devices are used for monitoring human activities, then activity detection capability is improved, but privacy protection deteriorates
Solution Approach 1:
The patent replaces visual sensing (cameras) with electromagnetic radar sensing to eliminate privacy intrusion. Radar waves at the frequencies used are non-ionizing and harmless, and they do not capture visual images that could reveal sensitive personal information. The system processes only motion-related signal characteristics, deliberately avoiding any visual data collection, thus maintaining privacy while achieving accurate activity detection through pattern recognition in radar signal variations.
3Measurement precision
If radar technology with multiple antenna arrays and AI processing is used, then activity detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the radar system into multiple independent antenna arrays, each capable of transmitting and receiving signals. This segmentation enables the system to process signals from different spatial directions and perspectives simultaneously. The multiple arrays work in parallel to gather comprehensive spatial information about user activities, improving detection accuracy through multi-angle observation while allowing modular processing that manages system complexity through division of functions.
Solution Approach 2:
The patent employs dynamic signal processing and adaptive AI algorithms that adjust processing parameters based on real-time signal characteristics and detected activity patterns. The system dynamically optimizes its processing pipeline, activating different analysis algorithms based on the type of activity being monitored. This dynamic approach allows the complex system to adapt its complexity level to the specific monitoring task, maintaining high accuracy while managing computational resources efficiently.
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
Provides accurate and reliable detection of human activities, including falls, without the need for wearable devices, by using non-intrusive radar technology that can differentiate between static and moving objects, and integrate with other sensors for enhanced activity recognition.
Implementation Method 1
A system utilizing a radar emitter and receiver with multi-core processors and artificial intelligence processes to process UWB and FMCW signals, employing a plurality of antenna arrays to detect and analyze radar reflections
Data Source
AI summary
A method for a computing system includes beaming with a radar emitter from a central hub, a plurality of radar signals into an interior room, receiving with a radar receiver within the central hub, a plurality of radar reflections in response to the plurality of radar signals, processing with a processor within the central hub, the plurality of radar reflections to form a plurality of processed radar signals, determining with an AI processor within the central hub, at least one activity from a plurality of activities in response to the plurality of processed radar signals, and determining with a central processing unit within the central hub, a notification action to perform in response to the one or more activities.