Fall Detection via Thermal Imaging and WiFi CSI Fusion
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Solution Overview
Problem
Current fall detection methods, such as those using infrared thermal imaging and CSI technology, face challenges like low accuracy due to ambient temperature changes and co-frequency interference, and high costs associated with hardware devices like barometers and millimeter-wave radars.
Innovation Solution
A fall detection method and apparatus that utilize a combination of infrared thermal imaging and wireless network packet data to determine the speed of a target and network packet throughput, thereby improving the accuracy of fall detection and reducing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If infrared thermal imaging technology is used for fall detection, then the detection can be performed with existing hardware, but the accuracy deteriorates due to ambient temperature changes and illumination transformation
Solution Approach 1:
The patent combines infrared thermal imaging with WiFi CSI technology to form a hybrid detection system. The thermal imaging unit provides visual confirmation while the WiFi CSI provides motion vector data, and the fusion module integrates both data sources to improve overall detection accuracy while maintaining cost-effectiveness.
Solution Approach 2:
The patent introduces a fusion module as an intermediary that processes and integrates data from multiple sources (thermal imaging and WiFi CSI). This intermediary component reconciles the limitations of individual technologies by combining their strengths to achieve more reliable fall detection.
2Productivity
If CSI technology is used for fall detection, then motion detection can be achieved, but the accuracy deteriorates due to co-frequency interference from strong WIFI signals
Solution Approach 1:
The patent merges WiFi CSI data with thermal imaging data to compensate for the inaccuracies caused by co-frequency interference. While WiFi CSI provides motion detection capability, the thermal imaging serves as a verification mechanism, and the fusion module integrates both to maintain detection accuracy despite signal interference.
3Measurement precision
If barometer, sensor, and millimeter-wave radar hardware devices are used for fall detection, then detection accuracy can be improved, but the cost increases
Solution Approach 1:
The patent employs inexpensive off-the-shelf components including a thermal imaging unit and WiFi-based CSI measurement, replacing expensive specialized hardware like barometers, sensors, and millimeter-wave radars. This approach achieves adequate detection accuracy using low-cost consumer electronics.
Solution Approach 2:
The patent makes existing consumer electronics (thermal imaging cameras and WiFi routers) serve multiple functions: thermal imaging provides both visual detection and motion tracking, while WiFi CSI provides motion vector data. This multi-functionality eliminates the need for dedicated expensive fall detection hardware.
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
The proposed method enhances the accuracy of fall detection while reducing the cost associated with hardware devices, achieving this through a comprehensive analysis of speed and network packet throughput.
Implementation Method 1
a first speed of a to-be-detected target is determined according to an infrared thermal image captured by a thermal imaging unit
Implementation Method 2
network packet throughput and a second speed of the to-be-detected target are determined according to wireless network packet data transmitted by the wireless access point and collected by the radio frequency transceiver
Data Source
AI summary
A fall detection method is applied to a fall detection system including a thermal imaging unit, a radio frequency transceiver, and a wireless access point. The method includes the following steps: a first speed of a to-be-detected target is determined according to an infrared thermal image of the to-be-detected target captured by the thermal imaging unit within preset time; network packet throughput and a second speed of the to-be-detected target are determined according to wireless network packet data transmitted by the wireless access point and collected by the radio frequency transceiver within the preset time; and a detection result of a fall state of the to-be-detected target is generated and determined according to the first speed, the second speed, and the network packet throughput.