Wi-Fi CSI Occupant Detection for Enclosed Vehicle Interiors
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Solution Overview
Problem
Existing automotive safety systems fail to effectively detect the presence of living beings, such as infants or children, in confined spaces to prevent overheating-related injuries and deaths, relying on visual or audio data that are inadequate.
Innovation Solution
Utilizing channel state information (CSI) from Wi-Fi signals to train a neural network for detecting living beings by analyzing spectral content, leveraging existing Wi-Fi transmitters and receivers to identify the presence of adults, children, or infants in automotive interiors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual or audio data are used for detection, then the system structure is simple, but the detection precision is insufficient for living beings in confined spaces
Solution Approach 1:
The patent replaces visual and audio detection systems with a wireless signal-based detection system using channel state information (CSI) from Wi-Fi signals. This substitution enables precise detection of living beings through spectral analysis of wireless signal interactions with the environment, achieving high detection precision while utilizing existing wireless infrastructure to minimize additional system complexity
Solution Approach 2:
The patent introduces channel state information (CSI) as an intermediary between the wireless transmitter/receiver and the detection algorithm. The CSI captures environmental interactions of wireless signals, serving as a mediator that translates physical presence into detectable data patterns through spectral analysis, enabling indirect but accurate detection of living beings
2Reliability
If specialized detection equipment is deployed, then the detection reliability improves, but the manufacturing cost and device complexity increase
Solution Approach 1:
The patent makes existing Wi-Fi transmitters and receivers perform dual functions: their primary wireless communication function and the secondary function of detecting living beings through CSI spectral analysis. This multi-functionality approach achieves reliable detection without requiring specialized detection equipment, thereby maintaining ease of manufacture while improving detection reliability
Solution Approach 2:
The patent enables the existing wireless communication system to serve itself by utilizing its transmitted signals and received CSI data for detection purposes. The same infrastructure that provides wireless connectivity automatically generates the data needed for living being detection, eliminating the need for separate dedicated detection systems and reducing manufacturing complexity
3Ease of manufacture
If existing Wi-Fi infrastructure is utilized, then the cost is reduced and ease of manufacture is improved, but the detection precision for living beings may be insufficient
Solution Approach 1:
The patent applies spectral analysis to specific frequency portions of the CSI data where living being signatures are most prominent. By focusing computational resources on analyzing only the relevant spectral components rather than processing the entire signal spectrum, the system achieves high detection precision using standard Wi-Fi infrastructure without requiring excessive computational power or complex processing algorithms
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 a low-cost and efficient solution to detect the presence of living beings, preventing potential injuries or deaths by notifying users when children or infants are left unattended, enhancing safety in automotive environments.
Implementation Method 1
generating the training data based on a spectral analysis of the CSI data
Implementation Method 2
the training data is based on a Fast Fourier Transform (FFT) of the CSI data
Data Source
AI summary
Methods and apparatus for training a neural network to detect living beings in an enclosed space are disclosed. An example method includes obtaining channel state information (CSI) data based at least in part on a sequence of signals received at one or more receivers located in the enclosed space, generating training data for the neural network based at least in part on the CSI data, training the neural network using the training data to detect living beings in the enclosed space, and processing the trained neural network for deployment.