Method for monitoring drunk driving by using wireless network and storable medium

Abstract

The invention discloses a method for monitoring drunk driving by using a wireless network and a storable medium, and relates to the field of intelligent detection. The method comprises the following steps: acquiring vital signs and mental movement coordination data; de-noising processing is performed on the vital sign and mental movement coordination data; inputting the vital signs and the mental movement coordination data into a self-attention convolutional neural network for processing; and predicting whether drunk driving occurs or not according to the self-attention convolutional neural network, and estimating the blood alcohol concentration (BAC) by using a random forest. The invention provides a series of signal processing methods and a self-attention convolutional neural network (namely C-Attention) integrating vital signs and mental movement coordination to realize a non-contact, non-intrusive and real-time drunk driving monitoring system.

Description

technical field [0001] The invention relates to the field of intelligent detection, and more specifically relates to a method and a storage medium for monitoring drunk driving by using a wireless network. Background technique [0002] Non-contact vital signs monitoring technology, vital signs are important indicators of physical and mental health. The use of wireless signals for non-contact vital sign monitoring has been extensively studied in recent years. For example, Received Signal Strength (RSS) of millimeter wave signals, etc. are used. However, all of these systems rely on proprietary hardware, such as radar. Therefore, some researchers have explored acoustic signals that can be easily captured by smart devices such as smartphones in vital sign monitoring. In this range, the BreathListener restores the breathing pattern according to the spectral density of the chest movement. Unfortunately, the perceived range of acoustic signals is small (approximately 30 cm), wh...

AI Technical Summary

Problems solved by technology

Unfortunately, the perceived range of acoustic signals is small (approximately 30 cm), which limits the use of these systems in scenarios such as heart rate monitoring in vehicles

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