Driving Physiological State Monitoring Based on IoT Sensing Architecture

Abstract

In clinical practice, alcoholic beverages will have imaging effects on the autonomic nervous system.

Common reactions of the human body after absorbing alcohol include unsteady walking, rapid heartbeat, and

reddening of the face. In this case, humans are usually unable to fully rely on self-consciousness to manipulate

the body, and consciousness tends to become blurred. In recent years, the incidents of drinking and driving have

emerged in an endless stream. Although there are laws and regulations, they cannot effectively prevent and

control drunk driving. Therefore, this study intends to develop an alcohol lock that can monitor the

physiological state of driving.

The architecture proposed in this study uses the pulse oximeter to obtain the PPG signal and then analyzes the

autonomic nervous system and uses the MQ-3 alcohol sensor to detect the air alcohol content in the cockpit. The

two signals are sensed by ESP32 and sent to the base station outside the car by LoRa through the IoT

architecture. Finally, the driving physiological information will be sent to the server for centralized display