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Related Experiment Video

Updated: Jun 13, 2025

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

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Published on: June 16, 2018

IoT-Based Assessment of a Driver's Stress Level.

Veronica Mattioli^1,2, Luca Davoli², Laura Belli²

¹Multimedia Laboratory, Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy.

Sensors (Basel, Switzerland)

|September 14, 2024

Summary

This study introduces an innovative in-vehicle system using wearable sensors and thermal cameras to monitor driver stress levels. The system effectively estimates driver arousal, enhancing road safety through advanced psycho-physiological assessment.

Keywords:

Driver Monitoring System Internet of Things IoT arousal thermal camera wearable

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Published on: December 18, 2020

Area of Science:

Human-Computer Interaction
Automotive Safety
Biomedical Engineering

Background:

Driver Monitoring Systems (DMSs) are crucial for preventing road accidents by detecting driving anomalies.
Driver stress and workload can be influenced by traffic and road conditions, impacting psycho-physiological status.
There is a need for advanced monitoring systems that incorporate psycho-physiological driver aspects.

Purpose of the Study:

To propose a novel in-vehicle Internet of Things (IoT)-oriented monitoring system for assessing driver stress.
To estimate the driver's arousal level, a key psycho-physiological response to driving tasks.
To develop an adaptable and effective system for real-time driver monitoring.

Main Methods:

Utilizing a wearable sensorized bodice and a thermal camera for data collection.
Extracting physiological parameters such as heart rate and skin temperature.
Employing innovative algorithms for processing and analyzing collected driver and vehicle data.

Main Results:

Experimental results were obtained from both simulated and real driving scenarios.
The proposed system demonstrated adaptability and efficacy in assessing driver stress levels.
Physiological data successfully correlated with driver arousal during driving tasks.

Conclusions:

The developed IoT-oriented system effectively monitors driver stress using physiological data.
The system shows promise for integration into future automotive safety technologies.
Advanced psycho-physiological monitoring can significantly contribute to preventing hazardous driving events.