IoT-Based Assessment of a Driver's Stress Level

Driver Monitoring Systems (DMSs) play a key role in preventing hazardous events (e.g., road accidents) by providing prompt assistance when anomalies are detected while driving. Different factors, such as traffic and road conditions, might alter the psycho-physiological status of a driver by increasing stress and workload levels. This motivates the development of advanced monitoring architectures taking into account psycho-physiological aspects. In this work, the authors propose a novel in-vehicle Internet of Things (IoT)-oriented monitoring system to assess the stress status of the driver. In detail, the system leverages heterogeneous components and techniques to collect driver (and, possibly, vehicle) data, aiming at estimating the driver's arousal level, i.e., their psycho-physiological response to driving tasks. In particular, a wearable sensorized bodice and a thermal camera are employed to extract physiological parameters of interest (namely, the heart rate and skin temperature of the subject), which are processed and analyzed with innovative algorithms. Finally, experimental results are obtained both in simulated and real driving scenarios, demonstrating the adaptability and efficacy of the proposed system.

• Record URL:
  • http://dx.doi.org/10.3390/s24175479
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/14248220
• Supplemental Notes:
  • © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
• Authors:
  • Mattioli, Veronica
  • Davoli, Luca
  • Belli, Laura
  • Gambetta, Sara
  • Carnevali, Luca
  • Sgoifo, Andrea
  • Raheli, Riccardo
  • Ferrari, Gianluigi
• Publication Date: 2024

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 5479
• Serial:
  • Sensors
  • Volume: 24
  • Issue Number: 17
  • Publisher: MDPI AG
  • ISSN: 1424-8220
  • Serial URL: http://www.mdpi.com/journal/sensors
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Drivers; Highway safety; Human factors; Internet of things; Monitoring; Stress (Physiology)
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01932244
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 30 2024 8:43AM