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This study introduces a novel automotive system using IoT sensors to monitor driver/passenger physiological signals and environmental data in semi-autonomous vehicles. This technology aims to enhance road safety and enable timely medical intervention during emergencies.

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Area of Science:

  • Automotive Electronics
  • Internet of Things (IoT)
  • Biomedical Engineering

Background:

  • Rising vehicle numbers increase road accidents, causing fatalities and pollution.
  • Current safety systems lack comprehensive real-time monitoring of driver/passenger well-being.

Purpose of the Study:

  • To develop an integrated system for monitoring driver/passenger physiological signals and environmental conditions within vehicles.
  • To leverage IoT technology for real-time data acquisition and transmission for enhanced safety and health management.
  • To create a foundation for improved accident intervention and telemedicine services.

Main Methods:

  • Equipping semi-autonomous vehicles with specialized non-invasive sensors for Electroencephalogram (EEG) and Electrocardiogram (ECG) acquisition.
  • Implementing an IoT-based system for indoor temperature monitoring using MEMS technology.
  • Developing algorithms for data analysis, fusion, and real-time transmission of critical health information.

Main Results:

  • Successful design and integration of specialized EEG and ECG sensors within car seats.
  • Implementation of a multi-point IoT temperature monitoring system.
  • Demonstrated potential for real-time detection of dangers and abnormal vital parameters.

Conclusions:

  • The developed system effectively monitors driver/passenger vital functions, including fatigue and cognitive state.
  • The technology can significantly reduce accident risks in semi-autonomous and autonomous vehicles.
  • Integration with e-Call systems facilitates timely emergency response and telemedicine, potentially saving lives.